En vue de l'obtention du Délivré par : Institut National Polytechnique de Toulouse (INP Toulouse) Discipline ou spécialité : Interactions plantes-microorganismes Présentée et soutenue par : le vendredi 12 février 2016 Titre : Unité de recherche : Ecole doctorale : A PROTEASE OF THE SUBTILASE FAMILY NEGATIVELY REGULATES PLANT DEFENCE THROUGH ITS INTERACTION WITH THE ARABIDOPSIS TRANSCRIPTION FACTOR AtMYB30 Sciences Ecologiques, Vétérinaires, Agronomiques et Bioingénieries (SEVAB) Laboratoire Interactions Plantes Microorganismes (LIPM) Directeur(s) de Thèse : MME SUSANA RIVAS Rapporteurs : M. PATRICK GALLOIS, UNIVERSITY OF MANCHESTER M. SEBASTIEN BAUD, INRA VERSAILLES GRIGNON Membre(s) du jury : 1 M. JEAN-PHILIPPE GALAUD, UNIVERSITE TOULOUSE 3, Président 2 Mme SUSANA RIVAS, INRA TOULOUSE, Membre 2 M. THOMAS KROJ, CIRAD MONTPELLIER, Membre
Transcript
En vue de l'obtention du
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Délivré par :
Institut National Polytechnique de Toulouse (INP Toulouse)
Discipline ou spécialité :
Interactions plantes-microorganismes
Présentée et soutenue par :
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le vendredi 12 février 2016
Titre :
Unité de recherche :
Ecole doctorale :
A PROTEASE OF THE SUBTILASE FAMILY NEGATIVELY REGULATES
PLANT DEFENCE THROUGH ITS INTERACTION WITH THE
ARABIDOPSIS TRANSCRIPTION FACTOR AtMYB30
Sciences Ecologiques, Vétérinaires, Agronomiques et Bioingénieries (SEVAB)
1. PLANT-PATHOGEN INTERACTIONS AND PLANT IMMUNITY 12
1.1. PLANT-PATHOGEN INTERACTIONS 12
1.2. PLANT DEFENCE MECHANISMS: A MOLECULAR BATTLEFIELD 14
1.2.1. Constitutive defences 14
1.2.2. Inducible defences 16
· Pathogen-Triggered Immunity (PTI) 17
· Effector-Triggered Susceptibility (ETS) 20
· Effector-Triggered immunity (ETI) 22
1.2.3. Signalling events during plant defence responses 24
1.3. PLANT PROTEASES: ROLES IN LIFE AND DEATH DURING PLANT DEFENCE SIGNALLING 27
1.3.1. Aspartic proteases 29
1.3.2. Cysteine proteases 30
1.3.3. Metalloproteases 33
1.3.4. Serine proteases 33
· Carboxypeptidase-like proteases 34
· Subtilisin-like proteases or Subtilases 34
2. TRANSCRIPTIONAL REGULATION OF PLANT DEFENCE RESPONSES 41
2.1. AP2/EREBP TFS 42
2.2. BHLH TFS 43
2.3. BZIP TFS 43
2.4. BBX TFS 43
2.5. NAC TFS 44
2.6. WHIRLY TFS 44
2.7. WRKY TFS 44
2.8. MYB TFS 45
2.8.1. DNA MYB Binding Sites (MBSs) 46
2.8.2. Classification of MYB TFs 47
· 1R-MYB 47
· 2R-MYB (or R2R3-MYB) 47
· 3R-MYB (or R1R2R3-MYB) 48
· 4R-MYB 48
2.8.3. Functions of MYB TFs 49
2
2.9. TRANSCRIPTIONAL CONTROL IN PLANT DEFENCE (REVIEW ARTICLE) 51
3. ATMYB30 A POSITIVE REGULATOR OF THE HR IN A. THALIANA 52
3.1. IDENTIFICATION OF ATMYB30 52
3.2. EXPRESSION AND FUNCTION OF ATMYB30 52
3.3. HORMONAL CONTROL OF THE ATMYB30-MEDIATED HR 54
3.4. TRANSCRIPTIONAL TARGETS OF ATMYB30 55
3.5. REGULATION OF ATMYB30 56
3.5.1. Post-transcriptional regulation of AtMYB30 56
3.5.2. Post translational modification of AtMYB30 57
3.5.3. Regulation of AtMYB30 activity through protein-protein interactions 58
SCIENTIFIC CONTEXT OF THE PHD PROJECT 62
OBJECTIVES OF THE PHD PROJECT 63
RESULTS 64
A PROTEASE OF THE SUBTILASE FAMILY NEGATIVELY REGULATES PLANT DEFENCE THROUGH ITS INTERACTION WITH THE
ARABIDOPSIS TRANSCRIPTION FACTOR ATMYB30 65
Previous results: Identification of AtSBT5.2 as a new AtMYB30 interacting partner. 65
1. CHARACTERIZATION OF ATSBT5.2 66
1.1. AtSBT5.2 is alternative spliced and encodes two distinct isoforms. 66
1.2. AtSBT5.2(a) is a secreted protein whereas AtSBT5.2(b) is intracellular. 67
1.3. AtSBT5.2(a), but not AtSBT5.2(b), is glycosylated in planta. 68
1.4. AtSBT5.2(a) is an active serine protease. 70
2. CHARACTERIZATION OF THE INTERACTION BETWEEN ATMYB30 AND ATSBT5.2 73
2.1. Neither AtSBT5.2(a) nor AtSBT5.2(b) affect AtMYB30 protein accumulation in planta. 73
2.2. AtSBT5.2(b), but not AtSBT5.2(a), colocalizes with AtMYB30 in planta. 73
2.3. AtSBT5.2(b), but not (a), interacts with AtMYB30 in planta. 74
2.4. The AtSBT5.2(b)-AtMYB30 interaction is specific and mediated through AtSBT5.2(b) C-terminal
domain 75
2.5. AtSBT5.2(b) localization in intracellular vesicles is mediated through its N-terminal domain 76
3. FUNCTIONAL ANALYSIS OF ATSBT5.2 IN PLANT DEFENCE 78
3.1. AtSBT5.2 negatively regulates plant defence and HR. 78
3.2. AtSBT5.2 controls the HR via AtMYB30. 80
3.3. AtSBT5.2(b), but not AtSBT5.2(a), negatively regulates defence-associated cell death responses.
81
3.4. Analysis of AtSBT5.2 expression after bacterial inoculation. 81
DISCUSSION 83
1. AS, AN EMERGING REGULATORY MECHANISM OF PLANT DEFENCE 84
2. REGULATION OF ATSBT5.2 FUNCTION THROUGH AS 87
2.1. AS AFFECTS THE SUBCELLULAR LOCALIZATION OF RESULTING ATSBT5.2 PROTEIN VARIANTS 87
3
2.1.1. AtSBT5.2(b) localizes to endosomes 88
2.1.2. Endosomes as important sites for regulation of defence signalling 91
2.2. AS AFFECTS THE GLYCOSYLATION STATUS OF RESULTING ATSBT5.2 PROTEIN VARIANTS 93
2.3. AS APPEARS TO AFFECT THE CATALYTIC ACTIVITY OF RESULTING ATSBT5.2 PROTEIN VARIANTS 94
3. THE APOPLAST AS A PRIVILEGED SITE FOR ANTI-MICROBIAL DEFENCE 98
4. NUCLEAR EXCLUSION THROUGH INTERACTION WITH ATSBT5.2(B): A NEW REGULATORY MECHANISM OF
ATMYB30 ACTIVITY 100
MATERIALS AND METHODS 103
OTHER RESULTS 113
REFERENCES 115
4
Abbreviations A, Ala Alanine A Aa Alternaria alternataf.sp. lycopersici Ab Alternaria brassicicola ABA Abscisic Acid ABP Activity-Based Profiling AD Activation Domain AP2/EREBP APETALA2/Ethylene Responsive Element Binding ARF Auxin-Response Factor At Arabidopsis thaliana AtPLA2 Phospholipase A2 of Arabidopsis thaliana Atu Agrobacterium tumefaciens As Avena sativa (oat) AS Alternative Splicing BBX B-box protein B Bc Botrytis cinerea BD Binding Domain Be Botrytis elliptica bHLH basic Helix-Loop-Helix BR Brassinosteroid BRI1 Brassinosteroid Insensitive 1 BRS1 Brassinosteroid Insensitive Suppressor 1 Bt Botrytis tulipae bZIP basic Domain Leucine Zipper Ca Capsicum annuum (Pepper) C CC Coiled-Coil Cd Colletotrichum destructivum CDPK Calcium-Dependent Protein Kinase CEV Citrus Exocortis Viroid Cf Cladosporium fulvum CFP Cyan Fluorescent Protein CK Cytokinin Cv Cochliobolus victoriae D, Asp Aspartic Acid D DAMPs Damage-Associated Molecular Patterns Ea Erwinia amylovora E Ec Erysiphe cruciferarum EE Early endosome EF-Tu Elongation Factor Thermo-unstable ECM Extracellular Matrix Endo H Endoglycosidase H ER Endoplasmic Reticulum ET Ethylene ETI Effector-Triggered Immunity ETS Effector- Triggered Susceptibility FLS2 Flagellin-Sensing 2 F FRET-FLIM Förster Resonance Energy Transfer-Fluorescence Lifetime Imaging Fs Fusarium solani
5
GA Giberellic Acid G Gc Golovinomyces cichoracearum GFP Green Fluorescent Protein Gm Glycin max (Soybean) H, His Histidine H HA Hemagglutinin (HA)-epitope tag Ha Hyaloperonospora arabidopsis HLH Helix-Loop-Helix HR Hypersensitive Response hrp HR and Pathogenicity IF Intercellular Fluid I ISR Induced Systemic Resistance JA Jasmonic Acid J Le Lycopersicon esculentum (Tomato) L LE Late Endosom LRR Leucine-Rich Repeat lsd lesion simulating disease MAMP Microbe-Associated Molecular Pattern M MAPK Mitogen-Activated Protein Kinase MBSs MYB Binding Sites Md Malus domestica (Apple tree) Me Manihot esculenta (Cassava) MIEL AtMYB30-Interacting E3 Ligase Mo Magnaporthe oryzae MS Murashige and Skoog MYB Myeloblastom N, Asn Arginine N NAC NAM (No Apical Meristem), ATAF (Arabidopsis thaliana transcription
Activation Factor) and CUC2 (Cup-Shaped Cotyledon) NBS Nucleotide-Binding Site NLR Nucleotide-binding Oligomerization Domain-Like Receptor NLS Nuclear Localization Signal Nb Nicotiana benthamiana Nt Nicotiana tabacum Nu Nicotiana umbratica Os Oriza sativa (rice) O p35S The cauliflower mosaic virus promoter P PA Protease associated domain PAMP Pathogen-Associated Molecular Pattern PCD Programmed Cell Death PCR Polymerase Chain Reaction PD Prodomain PGNase F Peptide N-glycosidase F PGSs Putative N-glycosylation sites Phs Phytophthora sojae Pi Phytophthora infestans
6
PR Pathogenesis-Related PRR Pattern-Recognition Receptor Ps Pseudomonas syringae Pst Pseudomonas syringuae pv. tomato Pt Puccinia striiformis f. sp. tritici PTI PAMP-Triggered Immunity PTM Post Translational Modification Pv Plasmopara viticola pv. Pathovar RFP Red Fluorescent Protein R RLCK Receptor-Like Cytoplasmic Kinase RLK Receptor-Like Kinase RLP Receptor-Like Protein ROS Reactive Oxygen Species Rs Ralstonia solanacearum S, Ser Serine S SA Salicylic Acid SAR Systemic Acquired Resistance SBT Subtilase SCF Skp1, Cullin, F-box-type ligase Sf Spodoptera frugiperda Sl Solanum lycopersicum (Tomato) St Solanum tuberosum (Potato) SUMO Small Ubiquitin-like Modifier T2SS Type II Secretion System T T35S The cauliflower mosaic virus terminator T3SS Type III Secretion System Ta Triticum aestivum (Wheat) TAD Transcription Activation Domain TAL Transcription Activator-Like TF Transcription Factor TGN Trans Golgi Network TIR Toll-Interleukin1 Receptor TMD Transmembrane Domain TMV Tobacco Mosaic Virus Tn Trichoplusia ni Ub Ubiquitine U UPS Ub/Proteasome System UTR Untranslated Region VLCFA Very Long Chain Fatty Acid V Vv Vitis vinifera (Grapevine) Xcc Xanthomonas campestris pv. campestris X Xcv Xanthomonas campestris pv. vesicatoria Xoo Xanthomonas oryzae pv. oryzae Y2H Yeast Two-Hybrid Y YFPv Yellow Fluorescent Protein venus Zm Zea mays (Maize) Z
7
Figure list
Figure 1. Disease symptoms on Arabidopsis leaves caused by pathogens (From Pieterse et al., 2009).
Figure 2. Overview on the various types of interaction (Adapted from Nürnberger et al., 2004). Figure 3. The zigzag model illustrates the quantitative output of the plant immune system (Adapted from Jones and Danggl, 2006 and from Pieterse et al., 2009).
Figure 4. Schematic representation of systemically induced immune responses (Adapted from Pieterse et al., 2009).
Figure 5. Plant PRRs and their signalling adapters. Figure 6. Examples of plant targets of bacterial type III effector proteins (From Deslandes and Rivas, 2014).
Figure 7. Major families of R proteins. Figure 8. Model of integrated decoys in NLR protein pairs (From Cesari et al., 2014).
Figure 9. Major signalling mechanisms in plant defence (From Bigeard et al., 2015).
Figure 10. Classic model established for the hormonal control of the plant defence (Addapted from David De Vleesschauwer et al., 2013). Figure 11. Development of the hypersensitive response (HR) on tobacco leaf in response to Pseudomonas syringae pv. tomato DC3000 (http://www.sidthomas.net/images/hypersensitive.jpg).
Figure 12. Cleavage mechanisms of the four major catalytic classes of proteases (From van der Hoorn, 2008).
Figure 13. Classification and number of the catalytic types of Arabidopsis proteases (From van der Hoorn and Jones, 2004).
Figure 14. Protein structure of proteases.
Figure 15. Phylogenetic tree of Arabidospsis subtilases (From Rautengarten et al., 2005).
Figure 16. Plant MYB transcription factor classes (Adapted from Dubos et al., 2010).
Figure 17. Schematic illustration of different MYB protein classes and their functions (From Ambawat et al., 2013). Figure 18. Schematic representation of the relationships between the different Arabidopsis R2R3-MYB subgroups (From Dubos et al., 2010).
Figure 19. Schematic representation of the AtMYB30 protein.
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Figure 20. Analysis of AtMYB30 expression in Arabidopsis upon bacterial infection (From Daniel et al., 1999). Figure 21. Overexpression of AtMYB30 in tobacco leads to accelerated HR in response to inoculation with different pathogens (From Vailleau et al., 2002).
Figure 22. AtMYB30 modulates the expression of very long chain fatty acid (VLCFA)-related genes after bacterial inoculation (From Raffaele et al., 2008).
Figure 23. Schematic overview of metabolic pathways regulated by AtMYB30 during the incompatible interaction between Arabidopsis and avirulent bacterial pathogens (Adapted from Raffaele et al., 2008).
Figure 24. Simplified model for the simultaneous regulation of AtMYB30-mediated HR cell death through interaction with AtsPLA
2−α and MIEL1 (Adapted from Raffaele and Rivas,
2013). Figure 25. Interaction between AtMYB30 and AtSBT5.2 in yeast.
Figure 26. AtSBT5.2 is alternatively spliced.
Figure 27. Sequence alignment of AtSBT5.2(a) and AtSBT5.2(b) proteins.
Figure 28. Subcellular localization studies show that AtST5.2(a) is secreted whereas
AtSBT5.2(b) is intracellular.
Figure 29. Intercellular fluid isolation confirms that AtSBT5.2(a) is secreted whereas AtSBT5.2(b) is intracellular.
Figure 30. Schematic representation of AtSBT5.2(a) and AtSBT5.1 protein sequences.
Figure 31. Sequence alignment of AtSBT5.2(a) and AtSBT5.1 proteins. Figure 32. AtSBT5.2(a), but not AtSBT5.2(b), is glycosylated in planta. Figure 33. All PGS in AtSBT5.2(a) are used for glycosylation in planta.
Figure 34. AtSBT5.2(a) self cleaves in planta.
Figure 35. AtSBT5.2(a) is an active serine hydrolase.
Figure 36. Mutation of some glycosylated residues affects the catalytic activity of AtSBT5.2(a).
Figure 37. Neither AtSBT5.2(a) nor AtSBT5.2(b) affect AtMYB30 protein accumulation in
planta.
Figure 38. AtSBT5.2(b), but not AtSBT5.2(a), colocalises with and retains AtMYB30 outside
the nucleus.
9
Figure 39. AtSBT5.2(b)-mediated retention of AtMYB30 outside the nucleus is independent
of C-terminal tagging of the subtilase.
Figure 40. AtSBT5.2(b) does not affect AtMYB123 nuclear localization.
Figure 41. AtMYB30 and AtMYB123 colocalize in nuclei with both AtSBT5.2362-730
and
AtSBT5.1405-780
.
Figure 42. Sequence alignment of AtSBT5.2(b)362-730
and AtSBT5.1405-780
proteins.
Figure 43. AtMYB30 localization in intracellular vesicles is AtSBT5.2(b) N-terminal domain-
dependant.
Figure 44. Genetic analysis of AtSBT5.2 and AtSBT5.1 Arabidopsis mutant lines.
Figure 45. AtSBT5.2 negatively regulates HR development and plant resistance to bacterial inoculation.
Figure 46. AtSBT5.2 is a negative regulator of AtMYB30-mediated HR cell death.
Figure 47. Characterization of AtSBT5.2(a) and AtSBT5.2(b) overexpressing Arapidopsis
lines.
Figure 48. AtSBT5.2(b), but not AtSBT5.2(a), negatively regulates defence-related HR cell
death.
Figure 49. AtSBT5.2(b) and AtMYB30 expression profiles and induction rates overlap during
infection with avirulent HR-inducing bacteria.
Figure 50. Predicted effects of AS on the proteins encoded by AtSBT2.2, AtSBT3.6,
AtSBT4.11 and AtSBT4.12 splice variants.
10
Table list
Table 1. Genetic model of the gene for gene theory (From Flor, 1971).
Table 2. Role of proteases in plant defence.
Table 3. FRET-FLIM analysis shows that AtMYB30 physically interacts with AtSBT5.2(b) in
N. benthamiana epidermal cells.
Supplemental Information Table 1. Oligonucleotide primers used in this study.
Figure 1. Disease symptoms on Arabidopsis leaves caused by pathogens (From
Pieterse et al., 2009). Disease symptoms on Arabidopsis leaves caused by the necrotrophic fungus Botrytis cinerea (left),
the biotrophic oomycete Hyaloperonospora arabidopsidis (center) and the hemibiotrophic
bacterium Pseudomonas syringae (right). Photos: Hans van Pelt.
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1. Plant-pathogen interactions and plant immunity
1.1. Plant-pathogen interactions
Plants are primary producers and therefore a source of nutrients for many organisms
(Cardinale et al., 2011). To adapt to their habitat and maximize their chances of survival,
plants have developed both root and aerial systems, which, in turn, increases the range of
organisms that they can encounter. Many of these organisms, such as plant growth-
promoting rhizobacteria, are beneficial to the plant (Gopal et al., 2013) whereas other
organisms, including phytopathogenic insects, viruses, bacteria, nematodes, fungi, and
oomycetes, have a detrimental effect on plant long-term survival (Dangl and Jones, 2001).
According to their lifestyles, phytopathogens are classified into broad categories (Figure 1):
(i) necrotrophs that kill the host, often through the production of phytotoxins, before
parasitising it, extract nutrients from the cells and then live on dead tissue (such as the fungal
pathogen Botrytis cinerea usually called grey mould) and (ii) biotrophs that obtain nutrients
from living cells, commonly through specialized feeding structures (haustoria) that invaginate
the host cell without disrupting it and require a living host to continue their life cycle (such as
the oomycete pathogen Hyaloperonospora arabidopsis). Hemibiotrophs are microbes that
require a living host initially, but kill it at later stages of infection (such as the bacterial
pathogens Pseudomonas syringae or Xanthomonas campestris) (Glazebrook, 2005).
Bacteria and fungi adopt biotrophic, hemibiotrophic or necrotrophic modes of infection while
viruses are ideal biotrophs (although viral infection can eventually result in host cell death)
(Dangl and Jones, 2001).
Although plants must thus face the diversity of aggressive biotic agents, over-investing in
defence in the absence of infection can be just as detrimental to survival as disease (Brown,
2003). Indeed, plant resistance to disease is a costly response, closely connected to plant
physiological and developmental processes (Lozano-Durán et al., 2013, Fan et al., 2014,
Figure 2. Overview on the various types of interaction (Adapted from Nürnberger et
al., 2004).
Non host resistance/immunity
No pathogen differentiation on the
plant
Sufficient preformed defense
Compatible interaction
Incompatible interactions
Susceptibility/disease
Pathogen propagation on the plant
Insufficient preformed/inducible
defense
Host resistance/immunity
No pathogen propagation on the
plant
Race/cultivar-specific resistance
13
Malinovsky et al., 2014). In agreement, mutants with constitutively active defence responses
often present reduced growth and low fertility (Lorrain et al., 2003).
In parallel, the establishment of a parasitic relationship is dependent on the response of the
plant under attack. Indeed, to adapt to their hostile environment, plants have evolved
sophisticated mechanisms of protection to counteract constant pathogen attacks. Some of
these mechanisms are efficient against a broad range of pathogens, while others are limited
to specific pathogens. These mechanisms are based on an efficient immune system that
depends on cell-autonomous events, and on the ability to develop systemic signals from the
site of infection. Therefore, in host-pathogen relationships severe epidemics of disease
remain the exception rather than the rule (Burdon, 1987).
Interactions of pathogens with plants can either be compatible or incompatible. A
compatible interaction occurs when the pathogen infects a susceptible or a tolerant host
plant. In this case, the plant reacts more or less effectively to this aggression and the
severity of symptoms is variable. Symptoms of disease include death and destruction of host
tissue, wilting, abnormal growth and differentiation and discolouration of host tissue (Dangl
and Jones, 2001). If the plant keeps the ability to grow, the plant is tolerant. Otherwise, if the
plant develops a disease that alters its development, the plant is susceptible. Defence
mechanisms are triggered but in a manner that is too slow and/or too weak for the plant to
survive. The pathogen is qualified as virulent; it multiplies actively within the plant and
appears to be able to suppress the resistance mechanisms of the host (Nürnberger et al.,
2004) (Figure 2). For a biotroph to form a successful infection, it must establish a basic
compatibility with its host. The pathogen may also produce compatibility factors that delay,
avoid or negate recognition by a normally resistant host plant.
An incompatible interaction occurs when the pathogen encounters a non-host plant (non-
host resistance) or a resistant host plant (cultivar-specific resistance or host
resistance). In both cases, failure of the pathogen to invade host cells will prevent it from
14
colonising the host and the plant will be named resistant. The pathogen qualifies as
avirulent as it loses its pathogenicity. Resistant hosts prevent or slow the development and
reproduction of the majority of pathogens that they come into contact with. Resistance can
be expressed at many stages in the infection process, from inhibition of germination and
penetration, to restriction of colony development after entry. In the case of a resistant plant
two situations are possible. When an entire plant species is resistant to all races of a
microorganism that is pathogenic to other plant species, resistance is known as non-host
resistance (Senthil-Kumar and Mysore, 2013). Non-host resistance, therefore, is the most
common form of disease resistance exhibited by plants. Such broad-spectrum resistance
contrasts with host resistance, which is displayed by plant genotypes of susceptible host
species against a specific pathogen agent (Hammond-Kosack and Jones, 1997) (Figure 2).
Having introduced the bases of the interaction between plants and pathogens, the next
section provides an overview of the co-evolutionary forces and the molecular mechanisms
that determine the outcome of this interaction.
1.2. Plant defence mechanisms: a molecular battlefield
Plants, unlike mammals, lack mobile defender cells and a somatic adaptive immune system.
Instead, they rely entirely on their innate immunity and on systemic signals originating from
infection sites (Dangl et al., 2013). Indeed, in response to pathogen attack, plants have
developed complex, multilayered signalling and defence mechanisms to protect themselves.
Defence barriers and mechanisms used by plants represent a co-ordinated network of
molecular, cellular and tissue-based responses that can be classified into constitutive
(passive) and inducible (active) defences.
1.2.1. Constitutive defences
Pathogen initial invasion can be primarily prevented by preformed physical and/or chemical
barriers called constitutive defences. Physical barriers largely involve properties of the plant
15
surface such as the thickness of the cuticle of leaves, cuticular lipid, wax layers or the size of
stomatal pores. The cuticle is a layer coating the outer surface of epidermal cells of organs of
the aerial part of the plants and also present within seed coats (Serrano et al., 2014).
Composed of an insoluble cutin polymer matrix and interspersed with waxes (epicuticular
and intracuticular lipids), the cuticle protects from desiccation and acts as a mechanical
barrier against various abiotic and biotic stress, such as UV radiation and pathogens
(Serrano et al., 2014). In addition to its hydrophobic surface, a vertical leaf orientation can
also add to plant resistance, by preventing the formation of moisture films on the leaf surface,
thus inhibiting infection by pathogens reliant on water for motility. Some plants present a very
thick cuticle and bark, if present; can also prevent the entry of pathogens (Reina-Pinto and
Yephremov, 2009). Therefore, to enter inside the plant, microorganisms must force these
barriers or use wounds or natural openings such as stomata or hydathodes, naturally used
for gas exchange or water-excreting, respectively (Schwab et al., 2015). Stomatal aperture is
driven by specialized plant cells called guard cells (Assmann and Shimazaki, 1999) that
control openings by turgor pressure. This aperture is very tightly controlled by several plant
hormones, most notably abscisic acid (ABA) (Pillitteri and Dong, 2013). In the presence of
pathogenic bacteria and fungi, stomata close rapidly to prevent microbial entry (Gudesblat et
al., 2009). Hydathodes are specialized stomata. Since aperture of hydathodes is not
controlled by the plant, they particularly serve as pathogen entry points (Gu et al., 2013)
especially after a guttation period when the water droplet is sucked back into the plant.
If a microorganism reaches the intercellular space, called apoplast, it must face the plant cell
wall before entering the cell. Although the composition and structure of the cell wall differ
significantly in the relative amounts of its compounds among plant lineages, plant cell walls
are composed of a complex network of polysaccharides, including cellulose microfibrils
embedded in a matrix of pectin, hemicelluloses, lignin, and structural proteins (Loqué et al.,
2015). This composition serves as the plant exoskeleton providing mechanical support but it
also serves as a physical barrier, important for resistance to pathogens. Evidence of the role
Phase 1: PTI Phase 2: ETS Phase 3: ETI
Figure 3. The zigzag model illustrates the quantitative output of the plant immune
system (From Jones and Dangl, 2006 and Pieterse et al., 2009). (A) The zigzag model illustrates the intensity of the plant defence responses in place upon
pathogen interaction. In phase 1, plants detect microbial/pathogen-associated molecular
patterns (MAMPs/PAMPs, red diamonds) via Pattern Recognition Receptors (PRRs) to trigger
PAMP-triggered immunity (PTI). In phase 2, successful pathogens deliver effectors that
interfere with PTI, or otherwise enable pathogen nutrition and dispersal, resulting in Effector-
Triggered Susceptibility (ETS). In phase 3, one effector (indicated in red) is recognized by an
NB-LRR protein, activating Effector-Triggered Immunity (ETI), an amplified version of PTI that
often exceeds a threshold for induction of hypersensitive cell death (HR). In phase 4, pathogen
isolates are selected that have lost the red effector, or perhaps gained new effectors through
horizontal gene flow (in blue). These can help pathogens to suppress ETI. In phase 5, selection
favours new plant NB-LRR alleles that can recognize one of the newly acquired effectors,
resulting again in ETI.
(B) Molecular events occurring in phases 1 to 3 of the zigzag model.
(B)
(A)
PAMPs
Am
pli
tud
e o
f d
efe
nce
Threshold for HR
Threshold for effective resistance
PTI Effectors
ETS Low
High
Avr-R
ETI IHR
Ph
ase
1
Ph
ase
3
ETI
Effectors
Avr-R
Ph
ase
5
16
that the cell wall plays in resistance comes from pathogens that use mechanical force or
release cell wall degrading enzymes to overcome this barrier (Kubicek et al., 2014, Hématy
et al., 2009). For example, Erwinia spp produce pectinases to increase accessibility for other
enzymes like cellulases and xylanases and several other hydrolases to break down the
hemicellulose chains (Toth and Birch, 2005), which disrupt host cell integrity and thus
promote rotting (Toth et al., 2003). Even though in the past these structures have been
regarded as “passive”, research has shown that they are very dynamic and intricately
connected to “active” defences (Traw and Bergelson, 2003).
Beside the physical barriers against pathogen penetration, plants constantly produce various
chemical compounds that inhibit pathogen growth (Osbourn, 1996). These constitutive
chemical barriers include compounds such as antimicrobial compounds (also referred as
phytoanticipins) (Pedras and Yaya, 2015) or secondary metabolites (such as glucosinolates,
tannins, ...) (Ahuja et al., 2012, Bednarek, 2012).
1.2.2. Inducible defences
Pathogens that overcome passive defence layers are systematically perceived. Following
perception of invading microbes, plants use a two-tiered receptor-based immune system to
prevent infection (see below). This adapted defence response is mounted locally and has
been summarized in the zigzag model proposed by Jones and Dangl (Jones and Dangl,
2006), which decrypts the co-evolutionary molecular events driving the interaction between
plants and pathogens (Figure 3).
The outcome of the interaction, which varies according to the genetic determinants of each
organism, is also presented in this model. Local perception of a microorganism can, in
addition, trigger systemic defence responses that prime the plant for resistance against a
broad spectrum of pathogens. Systemic acquired resistance (SAR) and induced systemic
resistance (ISR) are systemic resistance responses that are extremely rapid and usually
Figure 4. Schematic representation of systemically induced immune responses
(Adapted from Pieterse et al., 2009). Systemic acquired resistance (SAR) is typically activated in healthy systemic tissues of locally
infected plants. Upon pathogen infection, a mobile signal travels through the vascular system to
activate defence responses in distal tissues. Salicylic acid (SA) is an essential signal molecule for
the onset of SAR, as it is required for the activation of a large set of genes that encode
pathogenesis-related (PR) proteins with antimicrobial properties. Induced systemic resistance
(ISR) is typically activated upon colonization of plant roots by beneficial microorganisms. Like SAR,
a long-distance signal travels through the vascular system to activate systemic immunity in above-
ground plant parts. ISR is commonly regulated by jasmonic acid (JA)-and ethylene (ET)-dependent
signalling pathways and is typically not associated with the direct activation of PR genes. Instead,
ISR-expressing plants are primed for accelerated JA-and ET-dependent gene expression, which
becomes evident only after pathogen attack. Both SAR and ISR are effective against a broad
spectrum of virulent plant pathogens.
17
involve an amplification of the initial response in distal tissues (Kothari and Patel, 2004)
(Figure 4).
SAR is characterised by the increased, broad spectrum resistance against pathogens
following a primary infection (Gozzo and Faoro, 2013). Development of SAR usually involves
the establishment of a slowly expanding necrotic lesion and other localised responses to
infection, the release of a signal originating from the infection site, and the subsequent
priming of the plant against further attacks, allowing a more rapid response in the case of
subsequent infections. This response is dependent on the plant hormone salicylic acid (SA)
and is associated with the transcriptional reprogramming of a number of defence genes,
including pathogenesis-related (PR) genes, leading to accumulation of PR proteins that
contribute to resistance due to their antimicrobial properties (Muthamilarasan and Prasad,
2013). The precise nature of the signal triggering SAR is still unknown. Although SA levels
increase around necrotic lesions and remain high in plants displaying SAR, a phloem-
translocated lipid molecule, and not SA itself, has been proposed as the SAR-inducing long
distance signal (Chanda et al., 2011, Maldonado et al., 2002, Chaturvedi et al., 2008) (Figure
4).
ISR is triggered by non-pathogenic root bacteria (for example, Pseudomonas fluorescens)
and confers effective resistance against a broad range of pathogens and insect herbivores
(Pieterse et al., 2014). In contrast to SAR, ISR seems to develop independently of SA and
PR gene induction and is rather dependent on the phytohormones jasmonic acid (JA) and
ethylene (ET) (Pieterse et al., 2009) (Figure 4).
· Pathogen-Triggered Immunity (PTI)
When a pathogen manages to penetrate the plant cell wall and reaches the periplasmic
space, it comes into contact with the plasma membrane of the host cell where it is exposed
to surface receptors that are capable of perceiving a great variety of microorganisms. This
detection generally occurs through the perception of microbial molecules, conventionally
Figure 5. Plant PRRs and their signalling adapters. (A) Domain structures for receptor-like kinases (RLKs) and receptor-like proteins (RLPs). The
kinase domain is absent in RLPs. SP: signal peptide; TMD: transmembrane domain; LysM:
lysine motif; LRR: leucine-rich repeats.
(B) Bacterial elicitors flagellin (flg22) and EF-Tu (elf18) are recognised by the Arabidopsis RLKs
flagellin sensing2 (FLS2) and EF-Tu receptor (EFR), respectively. FLS2, and EFR, oligomerise
with BRI1-associated kinase1 (BAK1) in a ligand-dependent manner. Chitin binds to
homodimers of the Arabidopsis lysine motif receptor kinase (LysM-RK) chitin elicitor receptor
kinase1 (CERK1) to induce immune responses. The Arabidopsis RLK PEPR1 recognises
endogenous AtPep peptides that act as danger-associated molecular patterns (DAMPs).
(B)
(A) RLP RLKs
LRR
TMD
SP
Kinase
LysM
Key:
BACTERIA DAMPs
AtPep
peptides
PEPR1
AtProPep
proteins
FLS2
Flagelin
(flg22)
EF-Tu
(elf18)
EFR
BAK1 BAK1
FUNGI
CERK1
Chitin
18
located at the surface of the microorganism called pathogen-associated molecular patterns
(PAMPs) or microbial-associated molecular patterns (MAMPs). PAMPs are typically
conserved and indispensable molecules, such as bacterial flagellin or chitin, a substance
found in fungi cell walls and the exoskeleton of insects and nematodes. However, PAMPs
can also be intracellular molecules being secreted or released from dead bacteria, which are
perceived by the plant [e.g. elongation factor (EF)-Tu]. These molecules are recognized by
cognate plasma-membrane-bound extracellular receptor proteins called pattern recognition
receptors (PRRs), on the external face of host cells. PRRs are typically plasma membrane-
bound receptor-like kinases (RLK)- or receptors-like proteins (RLP)- type proteins (Zipfel,
2014). These receptors present an extracellular leucine-rich repeat (LRR) or lysine motif
(LysM) domain allowing the recognition of "non-self" molecules, a transmembrane domain
(TMD) and a kinase domain in the case of RLKs, involved in signal transduction (Figure 5A).
Without a kinase domain, the short intracellular domain of RLPs associates with intracellular
kinase proteins in order to transduce an appropriate signal response (Böhm et al., 2014).
The Arabidopsis RLKs flagellin sensing2 (FLS2) and EF-Tu receptor (EFR) recognize
bacterial flagellin and EF-Tu, respectively, and are the best characterized plant PRRs (Zipfel,
2014). These and other examples of PRR proteins are shown in Figure 5B. It has recently
become clear that several RLKs require other RLKs for full function (Zipfel, 2014). Binding of
flg22 or elf18 (the immunogenic peptides of flagellin or EF-Tu in Arabidopsis, respectively) to
FLS2 or EFR, respectively, induces their instant association with the co-receptor RLK BRI1-
associated kinase1 (BAK1), phosphorylation of both proteins and initiation of downstream
responses (Roux et al., 2011, Schwessinger et al., 2011, Chinchilla et al., 2007) (Figure 5B).
RLKs interact also with soluble receptor-like cytoplasmic kinases. For example, Botrytis-
induced kinase1 (BIK1) and related PBS1-like (PBL) kinases constitutively associate with
FLS2 and EFR and become quickly phosphorylated and released from the PRR complexes
upon PAMP binding (Lu et al., 2010, Zhang et al., 2010). These associations play positive
regulatory roles in immunity (Böhm et al., 2014). To penetrate into the host cell, several
19
pathogens produce a range of cutin-degrading enzymes, which are often crucial for the
successful penetration of the plant tissue, and release cell wall or cuticular fragments. Plants
are also able to detect and respond to these endogenous molecules released by pathogen
invasion, called danger-associated molecular patterns (DAMPs), that are not available for
recognition under normal conditions. Polysaccharides released from the plant cell wall (e.g.
oligogalacturonides), and some endogenous peptides are DAMPs detected as “infectious
self”. When cell wall damage is detected, the cell wall is remodelled and reinforced at the
penetration site by formation of cell wall-associated structures like papillae (Hückelhoven,
2007). This reaction prevents infection of individual cells and stunts pathogen growth. The
first plant DAMP/PRR pairs have been recently identified. The Arabidopsis RLKs PEPR1 and
PEPR2 perceive AtPep peptides (Yamaguchi et al., 2006, Yamaguchi et al., 2010) (Figure
5B). These peptides are derived from the propeptides (AtProPeps) that are encoded by a
multigenic family of seven-members whose expression is induced by wounding or PAMP
perception (Krol et al., 2010). Treatment with AtPep peptides induces defence gene
expression and overexpression of AtProPep1 leads to enhanced resistance to the fungal root
pathogen Pythium irregulare. AtPep perception is part of a PTI amplification loop and is
important for the induction of systemic immunity (Zipfel, 2013).
Stimulation of PRRs triggers a set of complex signalling pathways leading to the
development of the first line of active defence responses formerly called basal or horizontal
immunity. This response is known as PAMP, DAMP or MAMP-triggered immunity (PTI, DTI
or MTI) and is sufficient to prevent the colonization of the microorganism in the plant (Beck et
al., 2012) (Figure 3). Functional PRRs and co-regulators are crucial for the success of PTI,
as mutant plants with a defective recognition system show increased susceptibility to
pathogens (Miya et al., 2007, Zipfel et al., 2006).
After pathogen detection, activation of PRRs induces a number of defence mechanisms such
as the establishment of structural and/or chemical barriers. Indeed, antimicrobial compounds
can be synthesized de novo in response to microbial attack. Such compounds are known as
20
phytoalexins. For example, when Pseudomonas syringae enters the plant via stomata,
recognition of flg22 by FLS2 stimulates production of reactive oxygen species (ROS), which
have direct antimicrobial properties but also serve as signalling molecules to activate further
immune outputs (O'Brien et al., 2012), cell walls are reinforced by callose, lignin and suberin
deposition for extra protection (Senthil-Kumar and Mysore, 2013) and production and
secretion of molecules (such as camalexin) and defence-related proteins/peptides (such as
PR1) is induced (Bigeard et al., 2015, Bednarek, 2012, Ahuja et al., 2012, Melotto et al.,
2008). This recognition also leads to closure of stomata to limit bacterial entry (Sawinski et
al., 2013). Moreover, certain proline-rich proteins of the cell wall become oxidatively cross-
linked after pathogen attack in an H2O2-mediated reaction. This process strengthens the cell
wall in the vicinity of the infection site, increasing resistance to microbial penetration
(Morimoto et al., 1999). In response to cell wall degrading enzymes secreted by
phytopathogenic microorganisms, plants have evolved a diverse battery of defence
responses including protein inhibitors of these enzymes. These include inhibitors of pectin
degrading enzymes such as polygalacturonases, pectinmethyl esterases and pectin lyases,
and hemicellulose degrading enzymes such as endoxylanases and xyloglucan
endoglucanases (Juge, 2006).
All these defensive reactions, together with passive defences, build up a so-called basal
resistance that is regarded as non-specific as it is activated regardless of the
microorganism encountered. Ultimately, basal defence generally contributes to halt infection
before the microbe gains a hold in the plant allowing resistance to a variety of
phytopathogenic organisms. However, during evolution, some pathogens developed various
strategies to counter this first line of plant defence and acquired the ability to induce the
development of symptoms leading to disease and even the death of the plant.
· Effector-Triggered Susceptibility (ETS)
Successful pathogens such as bacteria, fungi, oomycete, and nematodes have evolved
strategies to circumvent PTI responses and are able to promote pathogenesis by delivering a
Figure 6. Examples of plant targets of bacterial type III effector proteins (From
Deslandes and Rivas, 2014). At the plasma membrane (PM), activation of the receptor complexes, for example, Flagellin-
Sensitive2/BRI1-Associated Kinase1 (FLS2/BAK1) or EF-Tu receptor/BAK1 (EFR/BAK1), by recognition
of conserved bacterial pathogen-associated molecular pattern (PAMP) molecules triggers PAMP-
triggered immunity (PTI)-associated signalling. Phytopathogenic bacteria inject type III effector (T3E)
proteins into plant cells using the type III secretion system (T3SS). Following their translocation into
plant cells, T3Es may be addressed to different subcellular compartments where they may manipulate
a variety of host cellular functions. Recognition of the activity of T3Es by R proteins triggers effector-
The cytoplasmic kinase proteins Pto and Fen act as molecular mimics of host virulence targets of
AvrPto and AvrPtoB to activate ETI. AvrPto, AvrPtoB, AvrB, AvrRpm1, AvrRpt2, and HopF2 target the
negative regulator of defence RPM1-interacting protein4 (RIN4) at the PM. AvrAC targets immune
kinases at the PM. HopZ1a, recognized by the R protein ZAR1, targets 2-hydroxyisoflavone
dehydratase (GmHID1), which is involved in isoflavone biosynthesis, and tubulin, which affects the
cellular microtubule network. Cleavage of PBS1 and additional related kinases (BIK1 and PBL1) by
AvrPphB is recognized by the R protein RPS5, triggering ETI. HopI1 and HopN1 are addressed to the
chloroplast where they respectively target the chaperone protein Hsp70, suppressing salicylic acid (SA)
accumulation, and the Photosystem II-associated protein PsbQ, diminishing reactive oxygen species
(ROS) production. HopM1 accumulates in the trans-Golgi network/early endosome (TGN/EE) where it
targets AtMIN7, a key component of vesicle trafficking, thereby suppressing cell wall-associated
defences. HopF2, HopAI1, and AvrB target mitogen-activated protein kinase (MAPK) signalling. In the
nucleus, the Transcription Activator-Like (TAL) effector AvrBs3 is able to mimic eukaryotic
transcription factors (TFs) and directly activate transcription. AvrBs3 binding to the UPA box in host
promoters induces plant cell hypertrophy, contributing to disease development. By contrast, in
resistant plants, activation of the resistance gene Bs3 leads to HR development. The effector protein
XopD targets the Arabidopsis TF AtMYB30, which a positive regulator of Arabidopsis defence
responses. This protein interaction results in repression of AtMYB30 transcriptional activation and
suppression of plant HR and defence responses. PopP2 induces nuclear relocalization of the vacuolar
protease RD19 and perception of PopP2 activity by the R protein RRS1-R activates immunity. HopU1
ribosylates GRP7/8 probably altering immunity-related RNA metabolism. Both HopA1 and AvrRps4
target the enhanced disease suceptibility1 (EDS1) immune regulator disrupting its association with
various immune surveillance proteins, including RPS4. Host targets are underlined.
21
battery of secreted molecules called effectors at the extracellular space of host plant cells
(apoplastic effectors) or inside plant cells (cytoplasmic effectors) (Win et al., 2012).
Therefore, by targeting PTI signalling (Zhang et al., 2007) or PTI receptors (Chaparro-Garcia
et al., 2015) these effectors can suppress PTI, thus resulting in effector-triggered
susceptibility (ETS) (Figure 6). During the past few years, the molecular functions of a
significant number of effectors from various phytopathogens have been discovered, revealing
an astonishing number of eukaryotic processes that are targeted by effector proteins
(Deslandes and Rivas, 2012). Apoplastic effectors are able to prevent PAMP recognition and
PRR activation, as well as chitinase or protease action (Asai and Shirasu, 2015). Pathogen
effectors delivered inside host cells suppress defence responses by targeting components of
defence signalling (details on signalling events triggered upon pathogenic infection are
provided in the next section) (Feng and Zhou, 2012). Host-translocated (cytoplasmic)
effectors are delivered into host plant cells via the type III secretion system (T3SS) (Galán et
al., 2014) or through specialized infectious structures called haustoria that are formed within
the host cell during infection (Giraldo and Valent, 2013). In plant-pathogenic bacteria, genes
encoding components of the T3SS are located in so-called hrp (HR and Pathogenicity) gene
clusters, as their mutation typically disrupts bacterial ability to cause disease on host plants
and to elicit a hypersensitive response (see section 3) on non-host plants (Tang et al., 2006).
The hrp cluster is conserved among Gram negative bacteria including Pseudomonas
syringae, Xanthomonas spp., Ralstonia solanacearum and Erwinia spp. (Galán et al., 2014).
Although the bacterial T3SS has been well studied (Galán et al., 2014), the mechanisms of
effector translocation by filamentous pathogens are still under debate (Giraldo and Valent,
2013). Once inside host cells, effectors subsequently traffic to distinct compartments
including the nucleus (Sarris et al., 2015), the plasma membrane (Wu et al., 2011), the
endoplasmic reticulum (ER) (Block et al., 2014), the tonoplast (Caillaud et al., 2012),
intracellular vesicles (Nomura et al., 2011), chloroplasts (Petre et al., 2015) or the
microtubule network (Lee et al., 2012). Figure 6 presents a general, not exhaustive, view of
the diversity of cellular processes targeted by type III effectors (T3Es) to promote disease.
Figure 7. Major families of R proteins. Representation of the location and structure of the main classes of plant disease resistance
proteins. The majority of R proteins contain tandem leucine-rich repeats (LRRs, depicted in blue),
which have a major role in recognition specificity. The most widely represented R protein family
consists of Nucleotide-Binding site–LRRs (NB-LRRs) proteins that contain a nucleotide-binding site
and a region of similarity to proteins that regulate PCD in metazoans. NB-LRR proteins are likely
localized in the cytoplasm, perhaps as peripheral membrane proteins. Some NB-LRR proteins
contain a putative coiled-coil domain (CC) at the N-terminus. Other NB-LRR proteins contain a
domain with homology to the metazoan superfamily of Toll-like innate immunity receptors (TIR).
Another class of R protein consists of an extracellular LRR (eLRR) anchored to a TM domain.
LRR
RLP (Cf-proteins)
CC
NBS
LRR
(RPM1,
RPS2) (RPS4,
RPS6)
TIR
NBS
LRR
NB-LRRs
Cytoplasm
Pla
sma
me
mb
ran
e
Nucleus
Apoplasm
22
· Effector-Triggered immunity (ETI)
Just as pathogens have evolved to disable plant defences, plants have gained the ability to
recognize and respond to these effector-mediated attacks. Indeed, plants have evolved a,
more efficient and specific, second line of active defence to recognise and protect
themselves from sneaky invaders. To detect effectors, or their interference with host
proteins, plants have developed receptors called resistance (R) proteins. The A. thaliana
Columbia (Col-0) accession presents around 150 R genes in its genome (Meyers et al.,
2003). A majority of R proteins belongs to the intracellular nucleotide-binding leucine-rich
repeat receptor (NLR or NB-LRR) protein family (Jones and Dangl, 2006) that displays
striking similarities with animal nucleotide-binding oligomerization domain-like receptors
(NLRs) or CATERPILLER proteins (Rairdan and Moffett, 2007, Inohara and Nuñez, 2003).
NLR proteins are multidomain proteins and possess a conserved architecture including a
central nucleotide binding site domain (NBS) and a C-terminal LRR domain (Takken and
Goverse, 2012) (Figure 7). Based on the presence in their N-terminal domain of either
Toll/Interleukin-1 receptor (TIR) or coiled-coil (CC) motifs, NLR proteins fall into two major
structurally distinct sub-classes named TIR-NB-LRR (TNL) or CC-NB-LRR (CNL),
respectively (Bonardi et al., 2012). Other R proteins belong to the group of eLRR
(extracellular LRR) domain proteins. This includes mainly the Receptor-Like Protein (RLP)
family characterized by an extracellular LRR domain, a TMD and a short cytoplasmic domain
(Muthamilarasan and Prasad, 2013) (Figure 7). The best characterized R proteins of this
class are Cf proteins which confer resistance of tomato to the fungal pathogen Cladosporium
fulvum (Rivas and Thomas, 2005).
This mode of recognition leads to co-evolutionary dynamics between the plant and the
pathogen that are quite different from those associated to PTI as, in contrast to PAMPs,
effectors are dispensable molecules although usually necessary for pathogenicity. This
specific recognition represents the second line of active defence known as specific
Figure 8. Model of integrated decoys in NLR protein pairs (From Cesari et al., 2014). Pathogen effectors target host proteins for manipulation in order to promote infection.
(A) Indirect recognition of effectors occurs when target proteins are guarded by host NLR
proteins,
(B) or if duplicated target genes evolve to encode decoy proteins monitored by host NLRs.
(C) Alternatively, the decoy may be integrated into the structure of the receptor component of an
NLR pair, allowing effector recognition by direct binding.
Pathogen genotype
Plant genotype Avr (Avirulent) avr (virulent)
R (Resistant) Resistance (HR) Disease
r (Susceptible) Disease Disease
Table 1. Genetic model of the gene for gene theory (From Flor, 1971). The resistance of the plant, often associated with the HR, is only established if the plant carries an
R gene corresponding to an Avr gene in the pathogen. In all other cases, disease occurs.
(A) Guard model
(B) Decoy model
(C) Integrated decoy model
23
resistance and commonly termed effector-triggered immunity (ETI) (Jones and Dangl, 2006)
(Figure 3).
Variation in host resistance is often controlled by the segregation of single R genes
(Hammond-Kosack and Jones, 1997). The genetic interaction underlying the induction of this
type of resistance is typically explained by the "gene for gene" model (Flor, 1971). This
classic concept is based on the observation that a plant carring a dominant resistance gene
(R) is resistant when it interacts with a pathogen that expresses a dominant and
complementary effector protein historically called avirulence protein (Avr). In the absence
of the R protein and/or the corresponding avirulence protein, the pathogen is not detected by
the plant, which results in the establishment of disease (Table 1) (Gassmann and
Bhattacharjee, 2012). The first biochemical interpretation of this hypothesis was a receptor–
ligand model that implies that plants activate defence mechanisms upon R-protein-mediated
recognition of pathogen-derived Avr gene products (Table 1).
More recent studies showed that direct recognition of Avr gene products by R proteins is the
exception rather than the rule and that a more prevalent mode of recognition exists that
involves indirect interaction mediated by accessory-proteins that the immune receptor
associates with and in which it recognizes effector-induced modifications. These accessory
proteins that mediate indirect recognition may either be direct virulence targets of the effector
(guard model) (Dangl and Jones, 2001, Dodds and Rathjen, 2010) (Figure 8-A) or decoy
proteins that the plant has evolved to mimic real effector targets (decoy model) (Hou et al.,
2011, van der Hoorn and Kamoun, 2008) (Figure 8-B). In some cases,a decoy protein fused
to a member of an NLR pair may act as bait to trigger defence signalling by a second NLR
member upon effector binding (integrated decoy model) (Cesari et al., 2014, Delga et al.,
2015) (Figure 8-C).
Figure 9. Major signalling mechanisms in plant defence. PAMPs perception by PRR induces rapid (seconds) immune receptor complex formation at the
plasma membrane and different auto- and transphosphorylations of the actors involved (1). BIK1
becomes quickly phosphorylated and released from the PRR complex (2). Phosphorylated Botrytis-
induced kinase1 (BIK1) has a higher binding affinity for respiratory burst oxidase homolog D
(RBOHD) and phosphorylates it (3). At the same time, BIK1 also activates Ca2+ channel(s) and
induces Ca2+ influx. A Ca2+ burst occurs (30 s to 2 min) and reaches a peak at around 4–6 min (4).
This Ca2+ influx induces opening of other membrane channels (influx of H+, efflux of K+ and Cl–),
which leads to extracellular medium alkalinization (1 min) and depolarization of the plasma
membrane (1–3 min) (5). A ROS burst then rapidly occurs (2–3 min) via RBOHD and peaks at
around 10–14 min (6). Full activation of RBOHD requires phosphorylation by BIK1 and Ca2+-
induced Calcium-dependent protein kinases (CDPKs) (6). Ca2+ also regulates RBOHD through direct
binding or modification of the protein (6). RBOHD produces O2.– in the apoplast, which is
converted into H2O2 by superoxide dismutases (SOD) (7). H2O2 can enter the cytosol and the
different organelles of the cell and is capable of inducing cytosolic Ca2+ elevations (8). 14-3-3
proteins modulate the activity of RBOHD and CDPKs (9). Effector recognition induces rapid
immune response (10). Mitogen-activated protein kinase (MAPK) modules are activated in a few
minutes leading to transcription factor (TF) activation (11). TFs participate in the regulation of
several thousand genes (12). SA, JA, and ET signalling pathways then contribute to downstream
regulation of gene expression (13). Crosstalks also occur with other phytohormones (14). This
complex signalling network finally leads to the implementation of plant-induced defences, such as
the production and secretion of antimicrobial compounds and the generation of toxic ROS (15).
Arrows denote enzymatic pathways, transport, or regulation (see text for more details). ABA:
proteases. Each protease class consists of several clans of proteases, which are identified by a
letter following the catalytic class (e.g. clan CA within class C). Members of a single clan are
believed, on the basis of their conserved tertiary structure and order and spacing of catalytic
residues, to have a common evolutionary origin. Proteases of clans starting with the letter ‘P’ can
have different catalytic residues. Each clan of proteases consists of several families which are
identified by a number following the catalytic type (e.g. family C1 within clan CA). Not all clans and
families of plant proteases are represented in Arabidopsis. The number of proteases belonging to
each family is indicated by bars, and the classification of well-studied proteases is indicated.
Table 2. Protease in plant defence (Part I).
Class Clan Family Group Name
Plant
species(a) Function in plant immunity(b) Reference
Cy
ste
ine
Pro
tea
ses
CA C1
Pa
pa
in-l
ike
pro
tea
ses
AtCathB At Positive regulator of basal resistance against
virulent Ps
McLellan et al., 2009
AtCEP1 At Positive regulator of defence response to Ec Höwing et al., 2014
C14 Nb Positive regulator in defence response to Pi Kaschani et al., 2010,
Bozkurt et al., 2011
CYP St Induced expression upon Pi infection which
correlates with resistance
Avrova et al., 1999
Mir1 Zm Positive regulator of resistance to Sf Pechan et al., 2000, Pechan
et al., 2002
NbCathB Nb Positive regulator of disease resistance induced by
Ea and Ps
Gilroy et al., 2007
NbCYP1
and
NbCYP2
Nb Positive regulators in host defence responses to Cd Hao et al., 2006
Pip1 Le Induced extracellular accumulation during infection
by Pi
Tian et al., 2007
RCR3 Le Positive regulator of resistance to Cf Krüger et al., 2002
RD21 At Positive regulator of defence response to Bc Shindo et al., 2012
StCath St Induced expression during HR response to Pi
infection
Avrova et al., 2004
CD
C14
Me
taca
spa
ses
AtMC1
and
AtMC2
At Positive and negative regulator of the HR response
to Ps, respectively
Coll et al., 2010
AtMC2-6 At Negative regulators of cell death in response to Bc,
Bt and Be
VAN Baarlen et al., 2007
AtMC4 At Negative regulator of cell death induction by Ps and
mycotoxin fumonisin B1
Watanabe and Lam, 2011
AtMC7
and
AtMYB8
At Positive regulators of cell death in response to Bc,
Bt and Be
VAN Baarlen et al., 2007
CaMC9 Ca Positive regulator of PCD and defence in response
to Xcv
Kim et al., 2013
LeMCA1 Le Induced expression during Bc infection Hoeberichts et al., 2003
NbMCA1 Nb Positive regulator of basal defence in response to
Cd
Hao et al., 2007
OsMC1-8 Os Induced or repressed expression upon Mo and Xoo
infection
Huang et al., 2015
TaMCA4 Ta Positive regulator of PCD and defence response to
Pt
Wang et al., 2012
C13
VP
Es
VPE1 At Positive regulator of defence response to Bc and Bt VAN Baarlen et al., 2007
VPE2 At Negative regulator of defence response to Bc VAN Baarlen et al., 2007
VPE3 At Negative regulator of defence response to Ha Misas-Villamil et al., 2013
VPE3 At Positive regulator of resistance and plant basal
defence to Ps, Bc and TMV
Rojo et al., 2004
VPE1a
and VPE1b
Nb Positive regulators of the HR during TMV infection Hatsugai et al., 2004
VPEs Nu Positive regulators of the cell death induced by the
fungal AAL-toxin from Aa
Mase et al., 2012
VPEs Md Induced expression during the HR-response to Ea Iakimova et al., 2013
aAa, A. alternata f.sp. lycopersici; As, Avena sativa; At, Arabidopsis; Ca, pepper; Gm, Glycin max; Le, Lycopersicon esculentum; Md,
M. domestica; Me, Manihot esculenta; Nb, N. benthamiana; Nt, tobacco; Nu, N. umbratica; Os, rice; Sl, tomato; St, Solanum
tuberosum; Ta, Wheat; Vs, Vitis species; Zm, Zea mays. bBc, B. cinerea; Bt, B. tulipae; Be, B.elliptica; Cd, C. destructivum; CEV, Citrus Exocortis Viroid; Cf, C. fulvum; Ea, E. amylovora; Ec, E.
cruciferarum; Fs, F. solani; Ha, H. arabidopsidis; Mo, M. oryzae; Pi, P. infestans; Ps, P. syringae; Pt, P. striiformis f. sp. tritici; Sf, S.
responsive factors (ERF) and related to ABI3/VPI (RAV). The ERF subfamily of proteins is
unique to plants with members that participate in the regulation of genes responsive to biotic
stress upon infection, in particular related to the JA and ET signalling pathways (Yang et al.,
2015). Several Arabidopsis ERF genes respond to pathogen infection with different but
overlapping kinetics, likely helping orchestrate an adequate defence response (Oñate-
Sánchez and Singh, 2002). The ERF subfamily includes Pto-interacting4 (PTI4) that interacts
with and is phospholylated by the product of the tomato R gene Pseudomonas Tomato
Resistance (PTO). Phosphorylation of PTI4 by PTO increases the DNA-binding of the TF,
resulting in a relatively simple signal transduction pathway that leads to resistance (Gu et al.,
2000).
43
2.2. bHLH TFs
The basic-Helix-Loop-Helix (bHLH) family was estimated to comprise more than 160
members in Arabidopsis and rice (Carretero-Paulet et al., 2010). Myelocytomatosis-related
(MYC) proteins belong to a subfamily of eukaryotic bHLH TFs that have been involved in the
establishment of defence responses. MYC TFs are key transcriptional regulators of the
expression of JA-responsive genes, positively regulating wound resistance genes and acting
as negative regulators during the expression of pathogen defence genes. For example,
AtMYC2/JAI1/JIN1, along with its closely related proteins AtMYC3 and AtMYC4 are key
master regulators coordinating JA-dependent defence responses and mediating crosstalk
with other phytohormones such as SA, ABA, GA, and auxin (Kazan and Manners, 2013). For
more details on the regulation of MYC proteins see the review article at the end of this
section (Buscaill and Rivas, 2014).
2.3. bZIP TFs
The Arabidopsis genome encodes 75 distinct members of the basic domain leucine zipper
(bZIP) family. In plants, bZIP TFs are central players of the regulation of plant immunity
especially within the SA-signalling pathway conferring resistance toward biotrophic
pathogens (Gatz, 2013). Among these proteins, AtTGA2, 5 and 6 play critical roles in
establishing SAR and are also essential activators of certain ET-induced defence responses
(Zander et al., 2014).
2.4. BBX TFs
The B-box (BBX) proteins are a class of zinc-finger TFs that sometimes also feature a
CONSTANS, CO-like, and a TOC1 (CCT) domains. BBX proteins are key factors in
regulatory networks controlling growth and developmental processes as well as responses to
biotic and abiotic stresses (Gangappa and Botto, 2014). BBX proteins also participate in
wounding and defence responses (Taki et al., 2005). For example, a study showed that
BBX32 expression is increased after a short treatment with chitin, suggesting involvement of
this TF in plant defence pathways (Libault et al., 2007).
44
2.5. NAC TFs
With 135 members in rice and 117 in Arabidopsis, no apical meristem (NAM), Arabidopsis
thaliana transcription activation factor (ATAF) and cup-shaped cotyledon (CUC2) (NAC)
proteins belong to a large TF family (Nuruzzaman et al., 2013). NAC proteins, which belong
to the largest family of plant-specific TF, have been reported to be involved in plant
development and biotic and abiotic stress regulation (Puranik et al., 2012). A significant
number of reports highlight the role of NAC TFs as central regulators of the plant innate
immune system, basal defence and SAR responses (Collinge and Boller, 2001, Jensen et
al., 2007, Jensen et al., 2008, Bu et al., 2008, Nuruzzaman et al., 2013, Delessert et al.,
2005, Seo et al., 2010a). For example, the Arabidopsis NAC protein NTL6 has been shown
to positively regulate pathogen resistance against P. syringae (Seo et al., 2010a).
2.6. Whirly TFs
Members of the Whirly family of proteins are found throughout the plant kingdom and are
predicted to share the ability to bind ssDNA (single-stranded DNA) (Desveaux et al., 2005).
This TFs family has been involved in the regulation of defence gene expression. For
example, the Arabidopsis Whirly protein AtWhy1 has been shown to be required for both
basal resistance, ETI and SAR (Desveaux et al., 2005).
2.7. WRKY TFs
WRKY proteins are a plant-specific family of TFs (Rushton et al., 2010). WRKY TFs belong
to one of the largest families of transcriptional regulators in plants with 72 representatives in
Arabidopsis, and more than 100 members in rice, soybean or poplar (Bakshi and Oelmüller,
2014). Extensive research has firmly established a major role of WRKY family members in
host immunity in Arabidopsis, barley or rice (Pandey and Somssich, 2009). Specific WRKY
family members show enhanced expression and/or DNA-binding activity following induction
by a range of pathogens, defence signals and wounding (Eulgem et al., 2000). WRKY
proteins bind to the W box, which is found in the promoters of many plant defence-related
genes (Bakshi and Oelmüller, 2014). Interestingly, expression profiling revealed that
45
expression of 70% of the Arabidopsis WRKY genes is differentially regulated in response to
SA treatment or infection by various pathogens (Dong et al., 2003, Eulgem and Somssich,
2007, Ulker and Somssich, 2004). This confirms that WRKY TFs are able to regulate
defence mechanisms to different pathogens and this activity is exerted by their action as
positive (Knoth et al., 2007, Liu et al., 2006) or negative (Journot-Catalino et al., 2006, Xu et
al., 2006) regulators. Finally, it was also shown that the WRKY TFs may act on hormonal
pathways by influencing their interconnections thus enabling the activation of various
defence pathways (Chen et al., 2013). For additional details on this particular TF family and
its role on plant defence regulation, see the review article at the end of this section (Buscaill
and Rivas, 2014).
2.8. MYB TFs
The Myeloblastom (Myb) gene was first identified as the v-Myb oncogene of an avian
myeloblastosis virus (Klempnauer et al., 1982). Subsequently, members of the Myb gene
family were identified in diverse plants and animals (Lipsick, 1996). The first plant MYB gene,
C1, was isolated from Zea mays and encodes a c-MYB-like protein with structural homology
to the vertebrate cellular proto-oncogene c-MYB that is involved in anthocyanin biosynthesis
(Paz-Ares et al., 1987). Since 1987, the size of catalogue of MYB-related TFs has increased
considerably due to the big number of MYB genes identified in higher plants. Analysis of the
Arabidopsis genome identified 198 genes in the MYB superfamily (Dubos et al., 2010).
MYB superfamily members present a modular structure characterized by the presence of a
highly conserved DBD – the MYB domain – located in the N-terminal part of the protein,
which generally comprises up to four imperfect repeats called R or MYB repeats. Each
repeat consists of approximately 50–53 amino acid residues that form a Helix-Turn-Helix
(HTH) which may or may not function synergistically in their ability to bind to DNA. The
second and third helices of each repeat build a HTH structure with three regularly spaced
tryptophan (or hydrophobic) residues, forming a hydrophobic core in the 3D HTH structure
46
(Ogata et al., 1996). The third helix of each repeat is the ‘‘recognition helix’’ that is
responsible for direct contact with DNA (Jia et al., 2004).
In contrast to the MYB domain, the C-terminal region of MYB proteins, the transcriptional
activation domain (TAD) is characteristically highly variable from one MYB protein to another.
In addition, the TAD may function as an activation or a repression domain (Dubos et al.,
2010), giving rise to the wide structural and functional variability of the MYB family.
2.8.1. DNA MYB Binding Sites (MBSs)
Despite the prominent roles played by MYB TFs in the regulation of plant gene expression,
little is known about how these proteins interact with their DNA targets (Prouse and
Campbell, 2012). Six DNA sequences have been well-characterized as DNA-binding sites for
87 proteins of the MYB superfamily: CNGTT(A/G), ACC(A/T)A(A/C), TTAGGG,
AAAATATCT, GATA and TATCCA. R2R3–MYB DNA-binding data mainly result from in vitro
assays. However, in vivo assays have also been used to determine R2R3–MYB DNA-
binding specificities. R2R3–MYB family members from different species have been
previously classified into different phylogenetic clades (groups A, B, and C) based on
sequence similarities (Romero et al., 1998). These groups were then analysed for DNA-
binding specificities. It was shown that members of group A bind the so-called MBS (MYB
Binding Site) type I sequence (C(A/C/G/T)GTT(A/G)), members of group B bind equally to
MBS type I and type II (G(G/T)T(A/T)GTT(A/G)), and most members of group C bind MBS
type IIG ((C/T)ACC(A/T)A(A/C)C) (Romero et al., 1998). However, other examples show that
MYB proteins, although similar in structure and function, are able to bind to different DNA
target sites. Overall, several studies highlight the importance of conducting DNA-binding site
experiments for individual MYB proteins because it is extremely difficult to predict MBSs on
the sole basis of sequence information (Prouse and Campbell, 2012).
Figure 16. Plant MYB transcription factor classes (Adapted from Dubos et al., 2010). Plant MYB proteins are classified depending on the number of adjacent MYB repeats (R). The
primary and secondary structures of a typical R2R3-MYB are indicated. H, helix; T, turn; W,
tryptophan; X, any amino-acid residue.
R1/2 R3
R3 R2
R3 R2
R2
R1
R1/2
1R-MYB
2R-MYB
3R-MYB
4R-MYB R2 R1
R3 R2
-W-(X19)-W- …. -F/I-(X18)-W- Primary structure
Secondary structure H H H H H H T T
Figure 17. Schematic illustration of different MYB protein classes and their
functions (From Ambawat et al., 2013).
Figure 18. Schematic representation of the relationships between the different
Arabidopsis R2R3-MYB subgroups (From Dubos et al., 2010). The tree was inferred using the neighbour-joining method and 1000 bootstraps with putative
amino acid full length of 126 Arabidopsis R2R3-MYB sequences with the Clustal X2 software.
Based on the conservation of the DNA-binding domain and of amino acid motifs in the C terminal
domains, R2R3-MYB proteins have been divided into 25 subgroups. AtMYB30 is boxed in red.
47
2.8.2. Classification of MYB TFs
The highly conserved DBD in MYB proteins suggests a common mechanism for the
regulation of DNA binding, whereas the more variable TAD domain may modulate TF
activation and DBD accessibility and thereby confer specificity of DNA binding to the TF.
Animal MYB TFs present three MYB repeats (Lipsick, 1996), while in plants the number of
repeats varies from one to four allowing classification of these proteins into four classes
(Figure 16).
· 1R-MYB
This heterogeneous class designated 1R-MYB (also called ‘‘MYB-related’’) comprises TFs
that usually contain a single MYB repeat (R3-MYB) or a partial MYB repeat (R1/2-MYB)
(Rosinski and Atchley, 1998) (Figure 16). A recent report identified 68 MYB-related genes in
Arabidopsis (Du et al., 2013). 1R-MYBs have been involved in organ morphogenesis
(Stracke et al., 2001, Simon et al., 2007, Pesch and Hülskamp, 2009) or in regulation of
secondary metabolism (Dubos et al., 2010, Matsui et al., 2008). Some of these TFs have
also been described as transcriptional activators associated with the regulation of the
circadian cycle (Schaffer et al., 2001), phosphate starvation and chloroplast development
(Ambawat et al., 2013). Others are capable of controlling gene expression indirectly through
modification of histones or chromatin remodelling (Boyer et al., 2002, Clapier and Cairns,
2009, Marian and Bass, 2005) (Figure 17).
· 2R-MYB (or R2R3-MYB)
In contrast to animals, plants contain a R2R3-MYB class which is characterised by the
presence of two MYB repeats (Wilkins et al., 2009, Jiang et al., 2004). R2R3-MYB proteins
are thought to have evolved from an R1R2R3-MYB gene ancestor, by the loss of the
sequences encoding the R1 repeat and subsequent expansion of the gene family (Rosinski
and Atchley, 1998, Du et al., 2013, Stracke et al., 2001). These proteins represent the largest
MYB class present exclusively in plants with 126 members in Arabidopsis (Dubos et al.,
2010) (Figure 18). Based on the conservation of the DBD and amino acid units located in the
48
conserved C-terminal domain of the protein, MYB R2R3 TFs were classified into 25
subgroups (Dubos et al., 2010) (Figure 18). Comparative phylogenetic studies enabled the
identification of new R2R3-MYB protein subgroups in other plant species (for example, in
Poplar and Vitis) that do not have orthologs in Arabidopsis. This suggests that these proteins
may have specific roles in these species (Wilkins et al., 2009, Matus et al., 2008). R2R3-
MYBs have been involved in primary metabolism, cell fate and identity, developmental
processes as well as responses to biotic and abiotic stresses (Ambawat et al., 2013) (Figure
17).
· 3R-MYB (or R1R2R3-MYB)
3R-MYB proteins are characterized by the presence of three MYB repeats called R1, R2 and
R3 (Figure 16). Each repeat motif of 3R-MYB proteins identified in tobacco and Arabidopsis
is more closely related to the vertebrate MYB repeats than to the repeats from plant R2R3-
MYB proteins. Thus, MYB proteins with three repeats from plants and animals represent an
evolutionarily conserved group in the MYB superfamily and are collectively called three-
repeat MYB (3R MYB) proteins (Ito, 2005). 3R-MYB proteins are encoded by five genes in
Arabidopsis and are found in most eukaryotic organisms, suggesting that they represent a
class of conserved genes which derived from the R2R3-MYB (Stracke et al., 2001, Ambawat
et al., 2013). These proteins are associated with the transcriptional control of cyclins and
thus involved in the regulation of the cell cycle (Ambawat et al., 2013, Haga et al., 2007)
(Figure 17).
· 4R-MYB
4R-MYB proteins are the smallest class of MYB proteins whose members contain four
R1/R2-like repeats (Figure 16). A single 4R-MYB protein is encoded in several plant
genomes and its role remains unknown to date (Ambawat et al., 2013) (Figure 17).
49
2.8.3. Functions of MYB TFs
While vertebrates present only three MYB proteins (c-Myb, A-Myb and B-Myb) (Lipsick et al.,
2001), members of the MYB-type family of TFs in plants are over-represented. In
vertebrates, MYB-related proto-oncogenes form a small family with a central role in
controlling cellular proliferation and development. In plants; the expansion of R2R3-MYB
proteins may have occurred in response to their adaptation to a sessile lifestyle. MYB TFs
play a wide variety of physiological functions in higher plants (Dubos et al., 2010) (Figure 17),
including regulation of primary and secondary metabolism (Lepiniec et al., 2006, Gigolashvili
et al., 2007, Zhou et al., 2009), control of cell development (Kang et al., 2009) and cell cycle
(Haga et al., 2007), participation in defence and response to various abiotic stresses (Seo et
al., 2009), hormone synthesis (Seo and Park, 2010) and signal transduction (Shin et al.,
2007).
In particular, MYB TFs play important roles as regulators of defence responses against
pathogen attack in various plant species. For example, in Nicotiana tabacum, the expression
of several MYB R2R3 genes is induced in response to elicitors (Sugimoto et al., 2000). In
barley (Hordeum vulgare), HvMYB6 functions as a positive regulator of immunity responses
to B. graminis (Chang et al., 2013). In Oryza sativa, an AtMYB78-related MYB gene has
been shown to be expressed in response to fungal attack (Lee et al., 2001). In Arabidopsis,
the R2R3-MYB TF AtMYB108/BOSI1 is a positive regulator of defence, as the Arabidopsis
mutant bos1 presents increased symptoms after infection by various necrotroph or biotroph
pathogens (Mengiste et al., 2003). Moreover, the R2R3-type MYB TF gene AtMYB72 was
identified as one of the significantly induced genes in Arabidopsis roots in response to P.
fluorescens WCS417r (Verhagen et al., 2004). This root-specific TF is an early signalling
factor that functions as a node of convergence in ISR elicited by diverse beneficial microbes
(Van der Ent et al., 2008). AtMYB44 acts as an integrator of the cross-talk between SA and
JA signalling during plant defence responses (Shim and Choi, 2013). Finally, R2R3-MYB
proteins of the subgroup 1, AtMYB30 and AtMYB96, are involved in immune responses.
50
Indeed, some studies indicate that AtMYB96 acts through the ABA signalling cascade to
regulate drought stress, freezing tolerance and disease resistance (Lee et al., 2015, Seo et
al., 2009, Seo and Park, 2010). AtMYB30 is probably the Arabidopsis MYB TF that has been
the best characterized for its positive regulatory function of the establishment of the HR,
acting through the activation of very long chain fatty acid (VLCFA) synthesis, associated with
resistance to various pathogens (Lacomme and Roby, 1999, Daniel et al., 1999, Vailleau et
al., 2002). An overview of our current knowledge about AtMYB30-mediated regulation of
defence responses is presented in section 3.
51
2.9. Transcriptional control in plant defence (Review article)
During my PhD, I had the opportunity to participate in writing a review article focused on the
transcriptional control in plant immunity. In this review, the importance of (i) defence-related
hormone signalling, (ii) the role of WRKY transcription factors during the regulation of plant
responses to pathogens, (iii) nuclear functions of plant immune receptor proteins, as well as
(iv) the varied ways by which microbial effectors subvert plant transcriptional reprogramming
to promote disease are discussed in more detail.
Transcriptional control of plant defence responsesPierre Buscaill1 and Susana Rivas2
Mounting of efficient plant defence responses depends on the
ability to trigger a rapid defence reaction after recognition of the
invading microbe. Activation of plant resistance is achieved by
modulation of the activity of multiple transcriptional regulators,
both DNA-binding transcription factors and their regulatory
proteins, that are able to reprogram transcription in the plant cell
towards the activation of defence signalling. Here we provide an
overview of recent developments on the transcriptional control of
plant defence responses and discuss defence-related hormone
signalling, the role of WRKY transcription factors during the
regulation of plant responses to pathogens, nuclear functions of
plant immune receptor proteins, as well as varied ways by which
promoter, suggesting a potential positive feedback regu-
latory loop and activation of WRKY33 transcriptionally
and post-translationally [27�]. In addition, SIGMA FAC-
TOR BINDING PROTEIN1 (SIB1) and SIB2 interact
with WRKY33 via their VQ motif that is also required to
stimulate WRKY33 DNA-binding (but not trans-
activation) activity [28�]. Similar to WRKY33, expression
of both SIB1 and SIB2 is induced by infection with B.
cinerea and SIB1 and SIB2 act as positive regulators of
WRKY33-mediated resistance to necrotrophic fungi
[28�]. In another study, WRKY33, and the closely related
WRKY25, were shown to interact with MAP KINASE
SUBSTRATE1 (MKS1), an additional VQ motif-contain-
ing protein [29]. In resting cells, MPK4 exists in nuclear
36 Biotic interactions
Current Opinion in Plant Biology 2014, 20:35–46 www.sciencedirect.com
complexes with WRKY33 and MKS1 although no direct
interaction between MPK4 and WRKY33 has been
demonstrated [30]. Upon bacterial infection, activated
MPK4 phosphorylates MKS1, which releases MKS1-
associated WRKY33 that then targets the expression of
camalexin biosynthesis genes [30]. In summary, different
VQ motif-containing proteins appear to be able to interact
with and activate multiple WRKY proteins and, in the
case of WRKY33, the dynamic nature of these molecular
interactions suggests distinct roles and regulations during
the plant response to either bacterial or fungal pathogens
(Fig. 2b).
Transcriptional control of plant immunity Buscaill and Rivas 37
Figure 1
Nucleus
(a) (c)
(b)
Cytoplasm
EIN3
ET
EIN3
EIN3
COI1
JAZ
JA
TRX
JAZ
JA
P
ET
JA
PR1/WRKY
TGA
MYC2/3/4
MYC2/3/4
PR1/WRKY
Redox
change
(rele
ased
)
(dephosphorylation)
SA
TGA
NPR3/4
-SA +SA
ET
-ET
+ET
-JA +JA
UbbUbb
UbbbUb
NPR1NPR1
NPR1NPR1
NPR1
NPR1NPR1
NPR1NPR1
NPR1
NPR1
NPR1
ETR1
ETR1
EIN2
EIN2
NPR1
NPR3/4NPR1
TA
EIN33333
(dephosphorylation)
EIN2
PRRRR111Ubb
UbbUbbb
Ub PRR11Ubb
UbbUbbb
Ub
SA
NPR1
N33
NPR
1
TPLTPL
NIN
JA
NIN
JA
CTR
1
CTR
1
EIN2
UbUb
UbUb
UbUb
UbUb
Current Opinion in Plant Biology
Simplified view of the transcriptional regulation of some defence related hormone pathways. (a) SA signalling depends on the key transcriptional
regulator NPR1 that in resting cells is sequestered in the cytoplasm as an oligomer. In these conditions, a small amount of NPR1 monomers is
translocated to the nucleus where the protein is ubiquitinated and degraded by the proteasome via the NPR1 paralogues NPR3 and NPR4 that act as
adaptors of the Cullin 3 ubiquitin E3 ligase [13��]. Increased SA levels induce changes in the cellular redox balance releasing monomeric NPR1 through
thioredoxin-mediated reduction of disulfide bonds among NPR1 molecules. Large amounts of momomeric NPR1 are then translocated to the nucleus
where NPR1 directly binds SA, which induces a conformational change that releases NPR1 C-terminal transactivation (TA) domain [12��]. Moreover,
NPR1 interacts with members of the TGA transcription factor family and promotes the transcriptional activation of defence-related genes, including
PR1 and WRKY genes [14]. (b) In non-induced cells, JAZ proteins act as transcriptional repressors through their interaction with the transcriptional
activators MYC2/3/4 [18]. The NINJA adaptor protein acts as a scaffold and mediates the interaction of JAZ proteins with the co-repressor TPL,
preventing untimely activation of JA-related gene expression [17�]. In challenged cells, JA is perceived by a COI1-JAZ receptor complex [16��].
Subsequent ubiquitination and proteasomal degradation of the JAZ transcriptional repressors releases MYC TFs and results in transcriptional
activation of JA-responsive genes [16��]. (c) In the absence of ET, the Raf-like kinase CTR1, that is able to interact with the ET receptor ETR1 in ER
membranes, phosphorylates the C-terminal domain of the key regulator EIN2, preventing its proteolytic cleavage and nuclear translocation
[20,21��,22��]. In this context, the transcriptional activator EIN3 is degraded by the proteasome preventing activation of ET signalling [23]. In the
presence of ET, the hormone binds to the ETR1 receptor, resulting in realease and deactivation of the Raf-like kinase CTR1, that is no longer able to
phosphorylate the EIN2 C-terminal domain [20,21��,22��]. Unphosphorylated EIN2 undergoes proteolytic cleavage and its C-terminal fragment is
translocated to the nucleus where it participates to inhibition of the proteasomal degradation of the EIN3, thereby triggering ET-dependent signalling
(Fig. 1C) [20,21��,22��,23].
www.sciencedirect.com Current Opinion in Plant Biology 2014, 20:35–46
A direct interaction between MAPK and WRKY proteins
has also been reported in Nicotiana benthamiana.
NbWRKY8 (closest homolog of Arabidopsis WRKY33)
is a substrate of three pathogen-responsive MAPKs,
SIPK, WIPK, and NTF4 [31]. Phosphorylation of
NbWRKY8 enhances its DNA-binding and trans-
activation activities, increasing expression of downstream
defence-related genes. Silencing of NbWRKY8 increased
plant disease susceptibility to Phytophthora infestans and
Colletotrichum orbiculare, indicating that NbWRKY8
regulates broad-spectrum disease resistance through acti-
vation of defence gene expression [31�].
A recent report showed that WRKY TFs are additionally
able to act synergistically with CPK proteins during ETI
signalling in Arabidopsis [32��]. WRKY46 was identified as
38 Biotic interactions
Figure 2
(a)
defence
defence
resistance
MIEL1
(relocalized)
coor
dina
tion
Pathogen
perception
Pathogen
perception
Pathogen
perception
Defence gene Defence gene
Defence gene
SA
Defence gene
Pathogen perception
MYB30 MYB30
MAPK4
MAPK4
MAPK3/6
VQ
VQ
VQ
SIB1/2
SIB1/2
MKS1MKS1
P
P
P
P
WRKY33
WRKY33
WRKY33
WRKY33
WRKY33
WRKY1/2
WRKY1/2
WRKY45
WRKY45
Pb1
WRKY1
MYB6
MYB6 MYB6
cell
death
fungal
growth
MLA10
MLA10
MLA10
UbUb
UbUb
VLCFA
Cytoplasm
Nucleus
camalexin
camalexin
WRKY33
AtsPLA2α
(b)
(c)
(d)
Current Opinion in Plant Biology
Simplified models for the action of selected nuclear TFs during the regulation of plant immune responses. (a) MYB30 positively regulates Arabidopsis
defence responses to bacteria [63,64]. Interaction with AtsPLA2-a, which relocalizes to the nucleus from Golgi vesicles, and the RING-type E3 ligase
MIEL1, which leads to MYB30 ubiquitination and proteasomal degradation, both result in reduced MYB30-mediated transcriptional activation of
VLCFA-related genes and suppressed defence [66�,67]. (b) In resting Arabidopsis cells, WRKY33 is inactive in a complex with the VQ-containing motif
protein MKS1 and MPK4 [30]. Following pathogen perception, MAPK4 phosphorylates MKS1, releasing MKS1-associated WRKY33 that is then able to
activate transcription of camalexin biosynthetic genes [30]. WRKY33 phosphorylation by MPK3/MPK6 is required for the transcriptional activation of
camalexin biosynthetic genes and WRKY33 itself, which results in a positive feedback regulatory loop [27�]. WRKY33 interaction with VQ-containing
motif proteins SIB1/2 stimulates its DNA-binding activity and thus promotes defence [28�]. (c) In resting barley cells (or during a compatible
interaction), WRKY1/2 repressors suppress defence gene expression [40��] and sequester HvMYB6 activator from activating defence [41�]. Following
recognition of the AVR10 effector, the R protein MLA10 is activated and interacts with WRKY1/2, which releases HvMYB6 from suppression byWRKY1
[40��,41�]. Released HvMYB6 may then activate defence gene expression both directly and through interaction with MLA6 [41�]. Coordination of MLA
molecular activities in the cytoplasm (for cell death activation) and in the nucleus (for restriction of fungal growth) is required for efficient activation of
defence signalling [42]. (d) In resting rice cells, WRKY45 accumulation is downregulated through proteasomal degradation [37]. Following pathogen
perception, interaction with the R protein Pb1 protects WRKY45 from proteasomal degradation, resulting in transcriptional activation of SA-mediated
signalling and resistance [36�].
Current Opinion in Plant Biology 2014, 20:35–46 www.sciencedirect.com
an ETI marker, its expression being strongly induced by
activation of the NLR immune receptors RPS2 and
RPM1. Activation of closely related CPK4,5,6 and 11
results in specific phosphorylation of a subgroup of
TFs, WRKY8, 28 and 48, and activation of WRKY46
expression, and these effects are dependent on
CPK4,5,6 and 11 kinase activity [32��]. Importantly,
phosphorylation of WRKY proteins by CPKs promotes
TF binding to target promoters, which suggests syner-
gistic roles of specific CPK and WRKY proteins to activate
WRKY46 during ETI signalling. In agreement with these
findings, cpk5,6, wrky8 and wrky48 were compromised in
defence gene activation and ETI-mediated disease resist-
ance [32��], although WRKY8 and 48 had been previously
described as negative regulators of basal resistance
[33,34].
Arabidopsis WRKY8 has also been shown to function in
the long-distance movement of crucifer-infecting Tobacco
Mosaic Virus (TMVcg) by modulating both ABA and ET
signalling [35]. Following TMVcg infection, WRKY8
respectively induces and represses the expression of
genes mediating ABA and ET signalling by directly
binding to their respective promoters. Since ABA and
ET respectively hamper and induce accumulation of
TMVcg, WRKY8 has been proposed to promote plant
resistance by mediating the crosstalk between these
signalling pathways [35].
Nuclear functions of plant immune receptorsin interaction with TFsIncreasing evidence points to the crucial role of nuclear
functions of plant immune receptor proteins that display
nucleocytoplasmic partitioning, which is essential for
proper initiation of host defences. In this section we
discuss recent reports highlighting the importance of
the interaction between immune sensors and TFs during
the regulation of defence signalling in different plant
species. These findings provide a direct connection be-
tween pathogen perception and defence-related tran-
scriptional reprogramming although the details of this
molecular process are not yet fully understood.
In rice (Oryza sativa), the CNL Panicle blast1 (Pb1)
confers durable broad-spectrum resistance to Magnaporthe
oryzae. A recent report showed that the nuclear interaction
between Pb1 and OsWRKY45 is essential for blast resist-
ance [36�]. OsWRKY45, whose transcriptional activity is
regulated by the 26S proteasome, was previously
described as being required for SA-mediated rice resist-
ance to Magnaporthe [37]. Interaction with Pb1 protects
OsWRKY45 from proteasomal degradation thus resulting
in plant resistance [36�] (Fig. 2d).
In N. benthamiana, the immune receptor N resides in the
cytoplasm and the nucleus of non-infected cells. After
TMV inoculation, and in the presence of the viral helicase
p50-U1, cytoplasmic N either enters the nucleus or sends
a signal that activates the N nuclear pool, resulting in the
activation of a successful defence response [38��]. A
recent report showed that, nuclear N interacts with the
SPL6 TF to promote defence gene activation and resist-
ance to TMV in a p50-U1-dependent manner [39�].
Interestingly, the SPL6 Arabidopsis ortholog is also
required for RPS4-mediated resistance to Pseudomonas
syringae pv. tomato expressing the effector AvrRps4 (Pst-
avrRps4), suggesting a novel and conserved function for
SPL6 TFs in activation of defence-related gene expres-
sion across several plant species.
In barley (Hordeum vulgare), the CLR immune receptor
MLA10 interacts with the transcriptional repressors
HvWRKY1 and HvWRKY2 in the nucleus to induce
resistance against the powdery mildew fungus Blumeria
graminis expressing AVR10 [40��]. Since this protein
interaction depends on recognition of AVR10 by
MLA10, HvWRKY1 and HvWRKY2 likely suppress
defence activation in the absence of the pathogen and,
upon infection, binding of MLA10 de-represses transcrip-
tion and triggers defence. A recent report identified the
MYB TF HvMYB6 as an additional MLA10-interacting
TF that positively regulates resistance to B. graminis
[41�]. Notably, both MLA10-HvMYB6 and N-SPL6 mol-
ecular interactions are only detected after activation,
suggesting that elicitor-triggered conformational changes,
oligomerization or subcellular relocalization of the R
proteins are likely required for R protein-TF interactions
[41�]. HvMYB6 DNA-binding is antagonized by its direct
association with the HvWRKY1 repressor. Activated
MLA10 releases the HvMYB6 activator from HvWRKY1
repression, thereby stimulating HvMYB6-dependent
gene expression and plant resistance [41�]. A structure-
function analysis of MLA10 has shown that cell death and
disease resistance signalling triggered by MLA10 depend
on its balanced nucleocytoplasmic activities [42]. Indeed,
MLA10 activity in cell death signalling appears to be
suppressed in the nucleus but enhanced in the cytoplasm
whereas nuclear localized MLA10 is essential and suffi-
cient to mediate disease resistance against B. graminis [42]
(Fig. 2c). In Arabidopsis, mutation of WRKY18 and
WRKY40 (homologs of barley HvWRKY1 and HvWRKY2)
results in massive defence-related transcriptional repro-
Moreover, the modular effector XopD from the strain
B100 of Xanthomonas campestris pv. campestris was shown
to target Arabidopsis MYB30 in the nucleus resulting in
suppression of plant resistance and defence-associated
cell death responses through inhibition of the transcrip-
tional activation of MYB30 VLCFA-related target genes
[68�] (Fig. 3b). In tomato, XopD from X. euvesicatoria
(Xcv) is able to target, deSUMOylate and destabilize the
ET-responsive TF SlERF4, leading to repressed SlERF4
transcription and thus reduced SlERF4-mediated ET
production, which is required for anti-Xcv defence and
symptom development [69�] (Fig. 3c). Another effector
able to target a host TF is HopD1 from Pseudomonas
syringae, which acts as a virulence factor in Arabidopsis.
HopD1 interacts with the TF NTL9, a positive regulator
of plant defence, in the ER resulting in the suppression of
ETI but not PTI responses [70].
Remarkably, some Pseudomonas strains have evolved the
ability to disrupt plant hormone homeostasis by produ-
cing the toxin coronatine (COR), a mimic of bioactive JA-
Ile, that contributes to disease by promoting opening of
stomata, and thus bacterial entry, as well as bacterial
growth through repression of SA signalling, and thus
activation of the antagonistic JA pathway [6]. A recent
report has identified the effector HopX1 from a Pseudo-
monas strain unable to produce COR that interacts with
and promotes the degradation of JAZ proteins through its
cysteine protease activity and independently of COI1
[71��]. Ectopic expression of HopX1 in Arabidopsis acti-
vates and represses JA- and SA-dependent gene expres-
sion, respectively [71��]. Moreover, HopX1 contributes to
bacterial virulence by mimicking COR-induced suscepti-
bility and this is dependent on the catalytic activity of the
effector [71��]. In a similar vein, the Pseudomonas effector
HopZ1a interacts with and acetylates JAZ transcriptional
40 Biotic interactions
Current Opinion in Plant Biology 2014, 20:35–46 www.sciencedirect.com
repressors, leading to their degradation through an
unknown COI1-dependent mechanism [72��]. Similar
to HopX1, HopZ1a is able to partially rescue the viru-
lence defect of Pseudomonas strains unable to produce
COR [72��].
Additional illustration of the varied strategies displayed
by nuclear effectors to block defence is provided
by HopU1, a mono-ADP-ribosyltransferase from
Pseudomonas that targets several RNA-binding proteins
including GRP7 [73�,74]. GRP7 is able to bind transcripts
of the PRRs FLS2 and EFR and HopU1 hampers this
interaction, resulting in reduced FLS2 protein accumu-
lation and suppression of PTI signalling [75�] (Fig. 3d).
The broadly conserved Mediator complex (>25 proteins)
is an essential transcriptional regulator that mediates the
interaction between TFs and RNA polymerase II [76].
Transcriptional control of plant immunity Buscaill and Rivas 41
Figure 3
RPS6
SNC1
Med19
HaRxL44
(Hpa )
Nucleus
SlERF4
immunityET
4 -SUMO
SA JA/ETdefence to
biotrophs
GRP7
HopU1
(Pst )
FLS2 mRNA
FLS2
SlERF4RPS4
cell death
RPS4
bacterial
growth
Defence gene
SlERF4
EDS1EDS1
EDS1
SRFR1
RPS6
HopA1
(Pst)
RPS4EDS1
SRFR1
AvrRps4
(Pst)
(a)
Cytoplasm
MYB30
VLCFA defence
XopD
(Xcc )
XopD
(Xcv )
FL
PTI
AvrRps4
(Pst)
AvrRps4
(Pst)
(b)
(e)
(d)
(c)
Current Opinion in Plant Biology
Schematic representation of the mode of action of certain microbial effector proteins inside the plant cell nucleus. (a) In resting cells, the repressor SRFR1
interacts at endomembranes with EDS1 and inactive RPS4 and RPS6 R proteins [51��,84]. The interaction of effectors AvrRps4 and HopA1 with EDS1
results in perturbation of receptor complexes residing at endomembranes [51��]. Nucleocytoplasmic coordination of molecular activities of a released
RPS4-EDS1-AvrRPS4 signalling complex is required for the activation of cytoplasmic cell death and transcriptional activation of defence genes, whereas a
nuclear RPS4-EDS1-AvrRPS4 complex restricts bacterial growth [50��]. The R protein SNC1 contributes to RPS4 defence responses through its
interaction with transcriptional co-repressor proteins [48]. Pst: Pseudomonas syringae pv. tomato. (b) XopD from Xcc targets the Arabidopsis MYB TF
MYB30 and suppresses MYB30-mediated transcriptional activation of VLCFA-related genes thereby blocking defence responses [68�]. Xcc:
Xanthomonas campestris pv. campestris. (c) XopD from Xcv targets and deSUMOylates the tomato TF SlERF4, resulting in reduced transcriptional
activation of SlERF4 and ethylene signalling-related genes, which blocks anti-Xcv immunity [69�]. Xcv: Xanthomonas euvesicatoria. (d) The mono-ADP-
ribosyltransferase HopU1 from Pst targets the RNA-binding protein GRP7 resulting in suppressed GRP7 binding of FLS2 transcripts, reduced FSL2
accumulation and inhibited PTI signalling [73�,74]. (e) HaRxL44 from Hpa interacts with the Med19 subunit of the mediator complex, which activates and
suppresses JA/ET and SA signalling respectively suppressing defence against biotrophs. Hpa: Hyaloperonospora arabidopsidis [77��].
www.sciencedirect.com Current Opinion in Plant Biology 2014, 20:35–46
The nuclear-localized effector HaRxL44 from Hyaloper-
onospora arabidopsidis (Hpa) interacts with the Mediator
complex subunit 19a (Med19a), which is a positive reg-
ulator of resistance to Hpa [77��]. This interaction results
in Med19a proteasomal degradation and increased and
decreased JA/ET and SA signalling, respectively. In
agreement with this finding, Hpa abolishes expression
of the SA marker gene PR1 specifically in haustoria-
dation of Med19a thus enhances susceptibility to Hpa
through attenuation of SA signalling (Fig. 3e).
ConclusionsBeyond the obvious contribution of TFs to modulation of
gene expression, recent groundbreaking studies have
shown that intracellular immune sensors display crucial
nuclear activities for efficient defence signalling, thereby
providing a direct link between pathogen perception and
defence-related gene expression. However, not every
NLR appears to function in the nucleus. For example,
the CNL RPM1 is located and functions at the plasma
membrane to initiate defence signalling [78]. Since
RPM1 was not found to translocate to the nucleus, the
question of how signals generated at the plasma mem-
brane are transduced to defence-related transcriptional
changes remains to be answered. Further work is clearly
necessary to shed light on the commonalities and specifi-
cities of the transcriptional responses downstream the
activation of nuclear and plasma membrane-located
immune receptors.
Although studies on RPS4 and MLA R proteins suggest
that programmed cell death may be uncoupled from
mechanisms that restrict bacterial growth, this is not a
universal principle for NLR defence signalling as exem-
plified by the nucleocytoplasmic CNL Rx that is acti-
vated in the cytoplasm by the Potato Virus X (PVX) coat
protein [79��]. Retention of Rx in the cytoplasm, which is
mediated by its interaction with the regulator of nucleo-
cytoplasmic traffic RanGAP2, is an essential requirement
to trigger cell death and resistance to PVX [79��,80�].
Overall, these studies suggest that coordination between
the cytoplasmic and nuclear compartments is a key fea-
ture directing effective defence outputs at least in a
significant number of cases. Nevertheless, the molecular
mechanisms that govern and are directed by nucleocyto-
plasmic partitioning of NLR immune receptors remain
elusive and clearly warrant further investigation. An
exciting possibility that needs to be explored in the future
is that nuclear-localized R proteins may directly promote
transcriptional regulation of target genes, as already
described for mammalian NLR immune regulators
[81]. For example, RPS4 and the TNL WRKY
domain-containing RRS1 cooperate genetically and con-
fer resistance to bacterial and fungal pathogens [82]. It is
thus tempting to hypothesize that effector-mediated acti-
vation of RPS4/RRS1 may promote transcriptional
regulation of target genes through RRS1 WRKY domain,
perhaps following a yet to be demonstrated RPS4–RRS1
physical interaction [83]. Finally, in order to obtain an
integrated view of the transcriptional changes associated
to plant defence responses, knowledge on mechanisms
used by plants to mount appropriate defence outputs
need to be brought together with new findings on the
molecular strategies used by microbes to subvert defence
signalling in host cells.
Within the current heyday of high-throughput genomic
and transcriptomic methodologies, a comprehensive over-
view of the global transcriptional changes in cells under-
going pathogen attack is starting to emerge. These global
studies (i) suggest a significant overlap in transcriptional
changes during PTI and ETI responses, (ii) highlight the
complexity of the molecular mechanisms involved in
defence-related transcriptional reprogramming of plant
cells, and (iii) represent an extremely valuable source of
information for further analyses aimed at understanding
the transcriptional control of plant immunity. Indeed, in
depth analysis of these global datasets should shed light
on the large-scale transcriptomic changes undergone by
plant cells during their interaction with microbes. Finally,
large-scale proteomic approaches represent an ideal
complement of global gene expression analyses and are
clearly indispensable to get a more complete picture of
the composition of protein complexes and the post-trans-
lational modifications that play a major role during the
regulation of protein activity.
AcknowledgementsWe apologize to all colleagues whose work could not be discussed becauseof space limitations. P.B. is funded by a grant from the French Ministry ofNational Education and Research/French Laboratory of Excellence project‘‘TULIP’’ (ANR-10-LABX-41; ANR-11-IDEX-0002-02). Our work issupported by the French Laboratory of Excellence project ‘‘TULIP’’(ANR-10-LABX-41; ANR-11-IDEX-0002-02).
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� of special interest
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39.�
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51.��
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55.��
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44 Biotic interactions
Current Opinion in Plant Biology 2014, 20:35–46 www.sciencedirect.com
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56.��
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57.��
Deng D, Yan C, Pan X, Mahfouz M, Wang J, Zhu JK, Shi Y, Yan N:Structural basis for sequence-specific recognition of DNA byTAL effectors. Science 2012, 335:720-723.
This study shows crystal structures of a 11.5-repeat artificially engineeredTAL effector, dHax3, in both DNA-free and DNA-bound states. See alsoRef. [58��].
58.��
Mak AN, Bradley P, Cernadas RA, Bogdanove AJ, Stoddard BL:The crystal structure of TAL effector PthXo1 bound to its DNAtarget. Science 2012, 335:716-719.
This paper shows the crystal structure of the Xanthomonas TAL effectorPthXo1 bound to its target DNA sequence. See also Ref. [57��].
59. Strauss T, van Poecke RM, Strauss A, Romer P, Minsavage GV,Singh S, Wolf C, Kim S, Lee HA, Yeom SI et al.: RNA-seqpinpoints a Xanthomonas TAL-effector activated resistancegene in a large-crop genome. Proc Natl Acad Sci U S A 2012,109:19480-19485.
60.�
Li T, Liu B, Spalding MH, Weeks DP, Yang B: High-efficiencyTALEN-based gene editing produces disease-resistant rice.Nat Biotechnol 2012, 30:390-392.
The authors exploit TALEN-based disruption to edit a specific ricesusceptibility gene, Os11N3, and engineer resistance to bacterial blight.This study illustrates the potential of TALEN-based technologies toengineer heritable genome modifications for plant resistance.
61.�
Chen LQ, Hou BH, Lalonde S, Takanaga H, Hartung ML, Qu XQ,Guo WJ, Kim JG, Underwood W, Chaudhuri B et al.: Sugartransporters for intercellular exchange and nutrition ofpathogens. Nature 2010, 468:527-532.
This work shows that biotrophic bacteria and fungi induce the expressionof SWEET genes, suggesting that sugar efflux by SWEET transporters isprobably targeted by pathogens for nutritional gain. See also Ref. [62].
62. Antony G, Zhou J, Huang S, Li T, Liu B, White F, Yang B: Rice xa13recessive resistance to bacterial blight is defeated byinduction of the disease susceptibility gene Os-11N3. Plant Cell2010, 22:3864-3870.
63. Vailleau F, Daniel X, Tronchet M, Montillet JL, Triantaphylides C,Roby D: A R2R3-MYB gene, AtMYB30, acts as a positiveregulator of the hypersensitive cell death program in plants inresponse to pathogen attack. Proc Natl Acad Sci U S A 2002,99:10179-10184.
64. Raffaele S, Vailleau F, Leger A, Joubes J, Miersch O, Huard C,Blee E, Mongrand S, Domergue F, Roby D: A MYB transcriptionfactor regulates very-long-chain fatty acid biosynthesis foractivation of the hypersensitive cell death response inArabidopsis. Plant Cell 2008, 20:752-767.
65. Raffaele S, Rivas S: Regulate and be regulated: integration ofdefense and other signals by the AtMYB30 transcriptionfactor. Front Plant Sci 2013, 4:98.
66.�
Froidure S, Canonne J, Daniel X, Jauneau A, Briere C, Roby D,Rivas S: AtsPLA2-alpha nuclear relocalization by theArabidopsis transcription factor AtMYB30 leads to repressionof the plant defense response. Proc Natl Acad Sci U S A 2010,107:15281-15286.
This study describes the nuclear relocalization of a secreted phospho-lipase to negatively regulate defence-related transcriptional responsesmediated by the transcription factor MYB30. This work identifies a novelfunction for a phospholipase beyond the classical lipid hydrolyzingactivities.
67. Marino D, Froidure S, Canonne J, Ben Khaled S, Khafif M,Pouzet C, Jauneau A, Roby D, Rivas S: Arabidopsis ubiquitinligase MIEL1 mediates degradation of the transcription factorMYB30 weakening plant defence. Nat Commun 2013, 4:1476.
68.�
Canonne J, Marino D, Jauneau A, Pouzet C, Briere C, Roby D,Rivas S: The Xanthomonas type III effector XopD targets the
Arabidopsis transcription factor AtMYB30 to suppress plantdefence. The Plant Cell 2011, 23:3498-3511.
This work shows that, in Arabidopsis, the Xanthomonas effector XopDdirectly targets the nuclear MYB transcription factor MYB30, resulting insuppressed MYB30-mediated transcriptional activation and defenceresponses.
69.�
Kim JG, Stork W, Mudgett MB: Xanthomonas type III effectorXopD desumoylates tomato transcription factor SlERF4 tosuppress ethylene responses and promote pathogen growth.Cell Host Microbe 2013, 13:143-154.
The authors demonstrate that, in tomato, the Xanthomonas effector XopDtargets and deSUMOylates the nuclear transcription factor SlERF4 sup-pressing ethylene production, which is required for immunity againstXanthomonas and symptom development.
70. Block A, Toruno TY, Elowsky CG, Zhang C, Steinbrenner J,Beynon J, Alfano JR: The Pseudomonas syringae type IIIeffector HopD1 suppresses effector-triggered immunity,localizes to the endoplasmic reticulum, and targets theArabidopsis transcription factor NTL9. New Phytol 2013,201:1358-1370.
71.��
Gimenez-Ibanez S, Boter M, Fernandez-Barbero G, Chini A,Rathjen JP, Solano R: The bacterial effector HopX1 targets JAZtranscriptional repressors to activate jasmonate signaling andpromote infection in Arabidopsis. PLoS Biol 2014, 12:e1001792.
This study shows that the effector HopX1 interacts with and promotes thedegradation of JAZ repressors, through its cysteine protease activity.Expression of HopX1 in Arabidopsis induces the expression of JA-dependent genes and represses SA signalling. When delivered by bac-teria, HopX1 promotes plant susceptibility to a similar extent as theaddition of the JA-mimicking phytotoxin coronatine. See also the workof Jian et al. (Ref. [72��]).
72.��
Jiang S, Yao J, Ma KW, Zhou H, Song J, He SY, Ma W: Bacterialeffector activates jasmonate signaling by directly targetingJAZ transcriptional repressors. PLoS Pathog 2013, 9:e1003715.
The authors show that the effector HopZ1a interacts with and acetylatesJAZ proteins. Inoculation with Pseudomonas producing HopZ1a, but nota HopZ1a catalytic mutant, promotes degradation of JAZ repressors andactivates JA signallin. Furthermore, HopZ1a partially rescues the viru-lence defect of a Pseudomonas strain unable to produce coronatine. Thiswork, together with the work of Gimenez-Inanez et al. (Ref. [71��])suggests that the JA receptor complex is potentially a target hub forbacterial pathogens.
73.�
Fu ZQ, Guo M, Jeong BR, Tian F, Elthon TE, Cerny RL, Staiger D,Alfano JR: A type III effector ADP-ribosylates RNA-bindingproteins and quells plant immunity. Nature 2007, 447:284-288.
This study identifies the Pseudomonas effector HopU1 as a mono-ADP-ribosyltransferase able to ADP-ribosylate the Arabidopsis glycine-richRNA-binding protein GRP7 and suppress plant immunity.
74. Jeong BR, Lin Y, Joe A, Guo M, Korneli C, Yang H, Wang P, Yu M,Cerny RL, Staiger D et al.: Structure function analysis of an ADP-ribosyltransferase type III effector and its RNA-binding targetin plant immunity. J Biol Chem 2011, 286:43272-43281.
75.�
Nicaise V, Joe A, Jeong BR, Korneli C, Boutrot F, Westedt I,Staiger D, Alfano JR, Zipfel C: Pseudomonas HopU1 modulatesplant immune receptor levels by blocking the interaction oftheir mRNAs with GRP7. EMBO J 2013, 32:701-712.
This work extends the findings of Fu and co-workers (Ref. [73�]). Theauthors demonstrate that GRP7 binds to FLS2 transcripts in vivo and thatthis interaction is inhibited in the presence of HopU1, resulting in reducedFLS2 protein accumulation and suppressed PTI responses.
76. Conaway RC, Conaway JW: Origins and activity of the Mediatorcomplex. Semin Cell Dev Biol 2011, 22:729-734.
77.��
Caillaud MC, Asai S, Rallapalli G, Piquerez S, Fabro G, Jones JD: Adowny mildew effector attenuates salicylic acid-triggeredimmunity in Arabidopsis by interacting with the host mediatorcomplex. PLoS Biol 2013, 11:e1001732.
This work shows the nuclear interaction of the Hyaloperonospora arabi-dopsidis effector HaRxL44 with the subunit Med19a of the Mediatorcomplex, which results in degradation of Med19a in a proteasome-dependent manner. Med19a is a positive regulator of resistance to H.Arabidopsidis and HaRxL44 targeting of Med19a leads to enhanced JA/ET and decreased SA signalling, which increases susceptibility to bio-troph pathogens by attenuating SA-dependent gene expression.
Transcriptional control of plant immunity Buscaill and Rivas 45
www.sciencedirect.com Current Opinion in Plant Biology 2014, 20:35–46
maculicola 1 (RPM1) is activated at, and functions on, theplasma membrane. Proc Natl Acad Sci U S A 2011,108:7619-7624.
79.��
Slootweg E, Roosien J, Spiridon LN, Petrescu AJ, Tameling W,Joosten M, Pomp R, van Schaik C, Dees R, Borst JW et al.:Nucleocytoplasmic distribution is required for activation ofresistance by the potato NB-LRR receptor Rx1 and isbalanced by its functional domains. Plant Cell 2010,22:4195-4215.
This work shows that interdomain interactions and folding states deter-mine the nucleocytoplasmic distribution of the potato R protein Rx1. Incontrast to the findings by Heidrich et al. (Ref. [50��]) and by Bai et al; (Ref[42]), the authors demonstrate that Rx1 is activated in the cytoplasm andcannot be activated in the nucleus. See also Ref. [81].
80.�
Tameling WI, Nooijen C, Ludwig N, Boter M, Slootweg E,Goverse A, Shirasu K, Joosten MH: RanGAP2 mediatesnucleocytoplasmic partitioning of the NB-LRR immunereceptor Rx in the Solanaceae, thereby dictating Rx function.Plant Cell 2010, 22:4176-4194.
This study shows that nucleocytoplasmic partitioning of Rx is regulatedby its interaction with RanGAP2, a protein that is involved in nucleocy-toplasmic trafficking of macromolecules through nuclear pores and that isrequired for extreme resistance to Potato Virus X. Together with the study
by Slootweeg and collaborators (Ref. [79��]), this study shows the crucialrole of nucleocytoplasmic distribution of Rx during the establishement ofdisease resistance.
81. Meissner TB, Li A, Biswas A, Lee KH, Liu YJ, Bayir E, Iliopoulos D,van den Elsen PJ, Kobayashi KS: NLR family member NLRC5 is atranscriptional regulator of MHC class I genes. Proc Natl AcadSci U S A 2010, 107:13794-13799.
82. Narusaka M, Shirasu K, Noutoshi Y, Kubo Y, Shiraishi T,Iwabuchi M, Narusaka Y: RRS1 and RPS4 provide a dualResistance-gene system against fungal and bacterialpathogens. Plant J 2009, 60:218-226.
84. Kim SH, Gao F, Bhattacharjee S, Adiasor JA, Nam JC,Gassmann W: The Arabidopsis resistance-like gene SNC1 isactivated by mutations in SRFR1 and contributes to resistanceto the bacterial effector AvrRps4. PLoS Pathog 2010,6:e1001172.
46 Biotic interactions
Current Opinion in Plant Biology 2014, 20:35–46 www.sciencedirect.com
Figure 19. Schematic representation of the AtMYB30 protein. As other R2R3-MYB TFs, AtMYB30 presents an N-terminal MYB domain and a C-terminal
transactivation domain. C-terminal motifs 1, 2 and 3 were used to classify AtMYB30 in the
subgroup 1 of R2R3-MYB proteins.
TAD 2 R2 R3 1 3 C N
1 11 115 234 264 323
MYB Domain
Transcriptional
Activation Domain
(A) (B)
Figure 20. Analysis of AtMYB30 expression in Arabidopsis upon bacterial infection
(From Daniel et al., 1999). (A) RT-PCR analysis of the expression of AtMYB30 in Arabidopsis resistant (Col-0) or sensitive (Sf-
2) ecotypes, following inoculation with H2O or with the avirulent strain Xcc147, as indicated.
(B) Analysis by RT-PCR of AtMYB30 expression in Arabidopsis in response to virulent Pst DC3000
or avirulent Pst DC3000 AvrB or Pst DC3000 AvrRpm1 strains.
52
3. AtMYB30 a positive regulator of the HR in A. thaliana
3.1. Identification of AtMYB30
A differential screening was previously performed in our team in order to identify genes
potentially regulating the early events of the establishment of the HR in Arabidopsis thaliana.
This screen was based on the inoculation of Arabidopsis cell suspensions pre-treated with
cycloheximide (in order to focus on genes whose expression did not depend on de novo
protein biosynthesis) with two different strains of Xanthomonas campestris pv. campestris
(Xcc): the avirulent strain Xcc147 that leads to the development of the HR in Arabidopsis,
and the non-pathogenenic strain Xcc8B2 that is asymptomatic due to the deletion of the hrp
cluster. This differential screening allowed the identification of 27 genes early transcribed
during the establishment of the HR. These genes were named Arabidopsis thaliana
hypersensitivity-related (Athsr) and grouped in seven different gene families (Lacomme and
Roby, 1999). Sequence analysis indicated that one of these clones corresponded to a single-
copy gene that encoded the protein AtMYB30, a member of the family of R2R3 class of plant
MYB TFs (Lacomme and Roby, 1999, Daniel et al., 1999) (Figure 19). Given the potentially
interesting role of AtMYB30 during the establishment of the HR, its functional analysis was
next initiated.
3.2. Expression and function of AtMYB30
The analysis of the expression pattern of AtMYB30 was performed in Arabidopsis plants and
in cultured Arabidopsis cells infected with either virulent or avirulent strains of Xcc or Pst.
This study showed that the AtMYB30 transcript is early, transiently and specifically detected
after infection by avirulent bacteria (Figure 20). In contrast, AtMYB30 expression was not
detected in compatible interactions that lead to disease development, or in response to an
asymptomatic hrp- mutant of Xcc (Lacomme and Roby, 1999, Daniel et al., 1999).
Furthermore, in order to better understand the mode of action of AtMYB30, AtMYB30 gene
expression was monitored in Arabidopsis mutant plants affected either in the initiation or in
Figure 21. Overexpression of AtMYB30 in tobacco leads to accelerated HR in
response to inoculation with different pathogens (From Vailleau et al., 2002). (A) Phenotypes of wild-type tobacco and AtMYB30-overexpressing (AtMYB30OE) lines in response
to inoculation with R. solanacearum. Different inocula were used for the avirulent strain
(GMI1000), ranging from 5x107 cfu/ml (no. 1), 107 cfu/ml (no. 2), to 5x106 cfuml (no. 3). The
virulent strain (K60) was inoculated at 5x107 cfu/ml (no. 4), and a control inoculation was
performed with water (no. 5). Symptoms are shown 20 hours post inoculation (left) and 6
days post inoculation (right).
(B) Disease symptoms caused by Cercospora nicotianae 14 days after inoculation in the wild-type
and AtMYB30-overexpressing (AtMYB30OE) lines. The black circle indicates the inoculated
zone.
(B)
(A)
Wild type AtMYB30OE
Wild type Wild type AtMYB30OE AtMYB30OE
20 hours post inoculation 6 days post inoculation
53
the propagation of the HR (“initiation class” or “propagation class” mutants). AtMYB30 was
constitutively expressed in initiation mutants lsd4 and lsd5 (exhibiting spontaneous necrotic
lesions simulating disease resistance in the absence of the pathogen) and was expressed
only under lesion promoting conditions in lsd3 mutant plants. AtMYB30 transcripts did not
accumulate in different phx (phoenix) mutants that act as suppressors of the lsd5 mutation.
Similarly, the AtMYB30 transcript was not detectable in the propagation mutant lsd1, which is
hyper-responsive to cell death initiators and unable to limit the extent of cell death. These
results suggest a strong correlation between AtMYB30 expression and genetically controlled
cell death and indicate that AtMYB30 expression is associated with the initiation rather than
the spread of the cell death (Lacomme and Roby, 1999, Daniel et al., 1999).
A functional analysis of AtMYB30 during the HR was then conducted through the use of
transgenic tobacco and Arabidopsis plants deregulated for AtMYB30 expression. In these
plants, the coding sequence of AtMYB30 was expressed under the control of the constitutive
promoter 35S from Cauliflower Mosaic Virus either in the sense (AtMYB30OE) or the
antisense (AtMYB30AS) orientation. As compared to wild-type plants, AtMYB30OE plants
showed accelerated and stronger HR, enhanced PR1 defence gene expression and reduced
bacterial growth in response to avirulent bacterial strains (Ralstonia solanacearum GMI1000
in tobacco, and Pst DC3000 AvrRpm1 or Xcc147 in Arabidopsis). Interestingly, an HR-like
response and decreased plant susceptibility were observed when tobacco and Arabidopsis
AtMYB30OE plants were infected with virulent bacteria (Vailleau et al., 2002) (Figure 21A). In
addition, AtMYB30 overexpression in tobacco increased resistance against the fungal
pathogen Cercospora nicotianae (Figure 21B). On the other hand, plants overexpressing
AtMYB30 in an antisense orientation showed reverse phenotypes, with delayed and weaker
HR and resistance in response to avirulent pathogens, and enhanced disease symptoms and
bacterial growth rates in the context of a compatible interaction with various virulent
pathogens. In both interaction contexts, the observed phenotypes were associated with lower
PR1 marker gene expression. Together these data showed that AtMYB30 is a positive
54
regulator of the signalling pathway controlling the establishment of cell death-associated
resistance against pathogen attack (Vailleau et al., 2002).
3.3. Hormonal control of the AtMYB30-mediated HR
As mentioned in the previous section, SA plays a central role in the regulation of defence and
cell death-associated responses in Arabidopsis, particularly in response to biotrophic
pathogens (Pieterse et al., 2009). In order to elucidate whether AtMYB30 expression is
regulated by the SA pathway, AtMYB30 transcript levels were first quantified in Arabidopsis
mutants affected in both SA biosynthesis and signalling. AtMYB30 expression was found to
be reduced in SA-related mutants npr1, sid1 and sid2 as well as in plants overexpressing the
NahG gene that are unable to accumulate SA. In contrast, SA treatment induced AtMYB30
expression, confirming that AtMYB30 expression is SA-dependent. Moreover, altered
expression of AtMYB30 modulated SA levels and expression of SA-associated genes such
as ICS1 and PR1, suggesting that AtMYB30 expression may be critical to trigger the SA
defence signalling pathway. Overexpression of AtMYB30 in the NahG, sid1, sid2 or npr1
genetic backgrounds suppressed the enhanced cell death and resistance phenotypes
previously observed in AtMYB30OE plants, indicating that the phenotypes conferred by over-
expression of AtMYB30 are dependent on SA accumulation and signalling. Taken together
these data suggest that AtMYB30 is involved in an amplification loop of the signalling
cascade that modulates synthesis of the plant defence-related hormone SA, which in turn
modulates cell death (Raffaele et al., 2006).
The ability of AtMYB30 to activate JA production and JA-dependent defence responses was
also investigated. Modification of oxylipin profiles in AtMYB30 transgenic plants was also
reported (Vailleau et al., 2002). JA marker-gene analysis showed that AtMYB30 interferes
with the ability of JA to activate PDF1-2 and PR4 but not VSP1 and LOX3 marker gene
expression. Moreover, AtMYB30 overexpression in a jar1 mutant background, affected in JA
signal transduction, led to enhanced HR and resistance phenotypes indistinguishable from
those displayed by AtMYB30OE plants after inoculation by an avirulent strain of Pst. This
Figure 22. AtMYB30 modulates the expression of very long chain fatty acid
(VLCFA)-related genes after bacterial inoculation (From Raffaele et al., 2008). List of 18 genes identified as putative targets of AtMYB30. aAffymetrix Probe set number. bArabidopsis Genome Initiative number and corresponding putative function. Columns in the right
show fold changes in the mean expression levels from two independent experiments in inoculated
wild type compared with the wild type at t0 (WT1/WT0) and in the AtMYB30OE
line compared with
the wild type after Xcc147 inoculations (Ox/WT).
55
study production of JA and of 12-oxo-phytodienoic acid (OPDA), a JA precursor, was
evaluated by GC-MS and revealed that JA signal transduction does not play an essential role
in AtMYB30-mediated defence signalling (Raffaele et al., 2008).
3.4. Transcriptional targets of AtMYB30
To identify putative AtMYB30 target genes, a transcriptomic analysis with the Affymetrix chip
"Complete Genome" was performed using Arabidopsis wild-type, AtMYB30OE and
AtMYB30AS plants of the Ws-0 ecotype inoculated with the avirulent strain Xcc147. The
analysis of differentially expressed genes in the first 6 hours after inoculation led to the
identification of 18 genes as potential targets of AtMYB30 (Figure 22). Interestingly, 14 of
them presented a function related to lipid metabolism, and more particularly, in the lipid
biosynthesis pathway that leads to the production of VLCFAs (Figure 22). Within the VLCFA
pathway, genes encoding subunits of the Acyl-CoA Elongase complex were over-
represented suggesting that AtMYB30 modulates the early steps of fatty acid elongation.
VLCFAs are involved in the production of lipid second messengers, such as sphingolipids or
ceramides, or in the production of epicuticular waxes and all these molecules have been
shown to be involved in defence and cell death regulation (Raffaele et al., 2009, Berkey et
al., 2012, Markham et al., 2013).
Molecular, genetic and biochemical studies were next undertaken to validate these
transcriptomic data. Regulation of the expression of these 14 putative target genes by
AtMYB30 after bacterial inoculation was further confirmed by quantitative RT-PCR not only in
the transgenic lines but also in a T-DNA insertion knockout (atmyb30ko) mutant. Interestingly,
following inoculation, the expression of these genes was higher in AtMYB30OE and lower in
atmyb30ko and AtMYB30AS lines. These results are consistent with these genes being
transcriptional targets of AtMYB30. Further support for this idea was obtained in
transactivation assays in Nicotiana benthamiana, in which AtMYB30 expression led to
activation of the reporter genes GUS and GFP fused to the promoter of the candidate target
genes. In addition, the levels of VLCFAs from a sphingolipid-enriched fraction were affected
Figure 23. Schematic overview of metabolic pathways regulated by AtMYB30 during
the incompatible interaction between Arabidopsis and avirulent bacterial pathogens
(From Raffaele et al., 2008). Elements strongly and positively regulated by AtMYB30 are indicated in red (genes of the acyl-CoA
elongase complex, accumulation of very long fatty acids (VLCFAs), accumulation of salicylic acid
(SA), and cell death). Other elements positively but weakly regulated by AtMYB30 are indicated in
orange (upstream steps of VLCFA synthesis, wax- and cutin-related genes, and wax accumulation).
Elements shown in gray are not significantly regulated by AtMYB30, at least during the early
events of the interaction, and elements shown in blue are negatively regulated (directly or
indirectly) by AtMYB30 (expression of genes encoding fatty acid (FA) desaturases). Inoculation
could trigger the synthesis of new signalling molecules as indicated by the dotted arrow. These
molecules, together with other lipid-derived signals, such as SA, oxylipins, jasmonic acid (JA), and
phospholipids, would subsequently act for activation of the hypersensitive cell death. Synthesis of
these VLCFA-derived signals may be enhanced by AtMYB30. Upregulation of VLCFA synthesis in
non-challenged AtMYB30OE
plants allows enhanced accumulation of VLCFAs and of VLCFA
metabolizing enzymes. The cell is thus predisposed for a stronger and faster response to pathogen
Figure 25. Interaction between AtMYB30 and AtSBT5.2 in yeast. Yeasts are shown after growth for 5 days on low stringency (left; SD/-TL) or high stringency (right;
SD/-TLHA) media. Co-expression of AtMYB30 deleted from its C-terminal transcription activation
domain (MYB30DAD) and the isolated cDNA clone encoding the last 103 amino acids of AtSBT5.2
(SBT5.2) resulted in yeast growth on selective medium. In a control experiment, yeast cells expressing
MYB30DAD or SBT5.2 with controls provided by Clontech (T-antigen or P53, respectively) were not
able to grow on selective medium. BD, GAL4 DNA-binding domain; AD, GAL4 activation domain.
65
A protease of the subtilase family negatively regulates plant defence
through its interaction with the Arabidopsis transcription factor AtMYB30
Previous results: Identification of AtSBT5.2 as a new AtMYB30 interacting partner.
In order to search for AtMYB30-interacting partners, an AtMYB30 version deleted from its C-
terminal TAD (AtMYB30ΔAD) was previously used as bait to screen a Y2H Arabidopsis
cDNA library generated from mRNAs isolated from leaf tissue inoculated with the avirulent
bacterial strain Xcc147 (Froidure et al., 2010a). A cDNA clone encoding the last 103 amino
acids of the Arabidopsis serine protease of the subtilisin-like family AtSBT5.2 (At1g20160)
was identified (Figure 25). AtSBT5.2 belongs to subgroup V, which contains 6 members
(AtSBT5.1-6), within the classification of the 56 members of the Arabidopsis subtilase family
(Figure 15) (Schaller et al., 2012, Rautengarten et al., 2005).
Figure 26. AtSBT5.2 is alternatively spliced. (A) Two gene models (At1g20160.1 and At1g20160.2) for AtSBT5.2 as shown in the TAIR database.
Exons are shown as dark blue boxes, introns as blue lines between exons and 5’ and 3’ UTRs are
shown in light blue.
(B) RT-PCR analysis of AtSBT5.2(a) and AtSBT5.2(b) transcripts in Col-0 Arabidopsis leaves.
(C) Nucleotide sequences of 5’ ends of AtSBT5.2(a) and AtSBT5.2(b) transcripts as obtained by
5’RACE amplification. The ATG encoding the fist coding Met residue in each protein is boxed in
blue. Identical sequences are highlighted in red. From the ATG in AtSBT5.2(b) both nucleotide
sequences are also identical and, thus, not shown. Sequences used to specifically amplify
AtSBT5.2(a) or AtSBT5.2(b) are underlined.
(D) Schematic representation of AtSBT5.2(a) and AtSBT5.2(b) protein sequences. The signal peptide
(SP) and the prodomain (PD) in AtSBT5.2(a) are respectively shown as black and grey boxes.
Catalytical conserved residues Asp (D), His (H), Asn (N), and Ser (S) residues are indicated.
Putative N-glycosylation sites are represented by black dots and their amino acid position
indicated. The C-terminal region of 103 amino acids encoded by the partial cDNA clone identified
in the yeast two-hybrid screen as interacting with AtMYB30DAD is boxed in blue.
1.1. AtSBT5.2 is alternative spliced and encodes two distinct isoforms.
Two gene models (splice variants) are annotated in the Arabidosis database TAIR
(http://www.arabidopsis.org) for the gene AtSBT5.2 (At1g20160), suggesting that its
transcript is alternatively spliced (Figure 26A). These two splice variants (At1g20160.1 and
At1g20160.2) were renamed AtSBT5.2(a) and AtSBT5.2(b), respectively. The two
corresponding transcripts contain different 5’UTRs and are predicted to encode two distinct
proteins.
To first investigate the existence of the two transcripts in planta, specific primers were
designed for each 5’UTR (in sense orientation) and one common primer in the fourth exon of
the AtSBT5.2 sequence (in antisense orientation). Semi quantitative RT-PCR analysis, using
cDNA from Col-0 Arabidopsis leaves, allowed amplification of both transcripts demonstrating
that both AtSBT5.2(a) and AtSBT5.2(b) are expressed in planta (Figure 26B). 5’RACE
experiments followed by cDNA sequencing confirmed that two distinct transcripts exist in
Col-0 leaves. The sequences of the 5’ end of both AtSBT5.2(a) and AtSBT5.2(b) mRNAs are
presented in Figure 26C.
AtSBT5.2(a) corresponds to a transcript of 2402 bp, which is predicted to encode a 769
amino acid preproenzyme containing a 27 amino acid signal peptide followed by a
prodomain of 74 amino acids (amino acids 35 to 108) and a 661 amino acid mature
polypeptide with a predicted molecular mass of 69.5 kDa (AtSBT5.2(a)) (Figure 26D). In
contrast, AtSBT5.2(b) corresponds to a transcript of 2373 bp, which is predicted to encode a
protein of 730 amino acids with no SP, and lacking the first five amino acids of the prodomain
in AtSBT5.2(a) and a predicted molecular mass of 77 kDa (AtSBT5.2(b)) (Figure 26D).
Except for their N-terminal differences, the two corresponding encoded proteins are identical.
Both predicted proteins contain the three conserved amino acids of the catalytic triad
characteristic of the subtilase family. Indeed, on the basis of sequence similarities with other
Figure 27. Sequence alignment of AtSBT5.2(a) and AtSBT5.2(b) proteins. Identical amino acids are highlighted in blue. The signal peptide and prodomain in AtSBT5.2(a) are
boxed in red and yellow, respectively. Catalytical conserved residues are indicated by red dots.
Putative N-glycosylation sites (PGSs) are indicated by blue dots. The 103 C-terminal amino acids
encoded by the partial AtSBT5.2 cDNA clone identified in the yeast two-hybrid screen as interacting
with AtMYB30ΔAD is boxed in blue. A putative myristoylation domain in AtSBT5.2(b) is boxed in
green.
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
AtSBT5.2(a)
AtSBT5.2(b)
Signal peptide Prodomain
Figure 28. Subcellular localization studies show that AtST5.2(a) is secreted whereas
AtSBT5.2(b) is intracellular.
Confocal images of epidermal cells of N. benthamiana leaves 36 hours after Agrobacterium-
mediated transient expression of the indicated constructs. Bars, 10 µm. RFP, Red Fluorescent
Protein.
AtS
BT
5.2
(a)-
RF
P
RFP fluorescence Bright Field Merged
AtS
BT
5.2
(b)-
RF
P
Figure 29. Intercellular fluid isolation confirms that AtSBT5.2(a) is secreted whereas
AtSBT5.2(b) is intracellular. Western blot analysis of total protein extracts (TE) and intercellular fluids (IF) of N. benthamiana leaf
tissue co-expressing the intracellular protein MIEL1 (Marino et al., 2013) with AtSBT proteins. All
proteins were HA-tagged and detected using anti-HA antibodies (a-HA). Molecular mass markers in
kiloDaltons are indicated on the right.
AtS
BT
5.2
(b)-
HA
MIEL1-HA +
a-HA
. 130
. 95
. 34
. 26
. 72
. 43
. 55
MIEL1
AtS
BT
5.2
(a)-
HA
67
subtilases the amino acid residues D145, H210 and S546 in AtSBT5.2(a) and D106, H171
and S507 in AtSBT5.2(b) were identified as residues of the catalytic triad (Figure 26D). The
complete deduced amino acid sequences of AtSBT5.2(a) and AtSBT5.2(b) are presented in
Figure 27.
1.2. AtSBT5.2(a) is a secreted protein whereas AtSBT5.2(b) is intracellular.
Alternative splicing of AtSBT5.2 may have important implications on the subcellular
localization of the proteins encoded by the two transcripts. The presence of a SP and a
prodomain in AtSBT5.2(a) suggests that this protein may enter the secretory pathway and be
secreted to the extracellular space. Indeed, secretion of AtSBT5.2(a) was previously reported
(Engineer et al., 2014). In contrast, the absence of the SP and the first five amino acids of
the prodomain in AtSBT5.2(b) may prevent this protein from being secreted. In order to test
this possibility, the subcellular localization of the two proteins was first investigated using
Agrobacterium-mediated transient expression of RFP-tagged AtSBT5.2(a) and AtSBT5.2(b)
versions under the control of the constitutive 35S promoter in leaf epidermal cells of N.
benthamiana. As expected, AtSBT5.2(a) was found to be located in the extracellular space,
confirming that AtSBT5.2(a) is a secreted protein (Figure 28). In contrast, AtSBT5.2(b) was
not secreted but detected in mobile punctuated structures inside cells (Figure 28).
In order to obtain biochemical validation of the distinct subcellular localization of AtSBT5.2(a)
and AtSBT5.2(b), HA-tagged versions of AtSBT5.2(a) and AtSBT5.2(b) were transiently
expressed in N. benthamiana and intercellular fluid (IF), where the secreted proteins are
expected to be present, was isolated. In order to control the detection of intracellular proteins
in the IF, the intracellular protein MIEL1 (Marino et al., 2013) was co-expressed with
AtSBT5.2 proteins in these assays. Being intracellular, MIEL1 was systematically detected in
the total extract fraction (TE) and not in the IF, confirming that the IF fraction did not contain
intracellular proteins due to undesired cellular lysis during IF isolation (Figure 29).
Figure 31. Sequence alignment of AtSBT5.2(a) and AtSBT5.1 proteins. Identical amino acids are highlighted in blue. Signal peptides and prodomains are boxed in red and
yellow, respectively. Catalytical conserved residues are indicated by red dots. Putative N-
glycosylation sites are boxed in orange. The 103 C-terminal amino acids encoded by the partial
AtSBT5.2 cDNA clone identified in the yeast two-hybrid screen as interacting with AtMYB30DAD are
underlined.
Figure 30. Schematic representation of AtSBT5.2(a) and AtSBT5.1 protein sequences. The signal peptide (SP) and the prodomain (PD) in AtSBT5.2(a) and its closest homolog AtSBT5.1 are
respectively shown as black and grey boxes. Catalytically conserved Asp (D), His (H), Asn (N), and Ser
(S) residues are indicated. Putative N-glycosylation sites are represented by black dots, and their
amino acid positions indicated, except for shared PGSs between AtSBT5.2 and AtSBT5.1, which are
represented by red dots.
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
AtSBT5.2(a)
AtSBT5.1
Signal peptide Prodomain
AtSBT5.1 - 780 1 -
SP PD
D H N S
_ 1
97
_ 2
30
_ 4
71
_ 7
76
AtSBT5.2(a) - 769 1 -
SP PD
D H N S
_ 2
25
_ 3
63
_ 4
67
_ 5
25
_ 6
36
_
65
0
_ 6
78
68
AtSBT5.2(a) was detected in the IF, whereas AtSBT5.2(b) was exclusively detected in the
TE and never in the IF fraction (Figure 29). These results demonstrate the secretion and
intracellular localization of AtSBT5.2(a) and AtSBT5.2(b), respectively.
1.3. AtSBT5.2(a), but not AtSBT5.2(b), is glycosylated in planta.
In silico analysis of AtSBT5.2 proteins indicated that both polypeptides comprise seven
Putative asparagine-linked Glycosylation Sites (PGS; N in NxS/T motifs): amino acids N225,
N363, N467, N522, N636, N650 and N678 in AtSBT5.2(a), and N186, N324, N428, N486,
N597, N611 and N639 in AtSBT5.2(b) (Figure 26 and 27). According to the Rautengarten
phylogenetic classification (Figure 15), the closest homolog of AtSBT5.2 is AtSBT5.1
(At1g20150). In contrast to AtSBT5.2, a single gene model (AtSBT5.1) is annotated for
At1g20150 in the TAIR database, suggesting that AtSBT5.1 is not alternatively spliced.
AtSBT5.1 corresponds to a transcript of 2343 bp, which is predicted to encode a 780 amino
acid preproenzyme containing a 25 amino acids SP followed by an 78-amino acid prodomain
(amino acids 28 to 106) and a 674 amino acid mature polypeptide with a predicted molecular
mass of 73.8 kDa (Figure 30). The amino acid residues Asp-146, His-215 and Ser-550 were
identified as residues of the catalytic triad in AtSBT5.1 (Figure 30). AtSBT5.1 shows four
PGSs (N197, N230, N471 and N776) two of which (N230 and N471) are conserved in
AtSBT5.2 (Figure 30). Figure 31 shows an alignment of AtSBT5.2(a) and AtSBT5.1 protein
sequences.
To first investigate whether AtSBT5.2 proteins are glycosylated in planta protein extracts
from N. benthamiana leaves transiently expressing AtSBT5.2(a) and AtSBT5.2(b) were
subjected to purification using a concanavalin A resin. Concanavalin A is a lectin
(carbohydrate-binding protein) that is often used to purify glycosylated macromolecules by
affinity chromatography. As shown in Figure 32A, AtSBT5.2(a) binds to the concanavalin A
resin from which it can be eluted by adding an excess of a-methyl-D-glycosamide and a-
Figure 32. AtSBT5.2(a), but not AtSBT5.2(b), is glycosylated in planta. The indicated HA-tagged AtSBT proteins were transiently expressed in N. benthamiana leaves.
Proteins were detected by immunoblot with anti-HA antibodies (a-HA). Molecular mass markers in
kiloDaltons are indicated on the right.
(A) HA-tagged AtSBT5.1 and AtSBT5.2(a), but not AtSBT5.2(b), can be affinity purified using a
concanavalin A resin. The presence of different proteins at the indicated steps of the affinity
purification is shown.
(B) AtSBT5.1 and AtSBT5.2(a), but not AtSBT5.2(b), are deglycosylated by PNGase F or Endo H.
Protein extracts containing the indicated HA-tagged AtSBT proteins were treated (+) or not (-)
with PNGase F or Endo H.
(C) Glycosylation of HA-tagged AtSBT5.1 and AtSBT5.2(a), but not AtSBT5.2(b), is blocked by
tunicamycin treatment N. benthamiana leaves transiently expressing the indicated proteins were
treated (+) or not (-) with tunicamycin; as indicated. Ponceau S staining confirms equal loading.
(B)
(A)
(C)
69
methyl-D-manosamide. AtSBT5.1 was also purified under the same conditions (Figure 32A),
suggesting that both AtSBT5.2(a) and AtSBT5.1 are glycosylated in planta.
In order to obtain additional proof of the in planta N-glycosylation of these subtilases, protein
extracts containing AtSBT5.2(a) and AtSBT5.1 were analysed by Western blot after
treatment with deglycosylases PNGase F or EndoH. The electrophoretic mobility shift
observed in Figure 32B confirmed that AtSBT5.2(a) and AtSBT5.1 are N-deglycosylated and
that the N-linked carbohydrate is very likely to be high manose. Finally, we investigated the
effect of tunicamycin, which inhibits N-linked glycosylation of newly synthesized
glycoproteins in the ER (Bassik and Kampmann, 2011), on glycosylation of AtSBT5.2(a) and
AtSBT5.1 proteins. The reduced electrophoretic mobility observed after tunicamycin
treatment in the case of AtSBT5.2(a) and AtSBT5.1 provided further evidence of the in planta
N-glycosylation of AtSBT5.2(a) and AtSBT5.1 (Figure 32C). It is worth noting that tunicamyn
treatment resulted in reduced accumulation of both AtSBT5.2(a) and AtSBT5.1, suggesting
that glycosylation may contribute to the stability of both subtilases.
Finally, to determine the contribution of each putative PGS to AtSBT5.2(a) and AtSBT5.1 N-
glycosylation in planta, individual PGS removal mutants, in which the N residue was replaced
by A, were transiently expressed in N. benthamiana and analysed on high resolution SDS-
PAGE gels to determine their electrophoretic mobility as compared to that of wild-type
proteins. Protein extracts containing mutant proteins were separated on 7.5% acrylamide
SDS-PAGE gels and run overnight at low voltage, with interspaced wild-type AtSBT5.2(a)
protein to facilitate detection of the small size difference expected from removing just one
PGS. This analysis revealed slightly, but significantly, reduced mobility for all PGS mutants in
AtSBT5.2(a) as compared to wild-type AtSBT5.2(a) (Figure 33A), suggesting that all PGS in
AtSBT5.2(a) are used in planta. Similarly, a reduction in the electrophoretic mobility was
observed for all AtSBT5.1 N-glycosylation mutants, except N471A, indicating that all PGS but
not N471, [which is conserved (Figure 31) and glycosylated in AtSBT5.2(a) (Figure 33A)] are
used for AtSBT5.1 glycosylation in planta (Figure 33B).
Figure 33. All PGS in AtSBT5.2(a) are used for glycosylation in planta.
Electrophoretic mobility of HA-tagged individual PGS removal AtSBT5.2(a) (A) and AtSBT5.1 (B)
mutants. N to A substitutions in AtSBT5.2(a) and AtSBT5.1 are indicated. Wild-type (WT) AtSBT5.2(a)
or AtSBT5.1 proteins were interspersed to facilitate detection of the mobility shifts. The PGS not used
for glycosylation in AtSBT5.1 is indicated in red. Western blot analyses were performed using anti-HA
antibodies. Molecular mass markers in kiloDaltons are indicated on the right.
(B)
(A)
Figure 34. AtSBT5.2(a) self cleaves in planta. Protein extracts containing the indicated HA-tagged AtSBT5.2 proteins transiently expressed in N.
benthamiana and analysed by Western blot using anti-HA antibodies (a-HA). Ponceau S staining of
ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) for confirmation of equal loading in each
lane is also shown (bottom). Molecular mass markers in kiloDaltons are indicated on the right.
. 130
. 95
Ponceau S
AtSBT5.2(a) unprocessed
AtSBT5.2(a) processed
AtSBT5.2(b)
a-HA
Rubisco
70
Taken together, affinity purification using concanavalin A, deglycosylation using PNGase F or
Endoglycosidase H, tunicamycin treatment of N. benthamiana leaves expressing the proteins
under study as well as systematic mutagenesis of PGS demonstrate that AtSBT5.2(a) and
AtSBT5.1 are glycosylated in planta.
Despite the fact that AtSBT5.2(b) contains the seven PGSs present in AtSBT5.2(a), (i) no
AtSBT5.2(b) binding to or elution from a concanavalin A resin was observed (Figure 32A) (ii)
AtSBT5.2(b) electrophoretic mobility was not modified after treatment with PNGase F or
EndoH (Figure 32B); and (iii) no effect of tunicamycin treatment on the AtSBT5.2(b)
electrophoresis profile was detected (Figure 32C). These results, which are consistent with
the absence of a SP in AtSBT5.2(b) and our previous observation that AtSBT5.2(b) is not
secreted, strongly suggest that AtSBT5.2(b) does not enter the secretory pathway and is
therefore not N-glycosylated.
1.4. AtSBT5.2(a) is an active serine protease.
As mentioned in section 1.3.4 of the introduction, subtilases, as other proteases, are typically
able to catalyze their self-processing to render a mature active polypeptide. In addition, the
presence of the three conserved amino acids in the catalytic triad of AtSBT5.2 proteins is
consistent with a possible protease activity of these proteins. When transiently expressing
AtSBT5.2(a) in leaf epidermal cells of N. benthamiana, two protein bands were detected that
may correspond to the processed and unprocessed forms of the protease (Figure 34). A
single band was detected for AtSBT5.2(b), suggesting that this protein is either not
processed or fully processed in planta (Figure 34). In order to learn more about proteolytic
cleavage of AtSBT5.2 proteins, AtSBT5.2(a) and AtSBT5.2(b) catalytic mutant versions were
generated, in which the conserved histidine residue in the catalytic triad of the proteins was
mutated to Alanine, (AtSBT5.2(a)-H210A and AtSBT5.2(b)-H171A). Following transient
expression in N. benthamiana leaf epidermal cells, mutation of the catalytic histidine residue
did not affect migration of AtSBT5.2(b) as compared to the wild-type protein, suggesting that,
consistent with the absence of a SP in AtSBT5.2(b), this protein is not processed in planta
Figure 35. AtSBT5.2(a) is an active serine hydrolase.
Protein extracts from N. benthamiana leaves transiently expressing the indicated HA-tagged AtSBT5.2
proteins were incubated with the ActivX Desthiobiotin-FP serine hydrolase probe. Protein extracts
from untreated N. benthamiana leaves and leaves transformed with an empty vector construct were
included as controls. Western blot analyses were performed using anti-HA or streptavidin antibodies.
Ponceau S staining confirms equal loading. Molecular mass markers in kiloDaltons are indicated on
the right. This experiment was performed five times with identical results.
Figure 36. Mutation of some glycosylated residues affects the catalytic activity of
AtSBT5.2(a). N. benthamiana leaf extracts expressing either HA-tagged AtSBT5.2(a) wild type, catalytic mutant or
PGS point mutant versions were incubated with ActivX Desthiobiotin-FP serine hydrolase probe.
Western blot analyses were performed using anti-HA or streptavidin antibodies. Ponceau staining
confirms equal loading. Molecular mass markers in kiloDaltons are indicated on the right. Similar
results were obtained in three independent experiments.
71
(Figure 34). In contrast, when expressing AtSBT5.2(a)-H210A, only the slow migrating band,
that very likely corresponds to the unprocessed form of the protein, was detected thus
suggesting that AtSBT5.2(a) is able to auto-process in planta and thus be active as a
protease (Figure 34).
Being a subtilase, we may hypothesize that AtSBT5.2(b) interaction with AtMYB30 may lead
to proteolytic degradation of the TF, perhaps providing a molecular mechanism of alleviation
of its activity. The catalytic activity of HA-tagged AtSBT5.2(a) and AtSBT5.2(b) was thus
investigated using an activity-based profiling (ABP) assay with a biotin-conjugated
fluorophosphonate (FP) probe able to bind specifically and irreversibly to the catalytic site of
active serine proteases. Biotin conjugation of the FP probe allows ready detection of active
serine proteases by Western blot using HRP-labelled streptavidin. AtSBT5.2(a), AtSBT5.2(b)
and their respective catalytic mutants were expressed in N. benthamiana leaves and the
corresponding protein extracts were incubated with the FP serine hydrolase probe. A specific
labelled band was detected for AtSBT5.2(a), whereas no signal was detected for its catalytic
mutant version AtSBT5.2(a)H210A, reinforcing the idea that the detected band reflects the
catalytic activity of AtSBT5.2(a) (Figure 35). Surprisingly, the detected band presents a
molecular size that is smaller than that detected for AtSBT5.2(a) by Western blot with anti-
HA antibodies (Figure 35). This result is consistent with an active AtSBT5.2(a) version that
would be both N- and C-terminally processed and thus undetectable by Western blot
analysis, as previously reported for some subtilase proteins (Yamagata et al., 1994, Von
Groll et al., 2002, Beilinson et al., 2002, Plattner et al., 2014). In contrast, no specific labelling
was detected for AtSBT5.2(b) or its catalytic mutant under the same conditions (Figure 35),
which does not allow to conclude on the catalytic activity of AtSBT5.2(b) .
In order to investigate the effect of N-glycosylation on the catalytic activity of AtSBT5.2(a),
AtSBT5.2(a) PGS removal mutants were tested for serine protease activity using the same
ABP assay. Protein extracts of N. benthamiana leaves expressing wild-type, catalytic mutant
or PGS mutant AtSBT5.2(a) versions were incubated with the FP probe as described above.
72
As shown in Figure 36, different effects were observed for different PGS mutant versions.
For example, AtSBT5.2(a)N678A appeared to display weaker protein accumulation and
stronger serine protease activity than the wild-type protein. In contrast, AtSBT5.2(a)N525A
appeared to display unchanged protein accumulation but weaker serine protease activity
than the wild-type protein suggesting that glycosylation of these residues may play a role in
modulating the catalytic activity of AtSBT5.2(a).
Figure 37. Neither AtSBT5.2(a) nor AtSBT5.2(b) affect AtMYB30 protein accumulation
in planta.
(A) TAP-Tagged AtMYB30 was transiently co-expressed with HA-tagged AtSBT5.2(a), or AtSBT5.2(b)
and their respective catalytic mutants side by side in the same N. benthamiana leaf.
(B) TAP-Tagged AtMYB30 was transiently co-expressed with the indicated HA-tagged AtSBT5.2
proteins in N. benthamiana leaves. Proteins were detected by Western blot analysis using anti-
HA or anti-TAP antibodies. Ponceau S staining confirms equal loading. Molecular mass markers in
kiloDaltons are indicated on the right. Identical results were obtained in five independent
experiments.
AtMYB30-TAP +
AtMYB30
Ponceau S
a-HA
. 130
. 95
. 72
a-TAP
(B)
(A)
AtMYB30-TAP +
AtSBT5.2(a)HA
AtMYB30-TAP +
AtSBT5.2(a)H210A-HA
AtMYB30-TAP +
AtSBT5.2(b)HA
AtMYB30-TAP +
AtSBT5.2(b)H171A-HA
73
2. Characterization of the interaction between AtMYB30 and AtSBT5.2
2.1. Neither AtSBT5.2(a) nor AtSBT5.2(b) affect AtMYB30 protein accumulation in planta.
Since the activity-based probe assay did not allow to conclude on the catalytic activity of
AtSBT5.2(b), the in planta accumulation of AtMYB30 when expressed with the different
AtSBT5.2 proteins was next analysed. To minimize differences in protein expression, which are
inherent to transient assays, AtMYB30 was co-expressed with AtSBT5.2(a) (or AtSBT5.2(b))
and their respective catalytic mutants, side by side in the same N. benthamiana leaf (Figure
37A). To avoid ex planta protein degradation, leaves were pre-treated with the protease inhibitor
phenylmethylsulfonyl fluoride (PMSF) 30 minutes before harvesting the tissue for protein
extraction. Western blot analysis consistently showed that AtMYB30 accumulation is not
significantly altered in the presence of AtSBT5.2(a) or AtSBT5.2(b) as compared to the
expression observed in the presence of the subtilase catalytic mutant versions (Figure 37B).
These results suggest that neither AtSBT5.2(a) nor AtSBT5.2(b) are able to proteolytically
cleave AtMYB30.
2.2. AtSBT5.2(b), but not AtSBT5.2(a), colocalizes with AtMYB30 in planta.
AtMYB30 was previously localized to the nucleus of Arabidopsis and N. benthamiana cells
(Froidure et al., 2010a). In order to investigate AtMYB30 potential colocalization with
AtSBT5.2(a) and/or AtSBT5.2(b), a Green Fluorescent Protein (GFP)-tagged AtMYB30 was
co-expressed with RFP-tagged AtSBT5.2(a) or AtSBT5.2(b) (Figure 38). Confocal
microscopy analysis of N. benthamiana leaves transiently co-expressing AtMYB30-GFP and
AtSBT5.2(a)-RFP showed that these proteins do not co-localize in the plant cell (Figure 38).
Indeed, AtSBT5.2(a)-RFP was located extracellularly whereas AtMYB30-GFP was located
inside the nucleus (Figure 38). Surprisingly, when co-expressed with AtSBT5.2(b)-RFP,
AtMYB30-GFP was excluded from the nucleus and localized to the same punctuated
Figure 38. AtSBT5.2(b), but not AtSBT5.2(a), colocalises with and retains AtMYB30
outside the nucleus.
Confocal images of epidermal cells of N. benthamiana leaves 36 hours after Agrobacterium-
mediated transient co-expression of GFP-tagged AtMYB30 with either AtSBT5.2(a) (top) or
AtSBT5.2(b) (down) RFP-tagged versions. Bars, 10µm. GFP, Green Fluorescent Protein; RFP, Red
Fluorescent Protein.
AtM
YB
30
-GF
P
+ A
tSB
T5
.2(a
)-R
FP
AtM
YB
30
-GF
P
+ A
tSB
T5
.2(b
)-R
FP
GFP Fluorescence RFP Fluorescence Merged
Table 3. FRET-FLIM analysis shows that AtSBT5.2(b) physically interacts with
AtMYB30-GFP AtSBT5.2(b)-RFP 2.274 0.019 54 10.86 5.85 x 10-21
AtMYB30-GFP AtSBT5.2(b)362-730-RFP 2.271 0.015 51 14.91 3.79 x 10-49
AtMYB30-GFP AtSBT5.1405-780-RFP 2.592 0.017 44 2.86 4.23 x 10-5
AtMYB123-GFP
AtMYB123-GFP AtMYB123-GFP
-
AtSBT5.2(b)362-730-RFP AtSBT5.1405-780-RFP
2.512
2.366 2.386
0.012
0.018 0.015
45
39 45
-
5.84 5.05
-
2.00 x 10-9 8.92 x 10-9
aMean lifetime in nanoseconds. bStandard error of the mean. cTotal number of measures. dPercentage of FRET efficiency (E = 1 - !DA/!D) calculated by comparing the lifetime of the donor in the
presence of the acceptor (!DA) with its lifetime in the absence of the acceptor (!D). eP value of the difference between the donor lifetimes in the presence and in the absence of the
acceptor (t-test).
Figure 40. AtSBT5.2(b) does not affect AtMYB123 nuclear localization.
Confocal images of epidermal cells of N. benthamiana leaves 36 hours after Agrobacterium-
mediated transient expression of GFP-tagged AtMYB123 co-expressed with RFP-tagged
AtSBT5.2(b). White arrows indicate cell nuclei. Bars, 10 µm. GFP, Green Fluorescent Protein; RFP,
Red Fluorescent Protein.
GFP Fluorescence RFP Fluorescence Merged
AtM
YB
12
3 -
GF
P
+ A
tSB
T5
.2(b
)-R
FP
Figure 39. AtSBT5.2(b)-mediated retention of AtMYB30 outside the nucleus is
independent of C-terminal tagging of the subtilase.
Confocal images of epidermal cells of N. benthamiana leaves 36 hours after Agrobacterium-
mediated transient expression of GFP-tagged AtMYB30 co-expressed with HA-tagged (left) or
untagged (right) versions of AtSBT5.2(b). Bars, 10 µm. GFP, Green Fluorescent Protein.
AtM
YB
30
-GF
P
+ A
tSB
T5
.2(b
)-H
A
AtM
YB
30
-GF
P
+ A
tSB
T5
.2(b
)
GFP fluorescence GFP fluorescence
74
structures where AtSBT5.2(b)-RFP was localized, suggesting a possible in planta interaction
between the two proteins outside the nucleus (Figure 38).
2.3. AtSBT5.2(b), but not (a), interacts with AtMYB30 in planta.
Subcellular co-localisation is a first prerequisite for the study of protein-protein interactions.
Since no co-localization was detected between AtMYB30 (nuclear) and AtSBT5.2(a)
(secreted), and because AtSBT5.2(b) co-localized with AtMYB30 in the small vesicle-like
structures described in the previous section, we sought out to investigate the interaction
between AtSBT5.2(b) and AtMYB30 in living plant cells.
The physical interaction between AtSBT5.2(b) and AtMYB30 was tested using a quantitative
non-invasive FLIM approach to monitor the Förster Resonance Energy Transfer (FRET)
between the GFP (donor) and RFP (acceptor) molecules fused to AtMYB30 and
AtSBT5.2(b), respectively. If these two proteins interact, the transfer of energy from the
donor to the acceptor decreases the fluorescence lifetime (average time that a molecule
remains in its excited state prior to returning to its basal state) of the donor fluorophore. The
relative difference of lifetime is a measure of FRET efficiency (E) that is considered to be
significant when higher than 7%. The average GFP lifetime in nuclei expressing AtMYB30-
GFP was 2.669 ± 0.009 ns (mean ± sem), whereas the GFP lifetime of AtMYB30-GFP in the
vesicle-like structures when co-expressed with AtSBT5.2(b)-RFP was 2.274 ± 0.019 ns
(Table 3; Figure 38). Although this reduction in GFP lifetime may result from the physical
interaction between AtMYB30 and AtSBT5.2(b), it was important to rule out that this
difference did not reflect distinct molecular environments of different subcellular
compartments in which AtMYB30 is localized (nuclear when expressed alone or in
intracellular vesicles when co-expressed with AtSBT5.2(b)). The subcellular localization of of
GFP-tagged AtMYB30 when co-expressed with non-fluorescent HA-tagged or untagged
versions of AtSBT5.2(b) was therefore investigated. As shown in Figure 39, both
Figure 41. AtMYB30 and AtMYB123 colocalize in nuclei with both AtSBT5.2362-730 and
AtSBT5.1405-780. Confocal images of epidermal cells of N. benthamiana leaves 36 hours after Agrobacterium-
mediated transient expression of GFP-tagged AtMYB30 co-expressed with the indicated truncated
versions of AtSBT proteins. White arrows indicate cell nuclei. Bars, 10 µm. GFP, Green Fluorescent
Protein; RFP, Red Fluorescent Protein.
GFP Fluorescence RFP Fluorescence Merged
AtM
YB
30
-GF
P
+ A
tSB
T5
.2(b
) 36
2-7
51R
FP
AtM
YB
30
-GF
P
+ A
tSB
T5
.14
05
-78
0R
FP
AtM
YB
12
3-G
FP
+ A
tSB
T5
.2(b
) 36
2-7
30R
FP
AtM
YB
12
3-G
FP
+ A
tSB
T5
.14
05
-78
0R
FP
75
AtSBT5.2(b)-HA and untagged AtSBT5.2(b), which are not able to act as acceptors for the
GFP fluorescence, still lead to AtMYB30 localization to mobile intracellular vesicles. As
shown in Table 3, a slight decrease in GFP-lifetime was indeed detected for AtMYB30-GFP
when co-expressed with AtSBT5.2(b)-HA (in intracellular punctuated structures) as
compared to AtMYB30-GFP expressed alone (located inside nuclei), suggesting differences
in the molecular environment between the two compartments. Importantly, a significant
reduction of GFP lifetime was observed when AtMYB30-GFP was co-expressed with RFP-
tagged AtSBT5.2(b) (2.274 ± 0.019 ns) as compared to co-expression with AtSBT5.2(b)-HA
(2.552 ± 0.013 ns), confirming the physical interaction between the two proteins in
intracellular vesicles.
Together, our data suggests that AtSBT5.2(b) may high jack AtMYB30 in the vesicle-like
structures, thus impeding its nuclear entry.
2.4. The AtSBT5.2(b)-AtMYB30 interaction is specific and mediated through AtSBT5.2(b) C-
terminal domain
The large number of subtilase proteins and MYB TFs in Arabidopsis suggests functional
redundancy, although it may also be indicative of functional diversification. Therefore, we
next addressed the question of specificity of the interaction between AtSBT5.2(b) and
AtMYB30.
In order to test whether AtSBT5.2(b) was able to induce mislocalization of other TFs in the
vesicle-like structures, AtSBT5.2(b)-RFP was co-expressed with the unrelated nuclear MYB
TF AtMYB123. Despite the formation of the vesicle-like structures containing AtSBT5.2(b)-
RFP, GFP-tagged AtMYB123 was consistently detected inside the nucleus (Figure 40),
suggesting that AtSBT5.2(b)-mediated mislocalization of AtMYB30 and, thus the interaction
Figure 42. Sequence alignment of AtSBT5.2(b)362-730 and AtSBT5.1405-780 proteins. Identical amino acids are highlighted in blue. The 103 C-terminal amino acids encoded by the partial
AtSBT5.2 cDNA clone identified in the yeast two-hybrid screen as interacting with AtMYB30DAD are
underlined.
AtSBT5.2(b)362-730
AtSBT5.1405-780
AtSBT5.2(b)362-730
AtSBT5.1405-780
AtSBT5.2(b)362-730
AtSBT5.1405-780
AtSBT5.2(b)362-730
AtSBT5.1405-780
AtSBT5.2(b)362-730
AtSBT5.1405-780
76
The identification of a partial AtSBT5.2 cDNA clone (the last 103 amino acids of AtSBT5.2) in
the previously perfomed Y2H screen (Froidure et al., 2010a) suggests that the AtMYB30-
AtSBT5.2(b) interaction is mediated by the C-terminus of AtSBT5.2(b). In order to test this
idea, a truncated AtSBT5.2(b) version containing the last 368 amino acids of the protein
(AtSBT5.2(b)362-730) fused to the RFP was generated and transiently expressed in N.
benthamiana leaves. Confocal microscopy analysis showed that AtSBT5.2(b)362-730-RFP
presents a nucleocytoplasmic localization and colocalises with AtMYB30 in the plant cell
nucleus (Figure 41). A significant reduction of the average GFP lifetime was measured in
nuclei coexpressing AtMYB30-GFP and AtSBT5.2(b)362-730-RFP (2.271 ± 0.112 ns), as
A Conserved Core of Programmed Cell Death IndicatorGenes Discriminates Developmentally andEnvironmentally Induced Programmed CellDeath in Plants1[OPEN]
Yadira Olvera-Carrillo2, Michiel Van Bel, Tom Van Hautegem, Matyáš Fendrych3, Marlies Huysmans,Maria Simaskova, Matthias van Durme, Pierre Buscaill, Susana Rivas, Nuria S. Coll, Frederik Coppens,Steven Maere, and Moritz K. Nowack*
Department of Plant Systems Biology, Vlaams Instituut voor Biotechnologie, and Department of PlantBiotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium (Y.O.-C., M.V.B., T.V.H., M.F., M.H.,M.S., M.v.D., F.C., S.M., M.K.N.); Institut National de la Recherche Agronomique, Laboratoire des InteractionsPlantes-Microorganismes, Unité Mixte de Recherche 441, and Centre National de la Recherche Scientifique,Laboratoire des Interactions Plantes-Microorganismes, Unité Mixte de Recherche 2594, F–31326 Castanet-Tolosan, France (P.B., S.R.); and Center for Research in Agricultural Genomics, Bellaterra-Cerdanyola del Valles,08193 Barcelona, Spain (N.S.C.)
A plethora of diverse programmed cell death (PCD) processes has been described in living organisms. In animals and plants,different forms of PCD play crucial roles in development, immunity, and responses to the environment. While the molecularcontrol of some animal PCD forms such as apoptosis is known in great detail, we still know comparatively little about theregulation of the diverse types of plant PCD. In part, this deficiency in molecular understanding is caused by the lack ofreliable reporters to detect PCD processes. Here, we addressed this issue by using a combination of bioinformatics approachesto identify commonly regulated genes during diverse plant PCD processes in Arabidopsis (Arabidopsis thaliana). Our results indicatethat the transcriptional signatures of developmentally controlled cell death are largely distinct from the ones associated withenvironmentally induced cell death. Moreover, different cases of developmental PCD share a set of cell death-associated genes.Most of these genes are evolutionary conserved within the green plant lineage, arguing for an evolutionary conserved coremachinery of developmental PCD. Based on this information, we established an array of specific promoter-reporter lines fordevelopmental PCD in Arabidopsis. These PCD indicators represent a powerful resource that can be used in addition toestablished morphological and biochemical methods to detect and analyze PCD processes in vivo and in planta.
Programmed cell death (PCD) is a fundamentalprocess of life. Already present in clonal colonies ofprokaryotes (Bayles, 2014), PCD has evolved to becomean essential mechanism in multicellular eukaryotes(Wang and Bayles, 2013). Many different forms of PCDhave been recognized, but a unifying definition char-acterizes PCD as genetically encoded, actively con-trolled cellular suicide.
In animals and plants, PCD is involved in many as-pects of development, sculpting structures or deleting un-wanted tissues (Fuchs and Steller, 2011; Van Hautegemet al., 2015). Over the last two decades, intensive in-vestigations have revealed mechanisms controllingdifferent forms of animal PCD; the most prominentamong them is apoptotic PCD (Green, 2011). In com-parison, there is still little knowledge of the molecularnetworks controlling PCD in plants, despite its abun-dance and its importance for plant life: plant PCD oc-curs as an integral part of development (dPCD) as wellas of the plant’s reactions to biotic and abiotic environ-mental challenges (ePCD; Lam, 2004). Concerning dPCD,
1 This work was supported by the Consejo Nacional de Ciencia yTecnología (postdoctoral fellowship registration nos. 186253 and203288 to Y.O.-C.) and the French Laboratory of Excellence (projectTULIP ANR–10–LABX–41 and ANR–11–IDEX–0002–02).
3 Present address: Institute of Science and Technology Austria, AmCampus 1, A–3400 Klosterneuburg, Austria.
* Address correspondence to [email protected] author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy de-scribed in the Instructions for Authors (www.plantphysiol.org) is:Moritz K. Nowack ([email protected]).
Y.O.-C. and M.K.N. conceived and coordinated the study; M.V.B.,F.C., and S.M. designed, and M.V.B. and S.M. performed the bioinfor-matics analyses; P.B., S.R., andN.S.C. designed, performed, and analyzedthe biotic stress experiments; Y.O.-C. performed and analyzed the wetlabexperiments and designed the figures together with M.F. and M.V.D.;T.V.H., M.H., M.S., and M.V.D. participated in the microscopy work;M.H. performed the terminal deoxynucleotidyl transferase dUTPnick-end labeling assays; Y.O.-C., S.M., and M.K.N. wrote the article.
[OPEN] Articles can be viewed without a subscription.www.plantphysiol.org/cgi/doi/10.1104/pp.15.00769
2684 Plant Physiology!, December 2015, Vol. 169, pp. 2684–2699, www.plantphysiol.org " 2015 American Society of Plant Biologists. All Rights Reserved.www.plant.org on December 11, 2015 - Published by www.plantphysiol.orgDownloaded from
a distinction can be made between (1) differentiation-induced PCD that occurs as final differentiation step inspecific cell types, for instance, in xylem tracheary ele-ments, the root cap, or the anther tapetum layer (Plackettet al., 2011; Bollhöner et al., 2012; Fendrych et al., 2014),and (2) age-induced PCD as the last step of organ se-nescence that occurs in all tissues of an organ or even theentire plant at the end of its life cycle (Thomas, 2013).Regarding ePCD, one of themost studied PCDprocessesoccurs during the hypersensitive response (HR), a local-ized plant response upon pathogen recognition (Collet al., 2011; Wu et al., 2014). Also abiotic stresses such asheat, UV radiation, or salt stress can lead to cell deathdisplaying certain hallmarks of PCD (Chen et al., 2009;Qiet al., 2011; Nawkar et al., 2013; Petrov et al., 2015).It is still unclear whether different PCD types in plants
share common regulatory mechanisms or if they arecontrolled by distinct pathways. Due to the scarcity ofmolecular information, most comparative analyses havebeen based on morphological and biochemical charac-teristics. Vacuolar cell death, defined by accumulation ofautophagosomes, vacuolar collapse, and corpse degra-dation, has been opposed to necrotic cell death, withswelling of mitochondria, protoplast shrinkage and un-processed cell corpses (vanDoorn et al., 2011). However,some types of PCD, including HR cell death, pollen self-incompatibility, or endosperm cell death, do not fall intoeither of these proposed classes (van Doorn et al., 2011).Here, we exploited publicly available genome-wide
transcriptome data that were associated with differentforms of cell death in the model plant Arabidopsis(Arabidopsis thaliana), with the aim to comparativelycharacterize plant PCD types. We identified distinct setsof differentially regulated genes in several develop-mental and environmental situations known to provokeplant cell death, suggesting that dPCD and ePCD pro-cesses are characterized by separate regulatory path-ways. Focusing on dPCD,we identified a conserved coreof transcriptionally controlled dPCD-associated genes.Based on this information, we created and analyzed anarray of promoter-reporter lines that are expressed incells preparing for different types of dPCD. The pre-sented data will be a powerful tool to complementmorphological analysis when attempting PCD discov-ery, recognition, and analysis of dPCD types in plants.
RESULTS
Meta-Analysis of Available ATH1 Data Sets RevealsDistinct Gene Expression Patterns Characterizing dPCDand ePCD
To get a viewon similarities anddifferences in the geneexpression profiles of different PCD types,we carried outa meta-analysis of Arabidopsis Affymetrix GeneChipGenome Array (ATH1) data sets. Based on their accom-panying experimental descriptions, we selected a total of59 ATH1 data sets associated with a range of generallyaccepted or hypothetical PCD contexts. For simplicity,we will refer to all of these contexts as PCD, though for
some of them, the actively controlled nature of the celldeath has not been unambiguously shown. From thiscompendium, we extracted 82 conditions, contrastingdifferent cell death situations with their correspondingnon-PCD controls (Table I; Supplemental Tables S1 andS2). We assigned these contrasts to nine categoriesbased on their experimental context. The dPCD categorydifferentiation-induced cell death contains experimentsdescribing specific cell types undergoing cell death as partof their differentiation program, while the senescence-induced cell death category comprises data sets pro-duced fromentire organs during late stages of senescence.In the ePCD categories, data sets produced from patho-gen assays (biotic stress), from plants experiencing oxi-dative stress, and from plants exposed to UV irradiation,genotoxic compounds, high or low temperatures, andosmotic and salt stresses were included. Finally, data setsfrom hormone treatments leading to cell death completethe list of putative PCD categories (Fig. 1).
To define the relatedness of the ATH1 data sets, in-dependent of predefined PCD categories, we performeda hierarchical clustering analysis (HCA) based on theexpression profiles of all genes that are differentiallyexpressed in at least one condition. Although the overallsimilarity of the entire compendium is low, it was foundto contain several functionally coherent clusters (Fig. 1).At a Pearson’s correlation distance threshold of 0.4, threeclusters of more than five conditions could be defined.The biotic stress clustermainly contains pathogen-relateddata sets but also contains some senescence, UV stress,and oxidative stress conditions. The osmotic stress clustercontains salt stress and osmotic stress conditions, and athird cluster indicates the tight relationship of most ge-notoxic stress conditions. At a more relaxed correlationdistance threshold, a fourth sizeable cluster emerges. Thiscluster, although containing more diverse expressionpatterns than the other three, is also functionally coher-ent, encompassing all differentiation-induced dPCDconditions alongwith two senescence-related conditions(Fig. 1, developmental cluster).
We compared the gene expression profiles of theconditions that fell in these four clusters and identifiedcommonly regulated genes within the clusters. In thedevelopmental cluster, we found SERINE CARBOXY-PEPTIDASE-LIKE48 (SCPL48), the aspartic proteasePASPA3, BIFUNCTIONAL NUCLEASE1 (BFN1), RIBO-NUCLEASE3 (RNS3), CALCIUM-DEPENDENT NU-CLEASE1 (CAN1), and a DOMAIN OF UNKNOWNFUNCTION679 MEMBRANE PROTEIN2 (DMP2) ofunknown function up-regulated in at least 10 out of 12conditions (Supplemental Table S3, developmental clus-ter). Additionally, 19 genes were found to be commonlyup-regulated in at least eight out of 12 conditions, in-cluding genes of families previously implicated in dif-ferent PCD processes, e.g., VACUOLAR PROCESSINGENZYMES (Hara-Nishimura and Hatsugai, 2011). Thebiotic cluster exhibits up-regulation of genes involved insalicylic acid (SA) and Ca2+ signaling: the SA-inducedgenes ENHANCED DISEASE SUSCEPTIBILITY5,PHYTOALEXIN DEFICIENT3, andWRKY DNA-BINDING
PROTEIN75; the calcium-binding protein-encoding geneIQ-MOTIF PROTEIN1; and AUTOINHIBITED CA2+
ATPASE12 (Supplemental Table S3, biotic cluster). Theseresults reflect the importance of calcium andSA signalingin the HR (Ma and Berkowitz, 2007;Mur et al., 2008). Theintegration of biotic stress conditions as well as senes-cence conditions in the biotic cluster suggests the acti-vation of conserved processes during biotic stress andsenescence conditions. In the osmotic cluster, 12 geneswere up-regulated in all 14 conditions of mannitol, salt,and cold stress treatments (Supplemental Table S3, os-motic cluster), including SENESCENCE-ASSOCIATEDGENE113 and several LATE EMBRYOGENESIS ABUN-DANT genes, which are known to be involved in cellularprotection and stress tolerance (Olvera-Carrillo et al.,2010; Candat et al., 2014). The genotoxic cluster com-prised DNA repair genes such as BREAST CANCERSUSCEPTIBILITY1, RAD51 (At5g20850), and two of itsparalogs, RAD17 and RAD21 (Trapp et al., 2011). Fur-thermore, nucleotide metabolism genes such as TSOMEANING UGLY IN CHINESE2 (TSO2, AT3G27060)
and THYMIDINE KINASE1A (Roa et al., 2009) and sev-eral plant-specific SIAMESE (SIM)/SIAMESE-RELATED(SMR) CYCLIN-DEPENDENT KINASE (CDK) inhibi-tors (Yi et al., 2014) were commonly up-regulated in thiscluster (Supplemental Table S3, genotoxic cluster).
In contrast to the observed correlation within each ofthe four clusters, there was little similarity between thegene expression profiles across the clusters. These re-sults indicate that distinct gene expression patternscharacterize different forms of PCD, in particulardifferentiation-induced dPCD and ePCD types. How-ever, which of the differentially expressed genes areeffectively involved in PCD regulation and which onesare elicited as part of processes other than PCD remainsto be investigated case by case.
Most dPCD-Regulated Genes Are Not Up-Regulated inePCD Situations
To test the hypothesis of distinct gene regulationoccurring in differentiation-induced dPCD and ePCD
Figure 1. PCD-associatedATH1 transcriptomedata sets group indistinct clusters.HCA showing theclustering of 82putativedPCDandePCDconditions based on the log-fold expression values of differentially regulated genes and indicating their affiliation to different putative PCDcategories (arrow). Four clusters are highlighted indicating the relatedness of data sets falling in the developmental, the biotic stress, the osmoticstress, and the genotoxic stress clusters. The color coding from blue to yellow indicates an increase in the Pearson’s correlation distance.
conditions, we applied two-dimensional clustering tothe expression profiles of a curated gene set, which con-tains the genes that are most commonly up-regulated inthe four clusters described above, as identified usingcustom R scripts (see “Materials and Methods” andSupplemental Table S3). The resulting gene clades mir-ror the original four clusters, and it again appears thereis little common regulation of these genes across clusters(Fig. 2).The genotoxic cluster appears most distinct; only few
genotoxic marker genes were up-regulated in the otherconditions. One example is the CDK-inhibitor SMR5(At1g07500) that is up-regulated in several salt andosmotic stress conditions (Fig. 2). Gene expressionprofiles in the osmotic stress and biotic stress clustershave larger overlaps; many biotic marker genes are up-regulated duringmannitol and salt treatments, and viceversa some osmotic marker genes are up-regulated as aconsequence of inoculation with the necrotrophicpathogen Botrytis cinerea (Fig. 2). The up-regulation ofdevelopmental marker genes is largely confined to thedifferentiation-induced dPCD data sets. Some genes,however, are also up-regulated in osmotic and saltstress conditions, suggesting a certain degree of com-mon gene regulation (see the lower tier of develop-mental marker genes in Fig. 2). Interestingly, conditionsof organ senescence lead to up-regulation of severalbiotic, osmotic, and developmental marker genes (Fig.2, arrow), suggesting that plant senescence activates acombination of pathways. Most developmental markergenes, however, are almost exclusively up-regulated indifferentiation-induced dPCD situations, suggestingthat the transcriptional regulation differs substantiallybetween these and ePCD contexts.
Supervised Classification of PCD Samples Based on TheirGene Expression Profiles Is Possible for Some PCD TypesBut Not for Others
Prompted by the results of the unsupervised clus-tering approaches in distinguishing PCD types (Figs.1 and 2), we attempted to classify the different putativePCD categories (Fig. 1) using supervised classificationalgorithms, based on their ATH1 expression profilesand the putative PCD class labels assigned to themfrom the experimental descriptions (see “Materials andMethods”). The aim of building such classifiers is toassess the feasibility of predicting the PCD type of anunlabeled experimental sample based on its gene ex-pression profile.We first built Support Vector Machine (SVM; Cortes
and Vapnik, 1995) and Random Forest (RF; Breiman,2001) classifiers distinguishing ePCD- from dPCD-related conditions, based on the expression profiles ofall genes. A moderate classification performance wasobtained on the full data set of ePCD and dPCD condi-tions (Supplemental Table S4). The performance in-creased markedly when excluding minority subclasses,i.e., senescence (for dPCD) and/or temperature stress,
UV stress, oxidative stress, and hormone treatments (forePCD). Using the curated set of putative PCD indicatorsfor the four major PCD clusters described above (Fig. 2;Supplemental Table S3 instead of all genes as classifica-tion features did not generally lead to improved classi-fication performance (Supplemental Table S4). Theseresults indicate that a clear molecular distinction ofePCD versus dPCD is hampered by expression similar-ities between certain subtypes of ePCD and dPCD. Inparticular, the expression profile similarities betweensenescence-induced dPCD and various ePCD conditions(see Fig. 2) appear to have a negative impact on thedPCD/ePCD classification performance (SupplementalTable S4). To investigate which PCD subtypes suffer themost from expression similarities with other subtypes,we attempted to classify particular PCD subtypesagainst all other types (Supplemental Table S4).Whereasthe maximum classification performance is high fordifferentiation-induced dPCD, genotoxic cell death, andosmotic cell death, the performance values for other PCDsubtypes are moderate to low, reflecting a lack of ade-quately distinctive expression signatures to separatethese poorly performing PCD subtypes from some of theother PCD types grouped together as the alternative la-bel set. Taken together, with the ATH1 data sets that arepublically available at this point, unconditionally dis-tinctive sets of marker genes are hard to find for manyPCD subtypes, even when using supervised classifica-tion strategies.
Identification of Unique dPCD Indicator Genes
The information that genes are predominantly up-regulated in differentiation-induced dPCD types openedthe possibility of testing some of these genes for theiraptitude as dPCD reporter genes. We took three com-plementary approaches to identify individual genes thatcould potentially be used as dPCD markers.
First, we compiled a list of genes that are significantlyup-regulated at least 2-fold in at least 60% of the dPCDdata sets in the ATH1 compendium described above.SCPL48 and PASPA3 show the highest frequency of up-regulation in all dPCD data sets (89% and 84%, re-spectively). TELOMERIC DNA-BINDING PROTEIN1(At5g13820) is up-regulated in 79%of all dPCD contrasts,and BFN1 is up-regulated in 74% of the contrasts. Ad-ditional commonly up-regulated genes inmore than 60%of all 19 dPCD contrasts include RNS3, CAN1, THIO-REDOXIN H-TYPE5, and three genes of unknownfunction (Supplemental Table S3, dPCD contrasts).
Second, we used the Genevestigator Condition Searchand Similarity Search tools (Hruz et al., 2008) to identifygenes that are commonly coregulated with BFN1,PASPA3, METACASPASE9 (MC9), and CYSTEINE EN-DOPEPTIDASE (CEP1), four genes that have been as-sociated with or functionally implicated in dPCD inseveral Arabidopsis cell types (Farage-Barhom et al.,2008; Helm et al., 2008; Ohashi-Ito et al., 2010; Bollhöneret al., 2013; Fendrych et al., 2014; Zhang et al., 2014).
Figure 2. Commonly up-regulated geneswithin PCD clusters are largely distinct between clusters. Two-dimensional clustering ofthe gene-conditionmatrix plotting the expression profiles of themost commonly regulated genes of the four clusters highlighted inFigure 1 over all conditions. The separate blocks of dark blue fields indicate that the regulation of commonly expressed markergenes is largely distinct for each cluster. The arrow indicates a cluster of senescence-related data sets that show up-regulation ofbiotic, osmotic, and developmental marker genes.
2688 Plant Physiol. Vol. 169, 2015www.plant.org on December 11, 2015 - Published by www.plantphysiol.orgDownloaded from
Seven genes were found to be commonly coregulatedwith these four target genes (Table II; Supplemental TableS5). Reiterating the analysis with these seven genes, weobtained a list of 154 genes that are coregulated with atleast two out of the seven genes (Supplemental Table S5).Of these genes, four are coregulated with all target genes:BFN1 andMC9, as well as RNS3 and DMP4 (At4g18425,a paralog of DMP2). An unknown gene that we dubbedEXITUS1 (EXI1; At2g14095) and the transcription factorANAC083 (for NO APICAL MERISTEM; ARABIDOPSISTRANSCRIPTION ACTIVATION FACTOR; CUP-SHAPED COTYLEDON [NAC]DOMAIN CONTAININGPROTEIN83) are coregulated with at least six of theseven target genes.Third, we constructed a list of genes potentially in-
volved in dPCD by comparing the gene expression pro-files of two root tissues that are known to execute dPCDas afinal differentiation step, the root cap (Fendrych et al.,2014), and the xylem tracheary elements (Bollhöner et al.,2012) with expression profiles of other tissues. Usingthe Visual Lateral Root Transcriptome Compendium(VLRTC; Parizot et al., 2010) based on a gene expressionatlas of the Arabidopsis root (Brady et al., 2007), wefound 95 genes commonly up-regulatedmore than 2-foldin xylem and lateral root cap (LRC) compared with roottissues not undergoing PCD (Supplemental Table S6).Eight of these genes are among the 154 genes identifiedbyGenevestigator as coexpressedwith at least two out ofseven genes in the target gene set, significantlymore thanexpected by chance (P = 1.5267e-06, hypergeometric test).Next to BFN1,MC9, PASPA3, SCPL48, and RNS3, a fattyacid desaturase family gene (At1g06090), the tran-scription factor ANAC046 (At3g04060), and SCPL20 arecommonly up-regulated, suggesting that these genes
might be involved in dPCD processes in the xylem andthe LRC.
Although the data sets used in the ATH1 meta-analysis and VLRTC approaches overlap to some ex-tentwith each other (the root cap data sets inVLRTCandthe meta-analysis are the same) and with the Geneves-tigator data, the different screening methodologies usedled to the identification of candidate reporter gene setsthat are only partially overlapping. By virtue of beingcommonly up-regulated in different differentiation-induced dPCD contexts, these genes can be consideredpotential dPCD reporters. To test the aptitude of thesegenes in this respect, we picked a set of 10 genes forin-depth characterization of their expression patterns:CEP1, PASPA3, BFN1, MC9, ANAC046, CAN1, RNS3,SCPL48, EXI1, and DMP4.
dPCD Reporters Are a Powerful Resource to DetectPutative dPCD Processes in Planta
The putative 59-regulatory regions (promoters) of theeight candidate dPCD reporter genes were cloned andfused to a Gal4 DNA binding domain fused to thetranscriptional activator domain of the herpes simplexvirus VP16 protein (GAL4-VP16) transcriptional activa-tor, combined with a GAL4-activated upstream activa-tion sequence (UAS) driving a nuclear-localized histone2A-GFP (..H2A-GFP) reporter gene. These lines can beused in a versatile manner: as marker lines to detect andanalyze PCD processes in planta, as driver lines to con-trol the transcription of transgenes in a PCD-specificspatial and temporal pattern, and as tools to sort GFP-tagged protoplasts or nuclei for tissue-specific -omicsanalyses.
Table I. Overview of the number of conditions profiled per PCD subcategory in the ATH1 compendium
PCD Category PCD Subcategory Tissue, Organ, and Stress Type No. of Conditions
In a first round, over a dozen independent lines perpromoter-reporter construct were investigated in T2,and lines with a single transfer DNA insertion locus anda representative GFP expression pattern were selectedfor in-depth analysis in T3. As the pEXI1 ..H2A-GFP,the pANAC046..H2A-GFP and the pCAN1..H2A-GFPconstructs conferred weak or inconsistent GFP signals,these lines were not included for further analysis. FromCEP1, PASPA3, MC9, and BFN1, which have been pre-viously reported as PCD-associated (Farage-Barhomet al., 2008; Helm et al., 2008; Bollhöner et al., 2013;Fendrych et al., 2014), we chose to display the ex-pression patterns conferred by pCEP1 and pPASPA3 asa reference for the expression pattern of the remaininggenes.
We focused our expression analysis on Arabidopsistissues or cell types known to undergo differentiation-induced dPCD: the tapetum layer in the developinganther, the protoxylem cells in the growing root, and thecells of the LRC. Cells are also dying in the central en-dosperm and in senescing petals, butmuch less is knownabout the nature of the cell death in these tissues (forreview, see Van Hautegem et al., 2015). We exploited atonoplast integrity marker (ToIM; Fendrych et al., 2014)to investigate vacuolar collapse, a hallmark of vacuolarPCD (van Doorn et al., 2011). In all tissues or cell types,the ToIM expression controlled by the pPASPA3 pro-moter shows that vacuolar collapse precedes cell deathinPASPA3-expressing cells (Fig. 3). In petals and the rootcap, we additionally performed whole-mount terminaldeoxynucleotidyl transferase dUTP nick-end labeling(TUNEL) assays, indicating that DNA fragmentationoccurs in these tissues in the stages investigated for theexpression pattern of the promoter-reporter constructs(Fig. 3).
The promoters of RNS3, PASPA3, and DMP4 con-ferred largely similar expression patterns in the degen-erating endosperm from torpedo stage onwards, in theanther tapetum layer before tapetum cell death, in dif-ferentiating LRC cells and tracheary elements, and insenescing petals (Fig. 4; Supplemental Figs. S1–S3). Inaccordance with the ATH1-derived expression data, thepRNS3 promoter conferred the strongest GFP expres-sion, while pDMP4..H2A-GFP produced weaker GFPsignals. Note that very high expression levels led to afailure to contain the H2A-GFP protein in the nucleus.Similar to pPASPA3, pRNS3 is activated many hoursbefore PCD in the LRC, leading to a broader expression
pattern compared with the one conferred by pDMP4,which only activated H2A-GFP expression shortly be-fore PCD, leading to a narrower expression pattern in theLRC (Fig. 4). In developing petals of pRNS3, pPASPA3,and pDMP4 reporter lines, expressionwas first restrictedto the tracheary elements, while expression spreadthroughout the entire organ during petal senescence(Supplemental Fig. S1). During anther development,pPASPA3 activation was confined to the differentiatingtapetum layer, while both pRNS3 and pDMP4 were ac-tive in the outer layers of the anthers in later stages offlower development (Supplemental Fig. S2). In devel-oping seeds, both pDMP4 and pPASPA3 exclusivelyconferred expression in differentiating endosperm fromthe torpedo stage onwards, while pRNS3 ..H2A-GFPsignals were also detected in the differentiating seed coatof later seed stages (Supplemental Fig. S3).
Compared with pRNS3, pPASPA3, and pDMP4, thepSCPL48 promoter conferred a broader spatial andtemporal expression pattern; it was, for instance, al-ready expressed in petals at anthesis (Supplemental Fig.S1) and in the entire LRC, and not only confined totracheary elements, but also expressed in their neigh-boring cells (Fig. 4). In developing anthers, pSCPL48activity was not confined to the tapetum but spread tothe outer anther layers (Supplemental Fig. S3). Duringseed development, pSCPL48 was not activated in theendosperm but strongly up-regulated in the differentlayers of the differentiating seed coat (SupplementalFig. S3).
Finally, the pCEP1 ..H2A-GFP expression patternwas confined to the dying LRC cells close to the root tip(Fig. 4), in accordance with earlier reports (Helm et al.,2008). Additionally, pCEP1 ..H2A-GFP conveys astrong expression in epidermal cells in the root hairzone, though these are not known to undergo cell death(data not shown). Interestingly, the close CEP1 homo-log CEP2 is highly expressed in LRC cells in the roottransition zone (Hierl et al., 2014) and might take overCEP1 functions here. In the developing seed, pCEP1 isactive in the embryonic suspensor during early embryodevelopment (data not shown) and is present in laterstages both in the seed coat and the differentiating en-dosperm (Supplemental Fig. S3).
In summary, most promoter-reporter lines are spe-cifically expressed in differentiating cells known toundergo dPCD or are associated with cellular degra-dation events that are thus far not well defined. Not all
Table II. Commonly coexpressed genes of BFN1, MC9, PASPA3, and CEP1
Coexpression scores as calculated by Genevestigator. AGI, Arabidopsis Genome Initiative gene code.
Figure 3. Cell death processes occur in different developmental contexts. AToIM combines expression of a freeGFPaccumulating inthe cytoplasm and the nucleus (green) and of a vacuolar-localized tagRFP (a monomeric derivative of a red fluorescent protein fromEntacmaea quadricolor ; red). Vacuolar rupture is indicated by the loss of compartmentalization and the merging of the two fluo-rescent signals. Note that in some dPCD cases, cytoplasmic acidification dampens the GFP signal, making the tagRFP signal moreprominent. The ToIM is expressed under the control of the pPASPA3 promoter. A, Time lapse imaging of dPCD in a protoxylemelement. The arrowheads indicate the cytoplasm around the cell’s nucleus, which is invaded by tagRFP upon vacuolar rupture(asterisk). B, Time lapse imaging of dPCD in a root cap cell. The arrowheads indicate the cell with intact vacuole, while the asteriskmarks the cell once vacuolar rupture has occurred. C, Time lapse imaging of dPCD in petal cells at the base of a petal. The ar-rowheads indicate the cell with intact vacuole, while the asterisk marks the cell once vacuolar rupture has occurred. D to F,Vibratome sections through developing anthers around the time point of tapetum dPCD. D shows a locule lined by pPASPA3::ToIM-expressing, viable tapetum cells. E shows a locule in which dPCD is ongoing; the arrowheads point at partly degenerated cells.F shows a locule after tapetum dPCD in which degraded remains of tapetum cells line the inside of the locule. G and H, Vibratomesections through a seed in the walking stick state of embryo (em) development. H is a detail of G. Arrowheads point at ToIM-expressing but intact endospermcells, while the asterisks indicate cells in the process of degeneration. I to K, TUNEL of whole-mountpetals and root tips. 49,6-diamidino-2-phenylindole (DAPI) staining is shown in red, and TUNEL signal is shown in green. I, Ar-rowheads indicate dying or dead TUNEL-positive root cap cells. J, Arrowheads indicate two fields of TUNEL-positive petal cells. K,TUNEL-positive control treated with DNase to induce tissue-wide DNA fragmentation, showing the overlap of TUNEL and DAPIsignals. In A to C, time is indicated in minutes. Bars = 50 mm (A–C, G, and I–K) and 20 mm (D–F and H).
T promoter-reporter lines are present in every dPCDprocess, and not all gene expression patterns are re-stricted to cells preparing for dPCD, but the combina-tion of these marker lines provides a powerful tool toidentify and analyze putative dPCD processes in a de-velopmental context in vivo and in planta.
dPCD Indicators Are Not Up-Regulated by Biotic andAbiotic Stresses Causing Cell Death
Our meta-analysis indicated that largely nonoverlap-ping sets of genes are up-regulated in differentiation-induced dPCD and various abiotic stress-induced ePCDtypes (Fig. 2), indicating that distinct transcriptionalprograms are activated in these plant cell death types. Tofurther test this hypothesis experimentally, we analyzeddPCD marker expression in roots of Arabidopsis seed-lings upon a variety of abiotic stresses. Propidium iodide(PI), which only enters cells with compromised plasmamembrane integrity (Truernit and Haseloff, 2008), wasused to highlight dead and dying cells. We investi-gated three marker constructs, pSCPL48, pRNS3, andpPASPA3, which showed a specific expression pattern inthe LRC of the control root tips. Upon treatments withhydroxyurea, bleomycin, UV-B irradiation, hydrogenperoxide, and NaCl, increasing numbers of PI-positivecells indicated the occurrence of cell death during thedifferent stress treatments (Fig. 5, arrowheads). Whilegenotoxic andUV stress led to localized cell death of rootmeristem cells, oxidative and salt stress produced morewidespread cell death. In all cases, cell death was neitherpreceded by ectopic dPCD marker expression at earlytime points nor accompanied by dPCD marker expres-sion at late time points. However, whether the observedcell death is a result of PCD programs activated by thestress treatments or is caused by direct cellular damageis difficult to ascertain. We performed whole-mountTUNEL and found that hydrogen peroxide treatmentleads to TUNEL-positive root cells (Supplemental Fig.S4). All other stress treatments did not lead to clearlyTUNEL-positive cells, apart from the dying root cap cellsthat are TUNEL positive due to stress-independentdPCD (Supplemental Fig. S4). These results confirmthat the stresses used to produce the ATH1 data setsmeta-analyzed in our study were sufficient to cause celldeath, but they leave open whether this cell death is anactive PCD or a passive, unregulated form of cell death.Although abiotic stresses have been shown to provokecell death displaying hallmarks of PCD (Chen et al.,2009; Qi et al., 2011; Nawkar et al., 2013; Petrov et al.,2015), detailed case-by-case investigations have to showif genuine actively controlled, genetically encoded pro-grams are responsible for these types of cell death.
Although there appears to be an overlap between thegenes up-regulated during abiotic stress-induced celldeath and pathogen-induced ePCD, our meta-analysissuggested that pathogen-related ePCD and differentiation-induced dPCD are regulated largely independently(Fig. 2). To confirm these results experimentally, we
Figure 4. Selected promoter-reporter lines highlighting cells preparingfor dPCD. PASPA3, RNS3, SCPL48, CEP1, and DMP4 expression pat-terns in developing seeds, developing anthers, the root cap, the xylem,and senescing petals (columns from left to right). pPASPA3..H2A-GFPis expressed in the embryo-surrounding region of the endosperm fromtorpedo stage onwards in the tapetum layer of the anther, in the LRCand the xylem, and in mature petals nearing floral organ senescence.pRNS3 ..H2A-GFP shows a very similar pattern. The SCPL48 pro-moter confers a broader spatial and temporal expression pattern and isnot only restricted to cells preparing for dPCD. pCEP1 ..H2A-GFPshows GFP expression in the endosperm and seed coat of developingseeds, the tapetum and its surrounding anther tissues, cells from thelowest tier of the LRC, differentiating xylem vessels, and the agingpetals. pDMP4 ..H2A-GFP is again more similar in expression topPASPA3 and pRNS3. TE, Tracheary elements. Bar = 50 mm.
performed a quantitative reverse transcription (qRT)-PCRexperiment of plants inoculated with an HR-inducingPseudomonas syringae strain. In contrast to HR markergenes, none of the canonical dPCD marker gene tran-scripts were significantly up-regulated during HR (Fig. 6;Supplemental Fig. S5). To test if only individual cells
express dPCD reporter genes, whichmight not register ona tissue-wide scale of RNA quantification, we also inves-tigated promoter-reporter lines but did not find any GFPsignals in or around HR lesions (data not shown). Theseresults confirm that dPCD marker genes are not tran-scriptionally regulated during HR-related ePCD.
Core dPCD Marker Genes Are Evolutionary Conserved inLand Plants
The phenomenon of developmentally regulated PCDis most likely evolutionary ancient and occurs also insimple land plants, for instance the moss Physcomitrellapatens (Xu et al., 2014). To assess the degree towhich themolecular regulation of dPCD might be evolutionaryconserved, we investigated the conservation of thedPCD indicator genes identified in Arabidopsis withinthe plant kingdom as well as between plants and ver-tebrates. According to the plant comparative genomicsplatform PLAZA (Proost et al., 2015), RNS3, BFN1,PASPA3, MC9, and SCPL48 are widely conserved inthe green plant lineage, while BFN1 appears to be re-stricted to the land plant lineage (Table III). Using thecomparative online tool Phytozome (Goodstein et al.,2012), we identified putative homologs of these dPCDmarkers in different angiosperm lineages, as well as inthe basal angiosperm Amborella trichopoda and in thelower land plants P. patens and Selaginella moellendorffii.In the green alga Chlamydomonas reinhardtii, we identi-fied protein sequences related to SCPL48, PASPA3, andRNS3, sequences with limited blast length for MC9 butno clear homolog for BFN1 (Supplemental Table S7).Outside the plant kingdom, the HomoloGene algo-rithm (Sayers et al., 2012) indicated conservation ofRNS3, SCPL48, and PASPA3 in all eukaryotes, whileBFN1 and MC9 appeared not to be conserved betweenplants and vertebrates (Table III). Interestingly, a pu-tative RNS3 homolog, the RNase T2, has recently beenimplicated in the control of melanocyte apoptosis viathe tumor necrosis factor receptor-associated factor2pathway in vitiligo patients (Wang et al., 2014). Fur-thermore, the putative PASPA3 homolog Cathepsin Dfunctions as a proapoptotic gene targeting Bid afterrelease from the lysosome (Appelqvist et al., 2012;Repnik et al., 2014).
These results suggest a high degree of conservation ofcore dPCDmarker geneswithin the green plant lineage.Whether the proapoptotic roles of PASPA3- and RNS3-related enzymes in mammals is due to functional con-servation or due to convergent evolution is difficult todetermine. Nevertheless, it is tempting to speculate thatsimilar mechanisms are functional in both animal andplant PCD types.
DISCUSSION
To date, despite the undisputed importance of thediverse forms of plant PCD for development and forenvironmental interactions (Wu et al., 2014; Petrov
Figure 5. Abiotic stress treatments cause cell death without the up-regulation of dPCD reporters. Abiotic stress treatments applied to 5-d-old seedlings from dPCDmarkers SCPL48, RNS3, and PASPA3. Pictureswere taken after the indicated time points and treatments at the root tipto show the expression around the LRC and were stained with PI tohighlight the cell walls and cells with compromised plasma membraneintegrity indicative of cell death (arrowheads). BM, Bleomycin; HU,hydroxyurea.
et al., 2015; Van Hautegem et al., 2015), still only little isknown about the molecular regulation of these pro-cesses. During the plant life cycle, PCD is induced atnumerous occasions, but it is unclear whether there arecommon mechanisms involved in controlling differentPCD types. Attempts to characterize and relate differ-ent plant PCD types have been made, based chiefly onmorphological and ultrastructural features of dyingcells (van Doorn, 2011; van Doorn et al., 2011). Here, weexplored the possibility to characterize different typesof plant PCD using molecular information. As tran-scriptional regulation has been implicated in plantPCD control (Van Hautegem et al., 2015), and as so faronly scarce proteomic data in plant PCD contexts exist,this transcriptome meta-analysis is a first step into asystematic molecular characterization of plant PCDprocesses.
One aim of our study was to investigate whetherexisting transcriptome data might be useful for a mo-lecular categorization of plant PCD types. By compar-ing transcriptome profiles of different developmentalstages and environmental stresses leading to cell death,we expected to find similarities and differences thatwould allow relating different PCD types based on thedegree of common gene regulation. Such informationcould be used to complement PCD characterizationbased on morphological and biochemical hallmarks(vanDoorn, 2011; van Doorn et al., 2011). Our approachof exploiting publicly available ATH1 data sets bymeans of several bioinformatics approaches was suc-cessful in identifying unique dPCD indicator genes.Promoter-reporter constructs of these genes markedcells preparing for cell death in well-defined PCD set-tings, e.g., the xylem (Bollhöner et al., 2012), the root cap
(Fendrych et al., 2014), or the tapetum (Plackett et al.,2011), but also highlighted cell types in which so faronly scarce genetic evidence exists for the occurrence ofPCD, e.g., the seed coat (Haughn andChaudhury, 2005)or the endosperm (Waters et al., 2013) in developingseeds. These results suggest that a conserved core ofPCD-associated genes is commonly regulated in di-verse dPCD contexts, and our findings will give im-pulses to investigate developmentally regulated PCDprocesses in more detail.
Among the genes that we found to be transcriptionallyregulated during differentiation-induced dPCD wereseveral genes encoding nucleases, including CAN1,BFN1, and RNS3. BFN1 is a well-known leaf senescencereporter, which has also been shown to function inchromatin breakdown during root cap PCD in Arabi-dopsis and tracheary element PCD in Zinnia elegans (Itoand Fukuda, 2002; Fendrych et al., 2014). CAN1 is astaphylococcal-like plasma membrane-bound nucleasewhose expression has been associated with PCD eventsbefore (Le!sniewicz et al., 2012), but its exact role re-mains unclear. RNS3 belongs to the evolutionary con-served family of T2 endoribonucleases that cleavesingle-stranded RNA. T2 endoribonucleases have beensuggested to perform a variety of functions, includingscavenging of nucleic acids, degradation of self-RNA,modulating host immune responses, and serving as cel-lular cytotoxins (Luhtala and Parker, 2010). In plants, T2ribonucleases are induced during phosphate starvationand have been hypothesized to function in providingphosphates from nucleic acids (Taylor et al., 1993; Bariolaet al., 1994). Our results showRNS3 up-regulation duringleaf and floral organ senescence, correlating senescence-induced cell death with differentiation-induced dPCD.
Figure 6. dPCD marker genes are not up-regulated during HR PCD. qRT-PCR of Col-0 wild-type plants inoculated with anavirulent HR-inducing P. syringae strain in a time course experiment after infection. Relative expression of the indicated genesboth in the inoculated area and in noninoculated tissue was determined by qRT-PCR at the indicated time points. PATHO-GENESIS RELATED1 (PR1), MC1, and MYB DOMAIN PROTEIN30 (MYB30) were used as HR marker genes. Expression valueswere normalized using the SAND family gene as internal standard. Ratios of the expression values for each gene in the inoculatedzone with respect to the noninoculated area are presented for each time point. Mean and SE of the mean values were calculatedfrom three independent experimentswith three replicates. Statistical significance according to a Student’s t test P value of 0.005 isindicated by asterisks. hpi, Hours after inoculation; a.u., arbitrary units.
Next to nucleases, also protein hydrolases includingPASPA3, MC9, SCPL48, and CEP1 are among the coreof dPCD-associated proteins. For most of these prote-ases, little data exist regarding their actual function andsubstrates. The degradome of MC9 has been investi-gated in detail, thoughmost substrates identified rathersuggested functions other than PCD (Tsiatsiani et al.,2013). Nevertheless,MC9 has been shown to be a part ofa proteolytic cascade effecting postmortem cell clear-ance of tracheary elements in Arabidopsis (Bollhöneret al., 2013). Recently, MC9 activity was found to be im-portant to mediate oxidative stress-dependent cell deathvia the cleavage of GRIM REAPER (Wrzaczek et al.,2015).Next to hydrolytic enzymes, genes encoding several
proteins of unknown functions such as the plasmamembrane-localized DMP4 were up-regulated duringseveral dPCD processes. DMPs represent a uniquefamily of plant-specific plasma membrane proteins ofunknown function that have been recently identified ina screen for senescence-associated genes in Arabidopsis(Kasaras and Kunze, 2010). Of the 10 Arabidopsis DMPparalogs, DMP4 is coregulated with the core of dPCDmarker genes and up-regulated in several dPCD con-ditions. Additionally, expression of DMP4 has beendescribed in abscission zones of floral organs (Kasarasand Kunze, 2010), although involvement of PCD in thisabscission process has not been investigated. The mo-lecular function of DMP proteins still needs to be de-termined, but misexpression of Arabidopsis DMP1 ledto an aberrant endoplasmic reticulum and in some casesto the death of transfected cells (Kasaras et al., 2012).Despite the fact that different PCD types appear to
exhibit different gene expression profiles, an adequatesupervised classification of PCD types based on theavailable transcriptome data proved to be possible onlyfor some PCD subtypes, possibly due to the nature andquantity of the available transcriptome data sets. Mostdata sets analyzed were not explicitly designed to
characterize gene expression changes associated withcell death processes but rather to identify regulators ofprocesses that precede or even might counteract celldeath. What is more, deducing from the experimentalmetadata which particular PCD subtype, if any, isrepresented in a given data set is not always straight-forward.
To reliably classify different types of plant PCD, amore thorough understanding of their molecular reg-ulation will be necessary. A means to this end will bethe generation of specific transcriptome profiles ofprecisely described PCD systems. For differentiation-induced dPCD, this is a challenging task, as only sin-gle cells, or small groups of cells, are undergoing celldeath at a time. Techniques of isolating these cells ortheir nuclei for transcriptome analysis by fluorescent-associated cell sorting or isolation of nuclei tagged inspecific cell types (Deal and Henikoff, 2011) will be in-strumental to obtain meaningful data sets. The dPCDpromoter-reporter constructs presented in this studywill facilitate these approaches. At least for closelyrelated PCD types, for instance, different forms ofdifferentiation-induced dPCD, such a comparative ap-proach will become valuable to reveal unique PCDmarkers and putative core PCD regulators. This ap-proach, accompanied by thorough morphological,molecular genetics and cell biological analyses, willopen the way to a more comprehensive understandingof PCD as a fundamental cellular process in plants.
CONCLUSION
Despite the progress achieved over the last decade bya relatively small research community dedicated toplant PCD, the molecular regulation of PCD largelyremains a terra incognita. To fill the white spots on themap, and to relate the findings made in different plantPCD systems, we need to understand more of the
Table III. Evolutionary conservation of putative core dPCD markers
% ID reflects the sequence similarity between the Arabidopsis gene and the best blast hit in vertebrates. All genes belong to PLAZA 3.0 orthologousgene families that encompass the Magnoliophyta (RNS3, BFN1, and MC9) or Viridiplantae (SCPL48 and PASPA3) clade (not shown). AGI, Arabi-dopsis Genome Initiative gene code; HOM, homologous; Nuclease PA3-like, a predicted protease (GenBank accession number XP_005974529.1);CPVL, carboxypeptidase, vitellogenic-like.
AGI (Name)PLAZA 3.0 Homologous
Gene Family
PLAZA 3.0 Plant
Clade of HOM FamilyHomoloGene Blast Hits in Vertebrates % ID Role in Vertebrates
RNase T2 30 Potentially skincell apoptosis(Wang et al.,2014)
AT1G11190 (BFN1) HOM03D001490 Embryophyta No information Nuclease PA3-like 27AT5G04200 (MC9) HOM03D001276 Viridiplantae No information No clear hits 0AT3G45010 (SCPL48) HOM03D000050 Viridiplantae 137548, conserved
molecular principles that govern plant cell death. Here,we made a step toward a comprehensive understand-ing of plant PCD by integrating genome-wide tran-scriptome profiles of different established as well as lesswell-known cell death systems. With the recognizedexpression patterns and dPCD reporter lines, we cannow progress to a more specific mode of analysis. Ofcourse, transcriptional regulation is only a fraction ofthe molecular control that leads to an ordered andtimely termination of vital processes of a cell under-going PCD. A challenge for the next decade will be todefine themolecular modes of function of putative PCDregulators and the posttranslational modifications thatlead to the rapid execution of cell death observed inmany systems.
MATERIALS AND METHODS
Meta-Analysis Data Retrieval
We retrieved Affymetrix ATH1 CEL files for the various transcriptome data
sets from ArrayExpress (http://www.ebi.ac.uk/arrayexpress/), Gene Ex-
pression Omnibus (http://www.ncbi.nlm.nih.gov/geo/), Riken Expression
Array Database (http://read.gsc.riken.go.jp/), or other third-party data pro-
viders. Multiple rounds of preanalysis processing steps (data curation and fil-
tering to remove conditions with little or no differential gene expression) were
performed to retain an optimal selection of expression data sets.
Meta-Analysis Detection of Differential Expression
Themicroarray datawere preprocessedwith the RobustMultiarrayAverage
procedure, as implemented in BioConductor (Irizarry et al., 2003; Gentleman
et al., 2004). An up-to-date Chip Defnition File based on the latest version of the
Arabidopsis genome annotation by The Arabidopsis Information Resource was
retrieved from BrainArray (http://brainarray.mbni.med.umich.edu) to define
probe-gene relations. A filtering of differentially expressed genes was per-
formed using the R/Bioconductor software package Limma (Ritchie et al., 2015)
to retain only those genes with an adjusted P # 0.05 and absolute log2 fold
change . 1.
HCA
The expression profiles of theATH1 genes showingdifferential expression in
at least one PCD condition were hierarchically clustered with the Orange
Canvas software (http://orange.biolab.si/) using Pearson’s correlation dis-
tance as the distance measure and the average linkage clustering option. To
identify the most commonly up-regulated genes in particular PCD clusters, we
used an R script that, given a cluster of interest, ranks genes according to the
number of conditions in the cluster in which they are significantly up-regulated
(P , 0.05) at least 2-fold. For each cluster, the resulting ranked gene list was
truncated at a specific number of observed up-regulations to obtain lists for all
clusters of 25 to 30 genes each (Supplemental Table S3). A similar analysis was
done to identify genes that are commonly up-regulated across all conditions
labeled as dPCD. A gene was considered to be commonly up-regulated in
dPCD when it was designated as significantly up-regulated (P , 0.05) at least
2-fold in 60% of the dPCD-labeled conditions.
Supervised Classification Analyses
SVM (Cortes and Vapnik, 1995) and RF (Breiman, 2001) analyses were
performed using the Orange toolbox (Demšar et al., 2013) by writing Python
scripts accessing the Orange API. In each analysis, an automated exhaustive
search of the algorithm parameter space was performed to optimize the pa-
rameter settings. These settings are reported per analysis in Supplemental Table
S4. Comparison of the classification performance across analyses and algo-
rithms was done by means of the Matthews Correlation Coefficient (MCC) as
reported after 5- or 10-fold cross validation (5-fold cross validation was used
when the number of contrasts in one of the classes was ,10). The MCC is a
balanced measure of binary classification performance that is particularly
useful if the classes are of different sizes. MCC scores range from 1 for perfect
classifiers to –1 when there is a total disagreement between the predicted and
observed class labels, with a score of 0 indicating that the classifier does not
perform better than random.
For the analyses on balanced dPCD- and ePCD-labeled data, 19 (or 10) ePCD
experiments were randomly sampled without replacement out of the relevant
ePCD subset and added to the 19 (or 10) dPCD experiments, after which SVM
and RF classifiers were learned. This random selection was performed
100 times, and the average MCC score is reported in Supplemental Table S4.
Genevestigator Coexpression Tool Search
The query genes were screened with the Conditions Search and Similarity
Search tools of Genevestigator. To find the relevant conditions that induce the
expression of the query gene, all ATH1microarrayswere given as input into the
Conditions search (Perturbation tool) and filtered by selecting microarrays
showing a log-fold change of the query gene greater than or equal to 2 and
a P value greater than or equal to 0.01. The resulting microarrays were saved
in a new list and fed in the Coexpression tool to find the top 200 positively
correlated genes in the Perturbation option. To identify commonly coregulated
genes between different genes, coregulated genes with a Genevestigator
score (Pearson’s correlation coefficient) greater than 0.6 were selected for
each gene. The resulting gene lists were fed into the online Venn Diagram tool
program provided by the VIB-Ghent University Bioinformatics and Systems
Biology laboratory at http://bioinformatics.psb.ugent.be/cgi-bin/liste/
Venn/calculate_venn.htpl to identify commonly regulated genes.
Identification of Genes Coregulated in Maturing Xylemand LRC
The VLRTC method (Parizot et al., 2010) was used to reanalyze the data
from Brady et al. (2007) as described in Fendrych et al. (2014). The candidate
genes were first thresholded for their expression in the LRC and in thematuring
tracheary elements as follows:
TRUE if !
EXPLRC$ 2 averageEXPrest
"
AND!
EXPXM$ 2 averageEXPrest
"
And these genes were further ranked according to:
rank ¼ ðaveragefEXPLRC;EXPXMgÞ=ðMAXfEXPrestgÞ
MAX refers to the maximum expression value; EXP to normalized expression
values, rest to {Stele (wol), Stele(J2501),Protophloem(S32), Phloem+Companion
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Author: Pierre BUSCAILL
Title: A protease of the subtilase family negatively regulates plant defence through its interaction with the Arabidopsis transcription factor AtMYB30.
Plants defence responses are often associated with the development of the so-called hypersensitive response (HR), a form of PCD that confines the pathogen to the infection site. The sharp boundary of the HR suggests the existence of efficient mechanisms that control cell death and survival. The Arabidopsis transcription factor AtMYB30 positively regulates plant defence and HR responses by enhancing the synthesis of sphingolipid-containing Very Long Chain Fatty Acids (VLCFA) after bacterial infection. The activity of AtMYB30 is tightly controlled inside plant cells through protein-protein interactions and post-translational modifications. During my PhD, we identified a protease of the subtilase family (AtSBT5.2) as a AtMYB30-interacting partner. Interestingly, we have shown that the AtSBT5.2 transcript is alternatively spliced, leading to the production of two distinct gene products that encode either a secreted [AtSBT5.2(a)] or an intracellular [AtSBT5.2(b)] protein. The specific interaction between AtMYB30 and AtSBT5.2(b), but not AtSBT5.2(a), leads to AtMYB30 specific retention outside of the nucleus in small intracellular vesicles. atsbt5.2 Arabidopsis mutant plants, in which both AtSBT5.2(a) and AtSBT5.2(b) expression was abolished, displayed enhanced HR and defence responses. The fact that this phenotype is abolished in an atmyb30 mutant background suggests that AtSBT5.2 is a negative regulator of AtMYB30-mediated disease resistance. Importantly, overexpression of the AtSBT5.2(b), but not the AtSBT5.2(a), isoform in the atsbt5.2 mutant background reverts the phenotypes displayed by atsbt5.2 mutant plants, suggesting that AtSBT5.2(b) specifically represses AtMYB30-mediated defence.
UMR CNRS/INRA 2594/441, 24 Chemin de Borde Rouge – Auzeville, CS 52627, 31326 Castanet-Tolosan cedex, France.
Auteur : Pierre BUSCAILL
Titre : Une protéase de la famille des subtilases régule négativement les réactions de défense à travers son interaction avec le facteur de transcription d’Arabidopsis AtMYB30.
Les réactions de défense végétales sont souvent associées au développement de la réponse hypersensible (HR), une forme de mort cellulaire programmée qui confine l'agent pathogène au niveau du site d'infection. La frontière nette de la HR suggère l'existence de mécanismes efficaces qui contrôlent la frontière entre mort cellulaire et survie. Le facteur de transcription d'Arabidopsis AtMYB30 régule positivement la HR et les réponses de défense de la plante en augmentant la synthèse des acides gras à très longue chaîne (VLCFA) après infection bactérienne. L'activité d’AtMYB30 est étroitement contrôlée à l'intérieur des cellules végétales par des interactions protéine-protéine et des modifications post-traductionnelles. Au cours de mes travaux de thèse, nous avons identifié une protéase de la famille des subtilases (AtSBT5.2) en tant que partenaire protéique d’AtMYB30. Chose intéressante, nous avons montré que le transcrit d’AtSBT5.2 est épissée de façon alternative, conduisant à la production de deux produits de gènes distincts codant soit pour une isoforme sécrétée [AtSBT5.2 (a)] soit une isoforme intracellulaire [AtSBT5.2 (b)]. L'interaction spécifique d’AtMYB30 avec AtSBT5.2(b), mais pas avec AtSBT5.2(a), conduit à une rétention d’AtMYB30 à l'extérieur du noyau au sein de petites vésicules intracellulaires. Des plantes d’Arabidopsis mutantes atsbt5.2, ne montrant ni expression d’AtSBT5.2(a) ni d’AtSBT5.2(b), présentent des réactions de défense et de HR accrues. Ce phénotype étant abolie dans un fond génétique mutant atmyb30, AtSBT5.2 est donc un régulateur négatif de la résistance aux maladies induites par AtMYB30. Fait important, la surexpression de l’isoforme AtSBT5.2(b), mais pas celle de l’isoforme AtSBT5.2(a), dans le fond mutant atsbt5.2 rétablit les phénotypes présentés par les plantes mutantes atsbt5.2, ce qui suggère qu’AtSBT5.2(b) réprime spécifiquement la réponse de défense induite par AtMYB30.
