ORIGINAL ARTICLE

OPEN ACCESS

# Some Like it Hot: Efficiency of the Type III Secretion System has Multiple Thermosensitive Behaviours in the *Pseudomonas syringae* Complex

E. Caullireau<fnref n="1" />,² | D. Danzi<fnref n="1" /> | V. M. Tempo<fnref n="1" /> | M. Pandolfo<fnref n="1" /> | C. E. Morris² | E. Vandelle<fnref n="1" />

**Correspondence:** E. Vandelle (elodiegenevieve.vandelle@univr.it)

**Received:** 29 July 2025 | **Revised:** 14 October 2025 | **Accepted:** 22 October 2025

**Funding:** We thank the EUR IMPLANTEUS program (ANR-18-EURE-0009) for funding supporting E. Vandelle collaboration with INRAE for this work.

**Keywords:** bacterial virulence | environmental factors | hypersensitive response | molecular plant-pathogen interactions | T3SS

## ABSTRACT

The *Pseudomonas syringae* species complex is an important group of ubiquitous bacteria containing plant-pathogenic strains of which many strains cause damage and economic losses to a wide range of crops. Efforts to elucidate host range determinants have focused on the effector repertoires in the type 3 secretion system (T3SS). However, recently, we showed that the inability of a *P. syringae* pv. *actinidiae* strain to trigger effector-triggered immunity (ETI) in *Arabidopsis thaliana* is due to an inefficient T3SS and not to the absence of a recognised effector. We thus compared the T3SS efficiency of several *P. syringae* strains belonging to different phylogroups. We assessed the temporal dynamics of their ability to induce ion leakage, an indicator of the hypersensitive response (HR), in *A. thaliana* Col-0, as a proxy for T3SS function. Though not a direct measurement of T3SS efficiency, the use of a robust statistical model allowed us to reveal that *P. syringae* strains DC3000 *avrB* and M6 *avrB* consistently triggered a strong HR while other strains induced it at significantly different intensities depending on temperature. Among thermosensitive strains, both low and warm temperature dependencies for T3SS efficiency were observed, irrespective of their in vitro growth optimum, even among quasiclonal strains. These results reveal a strong, strain-specific regulatory role of temperature in effector injection and reinforce the importance of environmental factors in the outcome of plant-bacteria interactions. Moreover, this work highlights the need to study bacterial virulence beyond model strains such as DC3000 and B728a that are not representative of the diversity of the *P. syringae* species complex.

## 1 | Introduction

*Pseudomonas syringae* is a complex of gram-negative bacteria that poses a threat to global agriculture with new outbreaks that emerge regularly (Lamichhane et al. 2014; Lamichhane et al. 2015). *P. syringae* has been divided into at least 13 phylogenetic groups (phylogroups, PG), further divided into 23 clades (Berge et al. 2014). During infection, *P. syringae* relies on an arsenal of virulence factors, though its pathogenesis is predominantly mediated by the type III secretion system

(T3SS), a highly conserved needle-like specialised protein secretion machinery found in numerous gram-negative bacterial pathogens affecting plants and animals. The T3SS forms a continuous channel, guiding the translocation of diverse proteinaceous effectors (T3Es) directly into the host cell or apoplast (Büttner and He 2009; Jin and He 2001; Li 2002; Roine et al. 1997). *P. syringae* strains with the canonical T3SS commonly harbour a repertoire of approximately 15–30 T3Es, which facilitate the invasion of plant host cells, suppress plant immunity or interfere with essential plant cellular processes

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Molecular Plant Pathology* published by British Society for Plant Pathology and John Wiley & Sons Ltd.

<footnote n="1">¹Department of Biotechnology, University of Verona, Verona, Italy | ²INRAE, Pathologie Végétale, Montfavet, France</footnote>
(Chang et al. 2005; Cunnac et al. 2009; Galán and Collmer 1999; Guo et al. 2009; Guttman et al. 2002; Hueck 1998; Lee 1997; Lindeberg et al. 2012; Martel et al. 2022; Mudgett and Staskawicz 1998; Xin et al. 2016). Of note, there is no direct relationship between the size or content of the T3E repertoire and host range (Baltrus et al. 2017; Morris et al. 2019).

According to the 'disease triangle' paradigm (Stevens 1960), plant diseases arise from the interplay between a susceptible plant and a virulent pathogen, under conducive environmental conditions, resulting in a compatible reaction. Overall plant-pathogen interaction mechanisms are highly influenced by environmental conditions, which can either favour, have neutral effects or hinder both partners (Velásquez et al. 2018; Xin et al. 2018). Among the environmental factors, temperature has a regulatory role for virulence in plant-associated bacteria (reviewed in references Smirnova et al. 2001; Velásquez et al. 2018).

Within the *P. syringae* species complex, temperature variations impact various traits crucial for bacterial fitness, including phytotoxin production, exopolysaccharide biosynthesis, motility or the quorum-sensing system (Aguilera et al. 2007; Aguilera et al. 2017; Arvizu-Gómez et al. 2013; Bender et al. 1999; Braun et al. 2009; Hockett et al. 2013; Krishna et al. 2022; Li et al. 2006; Nüske and Fritsche 1989; Palmer and Bender 1993; Peñaloza-Vázquez et al. 1997; Scalschi et al. 2022; Smirnova et al. 2001; Ullrich et al. 2000; Weingart et al. 2004). The T3SS has also been investigated concerning its possible thermoregulation. In *P. syringae* pvs. *syringae* and *tomato* (Pto), the secretion of HopPsyA and AvrPto effectors in vitro was impaired at temperatures above 22°C and 20°C, indicating some kind of low-temperature dependency for their T3SS efficiency (Van Dijk et al. 1999). In contrast, recent findings in Pto DC3000 revealed that the translocation of T3Es in *Arabidopsis thaliana* cells is enhanced at 30°C compared to 23°C, indicating that the T3SS can function efficiently even at elevated temperatures (Huot et al. 2017). However, in tomato, the expression of the Pto DC3000 T3SS-related genes *hrpL* and *hrpA*, encoding the master alternative sigma factor and the major structural protein of the T3SS pilus, respectively, was not affected by a temperature rise from 26°C to 31°C, although the expression of the avirulence gene *avrPtoB* was significantly reduced (Scalschi et al. 2022). On the other hand, for *P. syringae* pv. *actinidiae* strains, it was shown that there was no difference in *hrpA1* promoter activity in vitro across a temperature range of 18°C-28°C; nonetheless, substantial differences were evident at a functional level, demonstrating a low-temperature dependency for T3SS efficiency for these strains (Puttilli et al. 2022). However, the complete implications of warm temperatures on *P. syringae* virulence in plants remain poorly understood (Hockett et al. 2013; Li et al. 2006). Studies indicate complex interactions with plant immune signalling pathways, emphasising the need for further research to understand their implications in terms of disease (Cheng et al. 2013; Huot et al. 2017).

Evidence of the influence of temperature in regulating virulence factors in *P. syringae* species complex has been documented; however, there have not been studies dedicated to comparing strains under identical conditions. Consequently, we wanted to further understand the role of temperature on the function/

activation dynamics of the T3SS by investigating a broader range of diversity within the *P. syringae* species complex under comparable conditions. For this purpose, we transformed 13 strains of *P. syringae* in phylogroups 1, 2 and 3 to carry the effector AvrB and infiltrated them into *A. thaliana* Col-0 leaf disks. In this model plant, AvrB is indirectly recognised by the resistance protein RPM1, through RIN4 modification, which triggers HR (Innes et al. 1993; Mackey et al. 2002; Mudgett 2005). Infiltrated leaf disks were incubated at different temperatures and the quantification of electrolyte leakage served as the indicator of HR onset. Conductivity increase was used as a proxy for T3SS efficiency, and this allowed us (i) to effectively discriminate strains based on a robust phenotype directly linked to the activation of the T3SS, and (ii) to observe different behaviours in response to temperature.

## 2 | Results

### 2.1 | The Intensity of HR Induction Is Not Strictly Reproducible for Individual Strains

As the wild-type (WT) versions of many of the strains selected for study do not result in HR induction—due to compatible interaction (*P. syringae* strains DC3000, M6) or non-host incompatible interaction without HR (strains CRA-FRU 8.43, B728a, 1448A)—we introduced *avrB* to study T3SS efficiency based on ion leakage induction as a proxy (Table S3). Hence, to evaluate T3SS functionality at different temperatures, *avrB*-expressing *P. syringae* strains were infiltrated into *A. thaliana* Col-0 leaf disks. As a T3SS-dependent mechanism, ion leakage was quantified by measuring the increase in conductivity due to dying cells. Conductivity levels measured among the diverse replicated experiments were highly variable. The conductivity levels measured for a given modality (i.e., one strain infiltrated and incubated at one temperature) doubled or tripled among replicated experiments. Four examples of this variability are shown in Figure 1. For instance, across the seven replicated experiments for strain USA007 *avrB* at 18°C, the ratio of areas under the curves calculated between the one that induced the most and the least was equal to 2.8 (Figure 1B). Moreover, conductivity showed considerable heteroscedasticity, that is, there was a positive correlation between the mean area under the curves and their variance with Spearman's coefficient = 0.91; *p* < 0.05 (Figure S1). This large variability raised the question of how to quantify the HR induction to compare the strains, as addressed in the next section.

### 2.2 | The Intensity of HR Induction Varies Among Strains

To compare HR induction intensity among strains, we accounted for the variability described above by fitting linear mixed-effects models (LMMs) to our data. This statistical approach allowed us to classify strains as inducers or non-inducers at each of the temperatures that we tested. This revealed that almost all the *P. syringae* strains induced HR except for J35 *avrB* at all the temperatures, MAFF302273 *avrB* at 24°C and 28°C, B728a *avrB* at 24°C and 1448A *avrB* and CRA-FRU 8.43 *avrB* at 28°C (Table 1). The inducer strains led to conductivity
<figure><img src="image_1.png" /></figure>

<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /><figcaption>**FIGURE 1** | Electrolyte leakage curves obtained post-infiltration for *Pseudomonas syringae* strains M6 *avrB* at 18°C (A), USA007 *avrB* at 18°C (B), LAB0041 *avrB* at 24°C (C) and CC1498 *avrB* at 28°C (D). *Arabidopsis thaliana* Col-0 leaf disks infiltrated with each strain were incubated at different temperatures, as indicated. Each curve represents the mean increase in conductivity measured over time for one independent biological replicate performed with three technical replicates each. The experiment was performed at least five times ($5 \le n \le 8$) for each strain. Error bars represent standard error. For each curve, the area under the conductivity progress curve (AUCPC) was also calculated, as well as the ratio between the highest and the smallest AUCPC.</figcaption></figure>

levels that were significantly greater than those measured in the mock treatment (10 mM MgCl₂ or *hrp*-inducing medium, HIM) (*p* < 0.05) according to LMMs. More specifically, our results demonstrated that all the inducer strains varied in the intensity of the HR induction they caused. The model estimated the mean difference in points of conductivity measured between the tested modality and the mock treatment. The values presented in Table 1 ('Estimate') are proxies of the intensity of HR induction for each strain. DC3000 *avrB* and M6 *avrB* displayed the highest values ('Estimate' > 65 regardless of the temperature tested), whereas some others such as the three quasiclonal strains CC0073 *avrB*, CC0094 *avrB* and CC1498 *avrB* averaged < 20. These differences are also reflected in the mean areas under conductivity progress curves (AUCPC) at

each temperature as shown in Figure 2. This proxy of the HR induction intensity was correlated neither with the *avrB* expression levels (Figure S2) nor with the bacterial growth capacity at a given temperature (Figure S3).

## 2.3 | The Intensity of HR Induction Is Temperature-Sensitive in Half of the Inducer Strains

With LMMs, we categorised the HR inducer strains according to the temperature sensitivity of HR induction. Six out of 11 HR inducer strains were insensitive to a change in temperature (DC3000 *avrB*, M6 *avrB*, LAB0041 *avrB*, CC0073 *avrB*,
<table><caption>**TABLE 1** | Statistics associated with linear mixed-effects models fitted to ion leakage experiment results.</caption><thead><tr><th rowspan="3">Phylogroup</th><th rowspan="3">Strain</th><th colspan="6">Inducer at a given temperature</th><th colspan="2">Temperature effect</th></tr><tr><th colspan="2">18°C</th><th colspan="2">24°C</th><th colspan="2">28°C</th><th rowspan="2">p</th><th rowspan="2">Estimate</th></tr><tr><th>Estimate</th><th>p</th><th>Estimate</th><th>p</th><th>Estimate</th><th>p</th></tr></thead><tbody><tr><td rowspan="4">1a</td><td>DC3000</td><td>69.97</td><td><strong>2.00e-16</strong></td><td>73.12</td><td><strong>1.25e-15</strong></td><td>65.27</td><td><strong>8.46e-15</strong></td><td>8.02e-01</td><td>-0.19</td></tr><tr><td>M6</td><td>95.14</td><td><strong>2.00e-16</strong></td><td>89.06</td><td><strong>5.35e-16</strong></td><td>73.05</td><td><strong>1.59e-14</strong></td><td>1.95e-01</td><td>-2.07</td></tr><tr><td>T1</td><td>28.98</td><td><strong>2.00e-16</strong></td><td>29.07</td><td><strong>2.00e-16</strong></td><td>13.45</td><td><strong>2.81e-08</strong></td><td><strong>1.42e-02</strong></td><td><strong>-1.26</strong></td></tr><tr><td>LAB0041</td><td>31.36</td><td><strong>4.24e-11</strong></td><td>29.56</td><td><strong>2.00e-16</strong></td><td>16.83</td><td><strong>2.83e-09</strong></td><td>5.17e-02</td><td>-1.22</td></tr><tr><td rowspan="3">1b</td><td>J35</td><td>3.35</td><td>5.43e-02</td><td>0.18</td><td>9.19e-01</td><td>-1.27</td><td>4.46e-01</td><td colspan="2">NA</td></tr><tr><td>CRA-FRU 8.43</td><td>14.09</td><td><strong>4.69e-11</strong></td><td>4.97</td><td><strong>4.33e-04</strong></td><td>0.97</td><td>4.45e-01</td><td><strong>3.80e-03</strong></td><td><strong>-1.28</strong></td></tr><tr><td>USA007</td><td>52.24</td><td><strong>2.00e-16</strong></td><td>46.69</td><td><strong>8.58e-16</strong></td><td>34.15</td><td><strong>2.26e-12</strong></td><td><strong>3.35e-02</strong></td><td><strong>-1.70</strong></td></tr><tr><td rowspan="4">2d</td><td>CC0073</td><td>15.22</td><td><strong>5.97e-07</strong></td><td>15.28</td><td><strong>7.62e-07</strong></td><td>19.77</td><td><strong>3.42e-09</strong></td><td>3.55e-01</td><td>0.63</td></tr><tr><td>CC0094</td><td>6.86</td><td><strong>6.44e-08</strong></td><td>9.72</td><td><strong>2.61e-06</strong></td><td>14.49</td><td><strong>8.91e-08</strong></td><td><strong>9.76e-04</strong></td><td><strong>0.97</strong></td></tr><tr><td>CC1498</td><td>7.89</td><td><strong>4.96e-06</strong></td><td>12.69</td><td><strong>2.24e-05</strong></td><td>19.96</td><td><strong>1.52e-08</strong></td><td><strong>2.58e-02</strong></td><td><strong>1.36</strong></td></tr><tr><td>B728a</td><td>3.12</td><td><strong>2.08e-02</strong></td><td>2.22</td><td>1.61e-01</td><td>4.75</td><td><strong>8.07e-03</strong></td><td><strong>4.27e-02</strong></td><td><strong>0.37</strong></td></tr><tr><td rowspan="2">3a</td><td>MAFF302273</td><td>3.17</td><td><strong>1.73e-02</strong></td><td>2.88</td><td>9.68e-02</td><td>1.78</td><td>3.77e-01</td><td colspan="2">NA</td></tr><tr><td>1448A</td><td>5.14</td><td><strong>1.07e-02</strong></td><td>6.73</td><td><strong>9.73e-03</strong></td><td>2.46</td><td>2.41e-01</td><td>6.41e-01</td><td>0.53</td></tr></tbody></table>

Note: The effect of strains was calculated for each mutant bacterium at each temperature by comparing with the results obtained for the mock treatment (10 mM MgCl₂). Significant values of the estimate parameter (*p* < 0.05, in bold) are associated with hypersensitive response (HR)-inducing conditions. The temperature effect was evaluated for each *avrB*-expressing strain, inducing HR at least at two temperatures (non-inducer strains are highlighted in grey), comparing the electrolyte leakage curves obtained at these different temperatures. Strains insensitive to the temperature (*p* > 0.05) are highlighted in green, strains leading to minor changes in conductivity levels as the temperature increases (negative estimate, *p* < 0.05) are highlighted in blue and strains displaying a warm-dependency (positive estimate, *p* < 0.05) are highlighted in red. The number of replicated experiments for each modality (strain × temperature condition) varied from 3 up to 27.

<figure><img src="image_5.png" /><figcaption>**FIGURE 2** | Mean area under conductivity progress curve (AUCPC) calculations for all the replicated experiments (3 ≤ *n* ≤ 27) of each *avrB*-expressing strain at 18°C (A), 24°C (B) and 28°C (C). Error bars represent standard error.</figcaption></figure>

1448A *avrB*) (*p* > 0.05) (Table 1). The other HR inducer strains were temperature sensitive based on LMM analyses (*p* < 0.05) and could be categorised into two groups according to whether the ‘Estimate’ values were negative or positive. In one group, strains showed higher conductivity with lower temperatures (T1 *avrB*, CRA-FRU 8.43 *avrB* and USA007 *avrB*). In the case of the CRA-FRU 8.43 *avrB*, the decrease in conductivity observed with increasing temperature led the strain to be categorised as a

non-inducer at 28°C (Table 1). In the other group, strains showed higher conductivity with higher temperatures (CC0094 *avrB*, CC1498 *avrB* and B728a *avrB*). Importantly, the presence of *avrB* did not modify the behaviour of the strain. For instance, CC0094 WT induced HR in *A. thaliana* Col-0, displaying the same warm temperature dependency as observed with the *avrB*-expressing strain (Figure S4A). Likewise, the low temperature dependency behaviour of CRA-FRU 8.43 was conserved across both strain
<figure><img src="image_6.png" /><figcaption>**FIGURE 3** | HrpZ secretion profiles across a range of temperatures. *Pseudomonas syringae* strains expressing *avrB* were incubated in *hrp*-inducing medium (HIM) at 18°C, 24°C or 28°C for 5 h. Cell-free culture supernatant was obtained by centrifugation and filtration. Proteins of bacterial culture supernatant were then precipitated with trichloroacetic acid (TCA) and analysed by western blot using an anti-HrpZ antibody. The expected molecular weight is c. 40 kDa. A mix of samples proven to contain HrpZ in previous replicates was used as the positive control (C+) at two different concentrations (1× and 2×). Samples were run in different gels that were transferred onto membranes whose pictures were cropped and merged into a single figure.</figcaption></figure>

genotypes (with or without *avrB*) in the resistant *Actinidia arguta* (non-host plant inducing effector-mediated HR with strains belonging to the same biovar 3; Figure S4B; Table S3).

Moreover, the temperature sensitivity of the *avrB*-expressing strains was further confirmed by the analysis of HrpZ secretion in vitro as an assessment of T3SS functionality (Figure 3). A weak HrpZ signal was detected in the supernatants of CRA-FRU 8.43 *avrB* and USA007 *avrB* whereas no signal was detected in the supernatants of CC1498 *avrB* and CC0094 *avrB* at 28°C and 18°C. This confirms the temperature dependency of their T3SS with CRA-FRU 8.43 and USA007 preferring the low temperatures whereas CC1498 and CC0094 were more efficient as the temperature increased. Conversely, no significant differences were observed across all three temperatures for DC3000 *avrB*, M6 *avrB* and LAB0041 *avrB*, which were clearly categorised as temperature-insensitive strains. The absence of a signal in J35 *avrB*, on the other hand, was likely due to a poor capacity to induce its T3SS in vitro, and was correlated with its incapacity to induce HR in *A. thaliana*. Conversely, a strong HrpZ signal was observed in MAFF302273 *avrB* supernatant, even though it was unable to induce a detectable HR.

**2.4 | The Natural Genomic Background of the WT Strains Does Not Change the Temperature Responsiveness Patterns Observed With *avrB*-Expressing Strains**

Although we studied the ion leakage triggered by the same effec-
tor, namely AvrB, it is worth acknowledging that the response did
not take place in isolation from the rest of the responses, triggered
or not during the interaction of each of these strains with the plant
and from possible meta-effector interactions. Interestingly, while
the absence of HrpZ detection for J35 *avrB* was consistent with
its categorisation as an HR non-inducer, the strain MAFF302273
*avrB* displayed a functional T3SS at all tested temperatures
(Figure 3). Because this strain constantly did not lead to conduc-
tivity increase once infiltrated into leaf disks, this may suggest
that MAFF302273 contains in its repertoire some suppressive
effector(s) blocking the ability of AvrB to trigger the HR in *A.
thaliana*. Consequently, with the aim of revealing the presence

of effectors that may negatively affect the function of AvrB in the
non-inducing strains, we established the effector repertoire com-
position of all the strains by collecting information already avail-
able in the literature for 10 strains (Laflamme et al. 2020) and by
performing effector prediction in silico for three others. However,
to the best of our knowledge, none of the non-inducing strains
naturally harbour one (or more) uniquely present effectors as po-
tential direct or indirect antagonists of AvrB function (Table S2).
On the other hand, considering the same temperature-dependent
behaviour demonstrated for the WT versions of CC0094 in *A.
thaliana* and CRA-FRU 8.43 in *A. arguta*, described above, alto-
gether, these findings demonstrate that although the HR induc-
tion by AvrB in our experiment does not take place in isolation
from the background of both interaction partners, the various
outcome scenarios with the WT strains allow us to support our
conclusions made with the *avrB*-expressing strains, hence con-
firming the robustness of our approach.

**2.5 | Temperature-Responsiveness Patterns Vary Among Strains With Trends That Are Consistent Within a Given Phylogroup**

A given phylogroup could contain strains that induced HR in
temperature-sensitive and temperature-insensitive ways (Table 1).
However, the trend in temperature sensitivity was constant within
a phylogroup among its temperature-sensitive strains. Indeed,
the group of strains whose T3SS was more efficient at the lower
temperatures (T1 *avrB*, CRA-FRU 8.43 *avrB* and USA007 *avrB*)
and the group whose T3SS was more efficient at warmer tempera-
tures (CC0094 *avrB*, CC1498 *avrB* and B728a *avrB*) belong to the
phylogroups 1 and 2d, respectively (Table 1). Nevertheless, dra-
matic differences among strains even those that are very closely
related phylogenetically, were still observed, as illustrated by the
three quasiclonal *avrB*-expressing strains from phylogroup 2d,
CC0073, CC0094 and CC1498 (Table 1) (Figure 4). CC0073 *avrB*
was temperature-independent in its ability to induce HR, while
CC0094 *avrB* and CC1498 *avrB* both showed clearly greater ca-
cacity at warmer temperatures. Moreover, in terms of intensity,
CC1498 *avrB* caused higher values of conductivity measured at
24 h post-infiltration (hpi) than CC0073 *avrB* and CC0094 *avrB*.
Finally, in terms of kinetics, CC0073 *avrB* was responsible for a
faster HR induction at the beginning of the interaction—regardless of the temperature—whereas CC0094 *avrB* and CC1498 *avrB* were much slower in inducing HR (Figure 4).

## 2.6 | Strains From the *P. syringae* Complex Display Diverse Speeds of HR Induction

To account for dynamic aspects in the behaviours of *avrB*-expressing *P. syringae* strains, the time point when half of the total ions (i.e., final conductivity value measured at 24 hpi) has leaked was calculated for each replicated experiment for all modalities that were found to be HR-inducing. We used this parameter (hpi$_{50%}$) as an indicator of HR induction velocity. An analysis of variance of these ratios revealed significant differences among *avrB*-expressing strains (Kruskal–Wallis, *p* < 0.05). DC3000 *avrB* and M6 *avrB* proved to be the fastest HR inducers with half of their total induction already observable before 5 hpi (Figure 5A).

Yet again, the diversity of behaviours within phylogroups was revealed, even among the three *avrB*-expressing quasiclonal strains (Figure 5A, post hoc Dunn's test showed that CC0073 *avrB* and CC0094 *avrB* and CC1498 *avrB* groups differed significantly at *p* < 0.05). Furthermore, hpi$_{50%}$ values were compared across the different temperatures overall revealing that higher temperatures correlated with faster electrolyte leakage, consistent with the results observed for bacterial in vitro growth (Figure 5B).

# 3 | Discussion

## 3.1 | New Perspectives on Virulence Thermoregulation Processes

The diverse behaviours of T3SS efficiency observed in relation to incubation temperature indicate a very diverse adaptive potential of *P. syringae* for causing disease in the face of various

<figure><img src="image_7.png" /><figcaption>**FIGURE 4** | Electrolyte leakage curves over time obtained post-infiltration for *Pseudomonas syringae* strains CC0073 *avrB* (A), CC0094 *avrB* (B) and CC1498 *avrB* (C). Infiltrated *Arabidopsis thaliana* Col-0 leaf disks were incubated at 18°C (blue), 24°C (pink) and 28°C (red). Conductivity following infiltration of the mock treatment (10 mM MgCl$_2$) and incubation at 24°C is represented by the black dotted line. Data represent one single representative biological replicate with all strains and temperature conditions evaluated simultaneously with three technical replicates each. The experiment was performed at least five times ($5 \le n \le 11$) for each strain. Error bars represent standard error.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**FIGURE 5** | Estimation of velocity of hypersensitive response (HR) induction. The proxy for velocity was calculated as the time point when half of conductivity increase is reached for each *avrB*-expressing strain inducing HR in *Arabidopsis thaliana* Col-0 leaf disks at least at one temperature condition. (A) *Pseudomonas syringae* strains are sorted by phylogroup from left to right, PG1a (purple), PG1b (green), PG2d (yellow) and PG3a (red). Boxes were calculated from 5 up to 73 replicated experiments per strain (single dots). Boxes associated with different letters represent significantly different means (*p* < 0.05, according to a Kruskal–Wallis's test followed by post hoc Dunn's test). (B) Boxes were calculated from 70 to 97 replicated experiments per temperature (single dots). Boxes associated with different letters represent significantly different means (*p* < 0.05, according to a Kruskal–Wallis's test followed by post hoc Dunn's test).</figcaption></figure>
temperatures. This is another piece of evidence out of the many reported over the past 30 years regarding the role of temperature in virulence regulation in plant-associated bacteria (reviewed in references Smirnova et al. 2001; Velásquez et al. 2018). Our work has presented new examples of relatively warm-temperature dependency for virulence efficiency, consistent with previous findings about gene expression beyond and within the *P. syringae* species complex (Czajkowski et al. 2017; Huot et al. 2017; Krishna et al. 2022; Peñaloza-Vázquez et al. 1997; Wei et al. 2008; Wei et al. 2010). Altogether, these pieces of evidence contradict the long-standing notions that, firstly, 'almost all virulence genes of plant-pathogenic bacteria [...] exhibit increased transcription at temperatures well-below the respective growth optima' (Smirnova et al. 2001) and secondly that 'the increase of bacterial growth in plants at elevated temperature cannot be explained by variations in intrinsic bacterial growth rate or secretion of effector proteins at different temperatures' (Wang et al. 2009). Our findings support a distinctly different perspective, in which temperature dynamically shapes bacterial virulence and plant disease by modulating not only host responses but also pathogen responses, with evidence showing that higher temperatures can enhance T3SS function and bacterial fitness in planta, challenging the assumptions based on optimal growth temperature in the laboratory. This updated perspective aligns with more recent papers (Huot et al. 2017; Tribelli and López 2022; Velásquez et al. 2018).

## 3.2 | Effector Repertoire Contribution in HR Induction

Although *avrB* expression was assessed for all the strains, two of them (J35 *avrB* and MAFF302273 *avrB*) were categorised as non-inducers for at least two of the tested temperatures. The lack of HR induction could result from T3SS inactivation in *A. thaliana*, potentially because of a quick pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) onset (Crabill et al. 2010). On the other hand, it could also be a matter of the speed of ETI onset, whose rapidity prevents cell death occurrence (Künstler et al. 2016). Otherwise, it may be due to the presence in the repertoire of the strain of some suppressive effector(s) (Jamir et al. 2004), or some effector(s) targeting a molecular actor involved in both PTI and ETI, or simply blocking the PTI—required in the first place for ETI activation (Ngou et al. 2021). Although our analysis of effector repertoire composition (PsyTEC; Laflamme et al. 2020) did not allow us to identify one single or group of effectors antagonistic to AvrB, we cannot rule out the occurrence of ‘meta-effector’ interactions (Kubori et al. 2010; Martel et al. 2022). Overall, the in-depth study of the effector repertoires of all the strains used in our work could help to explain the differences observed in terms of HR intensity, with one or more effectors that may inhibit HR but also enhance it conversely—as observed for strain CC1498 *avrB* versus strain CC0094 *avrB*, for example.

## 3.3 | Temperature and Plant Immunity

Using HR induction as a proxy for T3SS efficiency, we implicitly accounted for plant defence mechanisms that play a role in the response (Künstler et al. 2016). In *A. thaliana*, the role of temperature in plant immunity is more complex than reported

by previous studies. In 2009, Wang and colleagues concluded that a mild increase in temperature impaired both PTI and ETI, suggesting a general deficiency in the plant defence system at elevated temperatures (28°C–30°C) (Wang et al. 2009). Subsequently, a straightforward dichotomy was established: less efficient ETI (effective from 10°C to 23°C, with a peak at 18°C) versus more efficient PTI (effective from 23°C to 32°C, with a peak at 28°C) as the temperature increases (Cheng et al. 2013). This model was later validated by the demonstration that, because ETI relies on distinct processes (i.e., virulence suppression and programmed cell death/HR), only HR was inhibited by elevated temperatures as the virulence suppression was maintained (Menna et al. 2015). However, despite their demonstration that ion leakage from *A. thaliana* leaf disks infiltrated with the avirulent DC3000 strain is completely inhibited at 28°C–30°C, our results for this *avrB*-expressing strain and CC0094 *avrB* and CC1498 *avrB* contradict this finding.

Temperature variations may affect the kinetics of effector translocation and/or binding to their targets and hence impact the speed and efficiency of signalling cascades involved in the defence response. Comparison of the time point when half of the final conductivity measured at 24 hpi (hpi$_{50%}$) among temperatures for a given HR-inducer strain revealed that the elevation of the temperature led to an acceleration of electrolyte leakage as temperature increased. As this observation was maintained across the strains that induced HR at different temperatures, it is tempting to associate this general effect of accelerated response with the effect of the higher temperature on the plant, and not on the T3SS activation or efficiency. Nevertheless, across all strains, we demonstrated that some were faster than others to induce HR, also indicating some pathosystem-specific behaviours.

## 3.4 | Temperature and Effector Secretion Properties

Interestingly, a few examples of temperature dependency for T3E secretion have been shown to be 'protein/effector specific'—mentioning some specific secretion properties of AvrB (Van Dijk et al. 1999). Likewise, the two avirulent DC3000 strains with which HR suppression at elevated temperatures was demonstrated carried either the HopZ1a or AvrRpt2 effector (Menna et al. 2015). HopZ1a, AvrRpt2 and AvrB are recognised by the NLRs ZAR1, RPS2 and RPM1, respectively, which are all members of the subgroup of CC-NLRs. The unclear variability of temperature sensitivity across different NLR subgroups (CC-NLRs vs. TIR-NLRs) (Hua 2014; Menna et al. 2015) suggests that sensitivity may not be conserved in all NLRs or CC-NLRs, given their distinct structural and functional properties. In this light, it is reasonable to attribute the differences observed between our work and the one of Menna et al. (2015) to the different 'ligand-receptor' couples used. Echoing the differences in 'protein/effector specific' secretion efficiency, there are likely to be differences in temperature sensitivity for effector recognition by R proteins, providing strong support for our choice to introduce the same effector in all strains to ensure a proper comparison of HR induction dynamics. Overall, we assume that the impact of temperature on T3SS-secretion/ETI/HR-triggering efficiencies can be highly pathosystem specific.
## 3.5 | Virulence Thermoregulation in Relation to Disease Development

Because various virulence factors may be controlled by the same thermoregulation components (Klinkert and Narberhaus 2009; Smirnova et al. 2001), one intriguing question is whether the effect of temperature on virulence factors is consistent (i) for a given strain, and (ii) with temperature conditions at which disease occurrence is generally reported. In other words, do our results correspond to what is known about disease epidemiology under field conditions? For *P. syringae* pv. *phaseolicola*, low-temperature dependency was established for phaseolotoxin production and type VI secretion system (T6SS) regulation, in line with the development of halo blight of bean favoured at temperatures below 25°C (Goss 1940; Nüsse and Fritsche 1989). However, T3SS-related gene expression inhibition has been reported at 18°C (Arvizu-Gómez et al. 2013), and our results indicate that the strain 1448A is thermo-insensitive in its ability to induce HR. Regarding *P. syringae* pv. *actinidiae*, our results confirmed a low-temperature dependency for T3SS efficiency (Puttilli et al. 2022), which is entirely in line with the environmental conditions—in late winter or early spring—under which *P. syringae* pv. *actinidiae* is reported to cause disease or damage in the kiwifruit orchards (Donati et al. 2020; Kim et al. 2017). On the other hand, concerning strains CC0073 and CC0094, isolated from cantaloupe during blight epidemics in southern France in the 1990s, the authors have reported that the climatic conditions that favoured disease outbreak and development were heavy rainfall associated with a mean minimum temperature below 12°C–13°C (under which the physiology of cantaloupe comes to a standstill) in 95% of cases, whereas our results demonstrated a major T3SS efficiency at higher temperatures (Mention et al. 2004; Morris and Pitrat 1998; Riffaud 2002). Finally, strain DC3000 displays a consistent behaviour, exhibiting both unaltered T3SS efficiency and corontatine production in response to temperature, at least within the 18°C–28°C range (Weingart et al. 2004). Its consistency in response to various environmental parameters associated with high reproducibility of data related to it has certainly contributed to making it the model strain it has become. However, this strain was generated in the laboratory as a rifampicin-resistant derivative of the strain DC52, which originated from Guernsey in 1960 (Cuppels 1986; Xin et al. 2018). Therefore, no conclusive connection could be established between its ecology and its virulence behaviour in response to temperature, as this model strain has evolved for many years in laboratories, far from a field context.

Our results also provide evidence that growth optima—at least in vitro—are not correlated with T3SS efficiency. This contributes to the debate about the question of whether the temperature conditions that favour virulence (specifically T3SS) are identical to those reported as favourable for disease development. Answering this question is challenging due to both supporting and opposing examples when accounting for the various traits characterising phytopathogenic bacteria that are thermosensitive, and each pathogen is characterised by growth and virulence mechanisms that are activated at precise temperatures, generating a complex scenario in which temperature can alter the outcome of the interaction between

plant and bacterium by differently influencing a spectrum of virulence traits (Tribelli and López 2022). Consequently, it is likely to be very difficult to simplify or generalise the behaviour of different strains relative to the influence of temperature on their virulence.

## 3.6 | Inter-Strain Variability

We observed that the behaviour of high temperature preference/dependency is exclusive to strains from phylogroup 2d, whereas the opposite case is specific to strains belonging to phylogroups 1a and 1b. This suggests that temperature responsiveness patterns might vary among strains but remain consistent within the same phylogroup. While the temperature sensitivity feature is widely distributed among the strains, the preference/dependency on low or high temperatures in the case of thermosensitivity is conserved within the same phylogroup. Therefore, the preference/dependency on low or high temperatures could be linked to the evolutionary history of pathogens, which may have been shaped by temperature-related selection pressures. Investigating this question would help shed light on the origin of the phenomenon. On the other hand, one important conclusion of our work is the significant variability in behaviour among strains, even when closely related at the genetic level (as illustrated with the 3 'CC' strain-quasiclones). Over the years of research on these issues, examples of such inherent variability in terms of virulence have been largely overlooked, with only a few cases reported in the literature, both beyond and within the *P. syringae* species complex (Baron et al. 2001; Hasegawa et al. 2005; Rohde et al. 1998; Weingart et al. 2004). This might be attributed to the aim of simplifying our understanding of plant-pathogen interactions. However, we emphasise the urgent need to study the diversity among strains, because evidence of their inherent variability has been documented. Although investigating model strains has facilitated the understanding and characterisation of intricate molecular mechanisms in plant-pathogen interactions, it is now imperative to consider the full spectrum of *P. syringae* species complex diversity (Berge et al. 2014; Gomila et al. 2017), both within and outside of the agronomic context.

# 4 | Experimental Procedures

## 4.1 | Bacterial Strains, Culture Conditions and Transformation

Thirteen *P. syringae* strains were selected for this study (Table S1; Supporting Information). Wild-type (WT) *P. syringae* strains were grown at 28°C on King's B agar (KB) (King et al. 1954)—supplemented with rifampicin at 50 µg/mL for DC3000 and B728a strains. Kanamycin at 50 µg/mL was added for the culture of *avrB*-expressing strains. Single colonies of each strain were picked and grown overnight in liquid KB medium, supplemented with rifampicin at 50 µg/mL for DC3000 and B728a strains and with kanamycin at 50 µg/mL for *avrB*-expressing strains, with agitation at 190 rpm at 28°C.

Selected strains were transformed with the pure plasmid carrying the *avrB* gene whose sequence was originally isolated from
the soybean pathogen *P. syringae* pv. *glycinea* (pVB01 Km<sup>R</sup>; Innes et al. 1993) through the electroporation process. Briefly, fresh suspensions of WT strains grown overnight in liquid KB (190 rpm, 28°C) were washed three times and resuspended in 50–100 µL of cold 10% glycerol. Pure plasmid (50–250 ng) was added, and the suspension was transferred into a cold 2 mm electroporation cuvette (Bio-Rad) Electroporation was performed with a MicroPulser machine (Bio-Rad) set at 1.8–2.5 kV. Cells were immediately recovered into fresh non-selective liquid KB medium and incubated at 28°C for 1–2 h at 190 rpm. Transformed strains were selected using kanamycin at 50 µg/mL (plus rifampicin at 50 µg/mL for DC3000 and B728a strains) and the presence of the plasmid was confirmed by colony PCR using Promega GoTaq DNA polymerase (Fisher Scientific) and specific primers (FOR: 5'-ATGGGCTGCGTCTCGTCAAAAAAG CA-3', REV: 5'-TTAAAAGCAATCAGAATCTAGCAAG-3', annealing temperature 65°C).

## 4.2 | *avrB* Expression Control

Relative expression levels of *avrB* in transformed strains were evaluated by reverse transcription-quantitative real-time PCR. Four millilitres of fresh suspension of *avrB*-transformed *P. syringae* strains grown overnight in selective medium was centrifuged (5 min at 4500 g at room temperature) and total RNA was extracted from pellets using TRIzol substitute (EuroGold TriFast Kit, EuroClone) according to the manufacturer's instructions. Extraction yield and quality of the transcripts were checked by spectrophotometry (NanoDrop, Thermo Fisher Scientific). Samples with absorbance ratios A<sub>260nm</sub>/A<sub>230nm</sub> and/or A<sub>260nm</sub>/A<sub>280nm</sub> outside the range of [2 ± 0.5] were subjected to a lithium chloride treatment to increase their purity (2.5 M LiCl, 50 mM EDTA, pH 8.0). One to two micrograms of RNA per sample underwent DNase treatment (TURBO DNase, Life Technologies) then the single-stranded complementary DNA synthesis was performed from 0.5 to 1 µg of template RNA using SuperScript III reverse transcriptase (Invitrogen) according to the manufacturer's instructions. Samples were 10-fold diluted and the real-time PCR was performed using Luna Universal qPCR Master Mix (New England Biolabs). To normalise the expression of the target gene, *rpoD* was chosen as a stable and robust housekeeping gene in *Pseudomonas* (Savli et al. 2003). Amplification was run on a QuantStudio 3 real-time PCR system (Applied Biosystems) (primers *avrB* FOR: 5'-ATACTCTGCATTCGCCTCCG-3', REV: 5'-TCAAC GACTCTGGCAAGGAC-3'; primers *rpoD* FOR: 5'-AAC TTGCGTCTGGTGATCTC-3', REV: 5'-ATCAAGCCGATGT TGCCTTC-3'). Expression of *avrB* was determined using the 2<sup>-ΔΔCt</sup> method and normalised against *rpoD*, and fold-change for each strain was established relative to the strain DC3000 *avrB*.

## 4.3 | Ion-Leakage Experiments

HR induction was assessed by quantifying programmed cell death through ion-leakage measurement, as previously published (in *A. thaliana* Col-0; Imanifard et al. 2018; Johansson et al. 2015; in *A. arguta* 'Kens Red': Jayaraman et al. 2021) with slight modifications provided as Supporting Information.

## 4.4 | Statistical Analysis

For each technical replicate, the conductivity value from the first measure was subtracted from the values measured at each successive time point for normalisation (Puttilli et al. 2022). For each strain-temperature modality within each replicated experiment, conductivity was calculated as the average of the values of the three technical replicates for each time point, and ion-leakage curves over time were established accordingly. AUCPC was calculated, as well as variance and mean AUCPC per modality. Conductivity values corresponding to 24 hpi as well as the time point for which half of this value was reached for each experiment were calculated via linear interpolation, and this variable hpi<sub>50%</sub> was used as a dynamic parameter, indicating how fast a given strain induced HR at a given temperature. Comparison of strains based on this parameter was assessed by variance analysis (Kruskal-Wallis's test) followed by a post hoc Dunn's test. The same procedure was conducted to compare the three different temperatures regardless of the strain. Data were represented by boxplots.

Each single conductivity progress curve constituted from six to nine time points and was considered as one statistical individual (i.e., one iteration) to fit LMMs. Details of the approach are provided as Supporting Information.

## 4.5 | In Vitro HrpZ Secretion

Twenty millilitres of fresh suspension of *avrB*-expressing *P. syringae* strains grown overnight in selective medium were centrifuged (5 min at 4500 g at room temperature) and pellets were washed three times in 10 mL of sterile minimal medium (HIM). OD<sub>600</sub> was measured with a spectrophotometer (Evolution, ThermoFisher Scientific) and bacterial cells were resuspended in sterile HIM to 7 × 10<sup>8</sup> CFU/mL (OD<sub>600nm</sub>=0.7; final volume=150 mL). Suspensions were divided into three portions of 50 mL; each was separately incubated at 18°C, 24°C or 28°C with agitation at 190 rpm. After 5 and 24 h of incubation, 25 mL of each bacterial suspension were sampled and OD<sub>600</sub> was measured again. Cell-free culture supernatant was obtained by centrifugation and filtration, and secreted proteins were precipitated with 5% trichloroacetic acid (TCA) as previously described (Flaugnatti and Journet 2017; Kobayashi et al. 1997).

For immunoblotting, proteins were separated on SDS-polyacrylamide gel electrophoresis and then transferred onto a nitrocellulose blotting membrane (GE HealthCare) using an electrophoretic apparatus. Protein detection was performed using anti-HrpZ (1:5000) (Alfano et al. 1996) and anti-rabbit (1:10000) conjugated with horseradish peroxidase as a secondary antibody. To confirm the correct loading ratio among wells, one gel was stained with a Coomassie R-250 staining solution (25% isopropyl alcohol, 10% acetic acid, 0.05% Coomassie R-250) and destained with 10% acetic acid.

## 4.6 | In Vitro Growth Measurement

Four millilitres of fresh suspension of *avrB*-expressing *P. syringae* strains grown overnight in selective medium was centrifuged
(5 min at 4500 g at room temperature) and pellets were washed three times in 1 mL of fresh liquid KB. Optical density at 600 nm was measured by spectrophotometer (Evolution, ThermoFisher Scientific) and bacterial cells were then resuspended to reach $2 \times 10^7$ CFU/mL ($OD_{600nm}$=0.02; final volume=2 mL). Suspensions were aliquoted in a micro titre plate (200 µL per well), with six technical replicates per strain, and plates were incubated at 18°C, 24°C and 28°C. Liquid KB (supplemented or not with the antibiotics) was used as a negative control. Optical density at 600 nm was measured every 1.5–2 h during the first 8 h of the experiment, and then two or three times between 18 and 24 hpi, obtaining from 6 to 9 optical density measures per well. To eliminate unspecific signals due to the colour of KB medium and the antibiotics, the value from the first measure was subtracted from values measured at each successive time point. Optical density was then calculated as the average of the values of the six technical replicates for each time point, and bacterial growth curves over time were established accordingly. Each strain–temperature modality was reproduced at least twice, except for T1.

## Author Contributions

E.V. designed research; E.C., D.D., and V.M.T. performed research; E.C., M.P. and E.V. analysed data; and E.C., C.E.M., and E.V. wrote the paper.

## Acknowledgements

We thank Prof. Boris A. Vinatzer, Dr. Perrine Portier and Dr. Marco Scortichini for kindly providing the *P. syringae* strains used in this study in addition to our strains. We also thank Prof. Sheng-Yang He for providing the antibody anti-HrpZ. Special thanks to Prof. Roberto Chignola and Dr. Davide Martinetti for their help in statistical analyses of ion-leakage data. We also thank the members of the Biotechnology Department of the University of Verona who provided technical support in conductivity measurements. We thank the EUR IMPLANTEUS program (ANR-18-EURE-0009) for funding supporting E. Vandelle collaboration with INRAE for this work.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supporting Information. Additional data related to this paper may be requested from the authors.

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## Supporting Information

Additional supporting information can be found online in the Supporting Information section. **Figure S1:** Variance of the mean area under conductivity progress curve (AUCPC) values obtained for each 39 modalities avrB-expressing strain × temperature. Conductivity was measured over time in *Arabidopsis thaliana* Col-0 leaf disks infiltrated with the different strains under different temperature conditions. Number of replicated experiments for each strain varied from 3 up to 27. Linear regression trend curve was fitted to the data, with $y=323.89x-150932$ and $R^2=0.8588$, showing a positive correlation between mean AUCPC and their variance (Spearman's coefficient = 0.91; $p<0.05$). **Figure S2:** avrB expression among the mutant strains. RNA was extracted from bacterial suspensions grown for 5 h at 24°C in liquid hrp-inducing medium (HIM). (a) Real-time PCR was performed using rpoD as the housekeeping gene. Expression levels were established using the mean normalised expression (MNE). Error bars represent standard error. Data represent the mean of three independent
biological replicates. (b) Scatterplot of hpi 50% versus avrB expression (MNE) showing the absence of correlation between the two variables according to the Pearson correlation. **Figure S3:** In vitro growth curves for DC3000 avrB (a), USA007 avrB (b) and CC0094 avrB (c). Bacterial growth was measured for 24h at 18°C (blue), 24°C (pink) and 28°C (red). Overnight grown bacteria were resuspended in liquid KB medium supplemented with kanamycin (50 µg/mL) and rifampicin (50 µg/mL, for DC3000 avrB only) at an initial load of 107 CFU/mL (optical density measured at 600 nm = 0.01). Data represent one single representative biological replicate with all strains and temperature conditions evaluated simultaneously with six technical replicates each. Error bars represent standard error. **Figure S4:** Electrolyte leakage curves over time obtained post-infiltration for CC0094 in *A. thaliana* Col 0 (a) and CRA-FRU 8.43 in *Actinidia arguta* (b). Infiltrated leaf disks were incubated at 18°C (blue) and 28°C (red). Conductivity following infiltration of the mock treatment (10 mM MgCl₂) and incubation at 18°C is represented by the black dotted line. Data represent one single representative biological replicate with all strains and temperature conditions evaluated simultaneously with three technical replicates each. Error bars represent standard error. **Data S1:** mpp70170-sup-0005-Supplementary Methods. pdf. **Table S1:** Set of selected *P. syringae* strains. **Table S2:** Matrix of effectors found among the *P. syringae* strains. Effector repertoires of all strains used in this study were already available publicly, with the exception of CC0073, CC1498 and LAB0041 whose repertoires were characterised following the same procedure, as described (Laflamme et al. 2020). **Table S3:** Known interaction outcomes of *P. syringae* WT and avrB-expressing strains in *Arabidopsis thaliana* Col-0.