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\begin{document}

\title{Pattern and causes of the establishment of the invasive bacterial potato
pathogen \emph{Dickeya solani} and of the maintenance of the resident
pathogen \emph{D. dianthicola}}



\author[1]{Pauline  Blin}%
\author[2]{Kévin Robic}%
\author[1]{Slimane Khayi}%
\author[2]{Jérémy Cigna}%
\author[2]{Euphrasie Munier}%
\author[2]{Pauline Dewaegeneire}%
\author[2]{Angélique Laurent}%
\author[1]{Yan Jaszczyszyn}%
\author[3]{Kar-Wai  Hong}%
\author[3]{Kok-Gan Chan}%
\author[4]{Amélie Beury}%
\author[5]{sylvie Reverchon-Pescheux}%
\author[6]{Tatiana Giraud}%
\author[4]{Valérie Hélias}%
\author[1]{Denis Faure}%
\affil[1]{CNRS}%
\affil[2]{French Federation of Seed Potato Growers}%
\affil[3]{Jiangsu University}%
\affil[4]{French Federation of Seed Potato Growers }%
\affil[5]{INSA Lyon}%
\affil[6]{Université Paris-Sud}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\selectlanguage{english}
\begin{abstract}
Invasive pathogens can be a threat when they affect human health, food
production or ecosystem services, by displacing resident species, and we
need to understand the cause of their establishment. We studied the
patterns and causes of the establishment of the pathogen Dickeya solani
that recently invaded potato agrosystems in Europe by assessing its
invasion dynamics and its competitive ability against the
closely-related resident D. dianthicola species. Epidemiological records
over one decade in France revealed the establishment of D. solani and
the maintenance of the resident D. dianthicola in potato fields
exhibiting blackleg symptoms. Using experimentations, we showed that D.
dianthicola caused a higher symptom incidence on aerial parts of potato
plants than D. solani, while D. solani was more aggressive on tubers
(i.e. with more severe symptoms). In co-infection assays, D. dianthicola
outcompeted D. solani in aerial parts, while the two species co-existed
in tubers. A comparison of 76 D. solani genomes (56 of which having been
sequenced here) revealed balanced frequencies of two previously
uncharacterized alleles, VfmBPro and VfmBSer, at the vfmB virulence
gene. Experimental inoculations showed that the VfmBSer population was
more aggressive on tubers while the VfmBPro population outcompeted the
VfmBSer population in stem lesions, suggesting an important role of the
vfmB virulence gene in the ecology of the pathogens. This study thus
brings novel insights allowing a better understanding of the pattern and
causes of the D.solani invasion into potato production agrosystems, and
the reasons why the endemic D.dianthicola nevertheless persisted.%
\end{abstract}%



\sloppy


\textbf{KEYWORDS}

competitive exclusion; \emph{Dickeya;} invasion; plant pathogens;
population genomics; quorum-sensing.



\textbf{1 Introduction}

Biological invasions represent major threats to biodiversity as invasive
species can replace native species. Evolutionary and ecological studies
are of major importance for understanding the patterns and causes of
biological invasions and plant and animal invasions have been
extensively studied since the 19\textsuperscript{th} century (Burns,
Murphy, \& Zheng, 2018; Cadotte, Campbell, Li, Sodhi, \& Mandrak, 2018;
MacDougall, Gilbert, \& Levine, 2009). Evolutionary and ecological
approaches aim at elucidating the dynamics of invasions as well as the
advantages of invaders that allow them to outcompete resident species
(Facon et al., 2006; Gladieux et al., 2015). Although microbial
invasions can represent important threats to ecosystems and human
societies, they have been much less studied than invasive plants and
animals (Gladieux et al., 2015; Kinnunen \emph{et al} ., 2016; Litchman,
2010; Mallon, Elsas, \& Salles, 2015; Perkins, Leger, \& Nowak, 2011).

In this work, we used evolutionary and ecological approaches for
understanding the patterns and causes of the establishment of the
bacterial pathogen \emph{Dickeya solani} in potato agrosystems and the
maintenance of the resident, related competitor \emph{D.~dianthicola} .
There are two major clades of potato bacterial pathogens in
Europe,\emph{Pectobacterium} and \emph{Dickeya,} two sister genera among
the order of Enterobacterales (Gamma-proteobacteria). While
some\emph{Pectobacterium} species had settled since before the 1970s in
potato agrosystems in Europe (P\selectlanguage{ngerman}érombelon, 2002), \emph{Dickeya} species
invaded later, in two successive waves. Mostly isolated from ornamental
plants such as \emph{Dianthus, Dahlia} and \emph{Begonia} , \emph{D.
dianthicola} has been reported in Europe as early as the 1950s.
Isolation of \emph{D. dianthicola} from \emph{Solanum tuberosum} dates
back to the 70's (Toth et al., 2011; Parkinson et al., 2009).
Nowadays,\emph{D.~dianthicola} is considered an endemic pathogen of
potato plants in Europe. It is present in all continents, including
North-America, where it was associated with disease outbreaks in potato
farms in 2015 (Oulghazi et al., 2017; Patel, Baldwin, Patel, Kobayashi,
\& Wyenandt, 2019; Sarfraz et al., 2018; Toth et al\emph{.} , 2011;
Wright et al., 2018).

\emph{Dickeya solani} has emerged in potato production systems in Europe
much more recently, in the early 2000s (Toth et al., 2011; van der Wolf
et al., 2014). Aside from potatoes, \emph{D. solani} has been isolated
from ornamental plants such as \emph{Hyacinthus} , \emph{Iris}
and\emph{Muscari} , but the primary host(s) of that species remain(s)
uncertain (Chen, Zhang, \& Chen, 2015; Slawiak et al., 2009; van der
Wolf et al., 2014). Population genomics revealed little genetic
variation in \emph{D. solani} , in agreement with a recent spread of
this species following a bottleneck during invasion (Golanowska et al.,
2018; Khayi et al., 2015). An analysis of 20 \emph{D. solani} genomes
identified a non-synonymous single nucleotide polymorphism (SNP) in each
of the two \emph{fliC} and \emph{fliN} genes that are involved in
bacterial motility (Khayi et al., 2015). Horizontal gene transfer events
from \emph{D.~dianthicola} to \emph{D. solani} have been documented,
adding or replacing genomic fragments (Khayi et al., 2015).

The \emph{D. solani} invader, as well as the \emph{D. dianthicola}
and\emph{Pectobacterium} spp. residents, are necrotrophic pathogens
causing similar symptoms, resulting in blackleg disease on stems and
soft-rot disease of tubers (Charkowski 2018; Toth et al., 2011). All
these bacteria secrete plant cell-wall macerating enzymes (including the
pectate lyases) and proliferate by assimilating the plant cell remains,
including iron by producing the chrysobactin and achromobactin
siderophores. Pectate lyases, i.e., PelA, PelD and especially PelE, play
a key role in the initiation of the plant cell wall maceration. Using
pectin as a substrate, these enzymes release oligosaccharides that
elicit expression of other plant-cell wall macerating enzymes in a
positive feedback loop (Duprey, Nasser, Léonard, Brochier-Armanet, \&
Reverchon, 2016). Noticeably, the \emph{pelA} gene is truncated, hence
non-functional, in \emph{D.~dianthicola} (Duprey et al., 2016; Raoul des
Essarts et al., 2019). The secretion of these virulence factors is a
costly process that is tightly regulated, being induced by the
perception of chemicals that inform the pathogen on plant host
physiology (mainly plant sugars) and on the size of its own population
(quorum-sensing signals) (Leonard, Hommais, Nasser, \& Reverchon,
2017).\emph{Dickeya} pathogens synthetize and sense two types of
quorum-sensing signals, the N-acylhomoserine lactones and Vfm compounds,
which activate virulence gene expression when a threshold concentration
of signals (reflecting the number of cells in the environment) is
reached (Crépin et al., 2012; Nasser et al., 2013; Potrykus, Golanowska,
Hugouvieux-Cotte-Pattat, \& Lojkowska, 2014; Potrykus, ,
Hugouvieux-Cotte-Pattat, \& Lojkowska, 2018). By modulating the
synthesis of virulence factors, the quorum-sensing signals participate
in the transition from an oligotroph lifestyle in soils and surface
waters, where \emph{Dickeya} and \emph{Pectobacterium} bacteria are
rare, to a copiotroph lifestyle on a plant host, where they increase in
number by several orders of magnitude (Laurila et al., 2008; Potrykus et
al., 2016). Functional differences such as metabolic capacities have
been identified between \emph{D.~solani} and \emph{D. dianthicola} by
comparative genomics, transcriptomics and biochemical approaches
(Bellieny-Rabelo et al., 2019; Raoul des Essarts et al., 2019), but
fitness differences within host plants remain only partially
investigated (Czajkowski et al., 2013; Czajkowski, de Boer, Velvis, \&
van der Wolf, 2010; Raoul des Essarts et al., 2019; Shyntum et al.,
2019). Whether the potato host could be differentially exploited
by\emph{D. dianthicola} and \emph{D. solani} and whether the two
pathogens stably coexist by using different ecological niches or compete
directly when exploiting this host remain unsolved questions, despite
their importance for understanding the \emph{D. solani} invasion.

Here, we combined epidemiological records in potato fields, experimental
inoculations and population genomics to contribute to our understanding
of the patterns and ecological determinants of \emph{D. solani}invasion.
Epidemiological records over one decade in France allowed to compare the
relative abundances of the \emph{D. solani} invader, the\emph{D.
dianthicola} resident and \emph{Pectobacterium} \emph{spp} . Using
experimental populations and plant assays in greenhouse, with a
diversity of strains and of ecological conditions, we then focused
on\emph{D. solani} and \emph{D. dianthicola} to determine the ecological
traits that could facilitate or constrain \emph{D. solani}establishment,
including competition or ecological niche differences between the two
\emph{Dickeya} species. Finally, we obtained the genomes of 56 \emph{D.
solani} isolates that we analyzed together with 20 genomes previously
published (Khayi et al., 2015), revealing novel variations in \emph{D.
solani} population. We focused on the quorum-sensing gene \emph{vfmB} to
investigate whether its variation, which has not been studied so far,
could be associated to invasion traits in \emph{D. solani} .

\textbf{2 Material and Methods}

\textbf{2.1 Pathogen sampling and identification in potato fields with
blackleg disease symptoms}

Pectinolytic bacteria were isolated from symptomatic plant tissues on
crystal violet pectate medium (Hélias, Hamon, Huchet, Wolf, \& Andrivon,
2012). Isolates were purified on agar plates and characterized at the
genus (\emph{Dickeya} and \emph{Pectobacterium} ) and species (\emph{D.
solani} and \emph{D. dianthicola} ) levels using the PCR primers listed
in \textbf{Table S1} . Two sampling strategies were used. From 2004 to
2015, a national inventory was conducted in French potato producing
areas. Each year (with the exception of the year 2006), fields
exhibiting blackleg symptoms were randomly sampled by collecting
diseased plants from which isolates were recovered and characterized.
From 541 fields, around 1600 isolates were collected and taxonomically
characterized. In parallel, from 2013 to 2016, 19 of the potato fields
exhibiting more than 1\% of blackleg incidence were deeply sampled.
Around 30 plants with blackleg symptoms were collected along a transect
in each field, and a single isolate was retained from each of the 548
plants. The resulting 548 isolates were characterized taxonomically.

\textbf{2.2 \emph{Dickeya solani} and \emph{D. dianthicola} strains used
in plant assays}

Five \emph{D.~dianthicola} strains (RNS11-47-1-1A, CFBP1888, CFBP2982,
CFBP2015, MIE34) and five \emph{D. solani} strains (3337 =
RNS08-23-3-1A, IPO2222, RNS05-1-2A, Ds0432.1, PPO9019) were used to
produce plant inoculation assays. The strains were chosen to be
representative of the diversity of the populations, i.e. from different
geographical locations, isolation years or host of collection (potato
plants \emph{vs} ornamentals, \textbf{Table S2} ), and regarding
phylogeny placement with neutral markers (\textbf{Figure S1} ).
Phylogeny analyses were conducted using MEGA7 (Kumar, Stecher, \&
Tamura, 2016). Bacterial strains were stored at -80°C in glycerol (25\%
vol/vol). They were cultivated in TY medium (tryptone 5
g.L\textsuperscript{-1}; yeast extract 3 g.L\textsuperscript{-1}) with
or without agar (15 g.L\textsuperscript{-1}) at 28°C.

\textbf{2.3 Plant and tuber inoculations by \emph{D. solani} and\emph{D.
dianthicola} strains and experimental populations}

In our plant and tuber assays, we use the term virulence as the capacity
of the pathogen to parasitize a host (symptom incidence) and the term
aggressiveness as the degree of damage caused by a pathogen on a host
(symptom or disease severity). The terms used to describe pathogens
behaviors (virulence, symptom incidence, aggressiveness, disease
severity index, fitness and competitive index) are defined more
extensively in \textbf{Supplementary Methods 1 (SM1)} . We designed the
whole plant experiments based on our knowledge of the pathosystem, to
investigate contrasting conditions relevant for the disease expression
in fields. Each bacterial strain was cultivated individually before
being used for plant and tuber inoculations, either separately or
assembled in populations. To constitute experimental populations
of\emph{D.~solani,} \emph{D. dianthicola,} or mixtures of the two
species, cell suspensions of different strains were assembled just
before plant inoculation. Potato plants (\emph{S. tuberosum} var.
Bintje) and hyacinths (\emph{Hyacinthus orientalis} var. Delft blue)
were cultivated in horticultural compost in individual pots (2 L) in a
greenhouse at around 23°C (minimum 20°C maximum 28°C) with a 12-hour
photoperiod. For mimicking plant infection by soil pathogens, potato
plants (three weeks post-tuber plantation) and hyacinths (four weeks
post-bulb plantation) were inoculated by watering the substrate with a
pathogen cell suspension at 10\textsuperscript{9} colony-forming units
(CFU) per pot. This inoculation load was calibrated to obtain a large
range (20 to 60\%) of symptom incidence in the unwounded potato plant
condition (Raoul des Essarts et al., 2015). In a wounded condition, the
potato roots were wounded with a sterile knife before infection. The
symptom monitoring was adapted from Raoul des Essarts et al. (2015). The
number of symptomatic potato plants (blackleg disease) and hyacinths
(soft-rot disease) was recorded twice a week (see examples of symptoms
in\textbf{Figure 1a-b} ). For each strain and experimental population
and unwounded and wounded conditions, the number of symptomatic and
asymptomatic plants (hence two symptom classes that were used in
statistical comparisons) was counted at 61 days post infection (dpi)
using 15 potato plants (up to 25 potato plants when indicated) and 8
hyacinths. A set of non-inoculated plants was used as an asymptomatic
control. In order to facilitate visualization of the virulence data in
the figures, they are presented as a percentage of symptomatic plants
(symptom incidence).

In tuber assays, potato tubers (\emph{S. tuberosum} var Bintje) were
inoculated using a tip to inject 10 \selectlanguage{greek}µ\selectlanguage{english}L of calibrated pathogen
suspensions. Based on previous results (Raoul des Essarts et al., 2019),
we chose two different inoculum loads of strains and experimental
populations (10\textsuperscript{7} CFU and 10\textsuperscript{5} CFU per
tuber) to obtain a large range of symptom severity, to compare the
capacity to initiate maceration at different population sizes, to
investigate fitness of the two pathogens in two contrasting ecological
conditions. After 5 days of incubation at 24\selectlanguage{ngerman}°C, the tubers were cut in
half and scored based on five aggressiveness classes according to the
symptom severity in each tuber (from no symptom to the most severe
symptoms; \textbf{Figure 1c} ). For each strain and experimental
population, at least 10 tubers were inoculated. A set of non-inoculated
tubers was used as an asymptomatic control. In order to facilitate the
presentation of the aggressiveness data in the figures, results are
presented as normalized disease severity index (DSI) of which values,
ranging from 0 to 100 (arbitrary unit), increase with symptom severity.
DSI was calculated using the five aggressiveness classes assigned to 10
tubers, see formula in \textbf{Supplementary Methods 1 (SM1).}

Emerging lesions from potato stems and hyacinths and rotting tissue
recovered from tubers at 5 dpi were collected and frozen at -80°C, and
then used to quantify the abundance \emph{D. solani} and \emph{D.
dianthicola} pathogens within hosts by Taq Man qPCR as described
in\textbf{Supplementary Methods 2 (SM2)} . Assessing
\emph{D.~dianthicola}and \emph{D. solani} in inoculum and plant tissues
(potato stems and tubers, and hyacinths) permitted the calculation of
competitive index (CI) values following the formula presented in
\textbf{SM1} . A CI value equal to one indicated an equal fitness
between \emph{D. solani} and\emph{D. dianthicola} , CI value greater
than one indicated a fitness advantage to \emph{D. solani} , and CI
value below one indicated a fitness advantage to \emph{D. dianthicola} .

\textbf{2.4 \emph{Dickeya solani} population genomics}

Total DNA was purified from each of 56 \emph{D. solani} isolates (their
characteristics in \textbf{Figure S2} ) using MasterPure complete DNA
and RNA purification kit (Epicentre, Illumina). After quantity and
quality controls of extracted DNA using a NanoDrop (ND 1000) device and
agarose gel electrophoresis at 1.0 \% (w/v), paired-end libraries were
constructed for each strain and then sequenced using High Output
Sequencing kit with 75 × 2 cycles on and Illumina NextSeq500 sequencer
(CNRS, Gif-sur-Yvette, France). For each strain, 2.4 to 18 million reads
were obtained, corresponding to an average coverage ranging from 37× to
270×. Paired-end reads were trimmed (quality score threshold 0.05) and
mapped against the \emph{D. solani} reference genome, from the 3337
strain, at mild stringency threshold (80\% identity on 50\% read length)
using CLC Genomics Workbench version 10.1.3 (Khayi \emph{et al.} 2015).
The mapping was used for the detection of SNPs and InDels using the
variant calling tool from CLC genomic workbench version 10.1.3. Only
SNPs and InDels (1 to 9 nucleotides) with a high occurrence (\selectlanguage{english}[?] 99 \% of
the reads) in the mapping step were retained. The representation of
allelic variants in \emph{D. solani} population was performed using
PHYLOViZ (Francisco et al., 2012).

\textbf{2.5 Characterization of the fitness differences
between\emph{Dickeya solani} strains carrying the
VfmB\textsubscript{Ser} and VfmB\textsubscript{Pro} alleles}

The structure of the VfmB proteins was modeled and represented using the
Phyr2 and EzMol web portals (Kelley, Mezulis, Yates, Wass, \& Sternberg,
2015; Reynolds, Islam, Sternberg, 2018). Given the known role in
virulence of the \emph{vfm} gene cluster (Nasser et al., 2013), we
assessed virulence differences between \emph{D. solani} strains
exhibiting either a serine (allele VfmB\textsubscript{Ser}) or a proline
(allele VfmB\textsubscript{Pro}) at the position 55 of the VfmB protein.
Using genomic data, we chose four isolates carrying
VfmB\textsubscript{Pro} (IPO2222, MIE35, AM3a and 3337) and four
isolates carrying VfmB\textsubscript{Ser} (Ds0432.1, RNS10-27-2A, Sp1a
and M21a), the four isolates in each group differing at other positions
in genomes (their characteristics in \textbf{Tables S3} and\textbf{S4}
). Plant inoculation assays (on potato tubers and stems) were performed
following the same protocols as described above using pure strains and
mixtures as inocula. In the figures, virulence was presented as the
percentage of symptomatic plants (in potato stem infections assay) and
aggressiveness by DSI values (in potato tuber infection assays).

To measure their relative fitness, co-inoculation assays were also
performed with VfmB\textsubscript{Ser} and
VfmB\textsubscript{Pro}experimental populations, and their relative
abundance was quantified by shot gun sequencing of DNA extracted from
inoculum and from lesions. From 12 to 28 million reads were obtained for
each sample, corresponding to an average coverage of \emph{D. solani}
genomes ranging from 180x to 420x. Sequencing (75 x 2 cycles) was
performed using an Illumina NextSeq500 at the I2BC platform (CNRS,
Gif-sur-Yvette, France) and Illumina MiSeq platform (University of
Malaya, Kuala Lumpur, Malaysia). The trimmed reads were mapped on
\emph{D. solani} \emph{vfmB} gene for quantifying the relative abundance
of the two VfmB\textsubscript{Ser}and VfmB\textsubscript{Pro} alleles in
each sample using the CLC genomic workbench version 10.1.3. The relative
abundances of the alleles permitted calculation of CI values of the
VfmB\textsubscript{Ser} and VfmB\textsubscript{Pro} populations (see
\textbf{SM1} ). A CI value equal to one indicated an equal fitness
between \emph{D. solani}VfmB\textsubscript{Pro} \emph{and}
VfmB\textsubscript{Ser} populations, CI value greater than one indicated
a fitness advantage to VfmB\textsubscript{Pro}, and CI value less than
one indicated a fitness advantage to VfmB\textsubscript{Ser}. Finally,
we used transcriptomics to identity the genes that were differentially
expressed between IPO2222 (VfmB\textsubscript{Pro}) and Ds0432.1
(VfmB\textsubscript{Ser})\emph{D. solani} strains when they grew inside
potato tubers (\textbf{SM2)} . Transcriptomes were compared as described
by Raoul des Essarts et al. (2019).

\textbf{2.6 Statistical analyses}

The slopes of the dynamics of the percentages of \emph{Dickeya}
-,\emph{Pectobacterium} -, \emph{D. solani} - and \emph{D. dianthicola}
-positive fields were analyzed using F-tests and ANCOVAs using GraphPad
Prism version 8.4.2 for MacOS, GraphPad Software (www.graphpad.com). A
Chi-squared method was used to test the non-random distribution of taxa
in each field.

In all the plant assays, the non-inoculated plants and tubers remained
asymptomatic, and this control condition was not considered in
statistical analyses. The two symptom levels (with or without symptoms)
of potato plants and hyacinths virulence assays, the five symptom
classes in tuber aggressiveness assays, and gene expression levels were
compared among treatments (the different pathogens) by Kruskal-Wallis
tests (\selectlanguage{greek}α \selectlanguage{english}= 0.05) because the data significantly deviated from normality.
Then, post-hoc Tukey tests were run to assess what pairwise differences
were significant. When the bacterial strains were inoculated separately
on plants and tubers, we compared the \emph{D. solani} and \emph{D.
dianthicola} species traits using each bacterial strain as a replicate
of the considered species. When the bacterial strains were inoculated
altogether to constitute an experimental population, we compared
the\emph{D. solani} and \emph{D. dianthicola} species traits using at
least two independent replicates of the experiments.

In competition assays, the hypothesis of balanced abundances of the two
competitors was tested by comparing the calculated CI values to one
using a Kruskal-Wallis test. Analyses were carried out with the software
R (http://www.R-project.org) using the packages RcmdR and nparcomp.

\textbf{3 Results}

\textbf{3.1 Little co-occurrence of \emph{D. dianthicola} and \emph{D.
solani} in potato fields}

A monitoring of the \emph{Pectobacterium} and \emph{Dickeya} populations
was performed over one decade (2004-2015) in France. Annual surveys were
conducted in 541 different potato fields, all exhibiting symptomatic
plants. The samplings resulted in the collection of over 1,600 isolates
that were characterized taxonomically. Each year, we recorded the number
of fields from which we isolated each taxon. These data informed on the
dynamics of the different pathogen populations. Over the
period,\emph{Dickeya} was detected in 10\% to 35\% of the sampled fields
(\textbf{Figure 2a} ). A moderate increase of the percentage
of\emph{Dickeya} -positive fields was observed over time (F= 5.05; DFn=
1; DFd= 9; p= 0.05; R\selectlanguage{ngerman}² = 0.36). Although decreasing in incidence, the
resident \emph{Pectobacterium} species remained the most widespread. As
expected, the slopes of the dynamics of the percentage of\emph{Dickeya-}
and \emph{Pectobacterium-} positive fields diverged (F= 10.11; DFn= 1;
DFd= 18; p= 5 x 10\textsuperscript{-3}). Among the\emph{Dickeya}
isolates, only two species were identified, \emph{D. dianthicola} and
\emph{D.~solani} (\textbf{Figure 2b} ). The slopes of\emph{D.
dianthicola} -positive (F= 1.35; DFn= 1; DFd= 9; p= 0.28) and\emph{D.
solani} -positive (F= 3.10; DFn=1; DFd= 9; p= 0.11) field percentages
were not different from base line and were not different from each other
(F= 0.26; DFn = 1; DFd = 18; p= 0.62). This suggests that the
\emph{D.~solani} invasion did not occur at the expense of\emph{D.
dianthicola} in French potato agrosystems.

Aside from this national survey, we zoomed at the field level using a
more extensive sampling strategy over a four-year period (2013-2016).
Along a transect in each of 19 sampled fields, we collected ca. 30
plants with blackleg symptoms and a single isolate was characterized
from aerial symptoms of each plant, resulting in the sampling of 548
isolates (\textbf{Figure 2c} ). The \emph{Pectobacterium} populations
were present in all the 19 sampled fields. In each of the 19 fields, the
null hypothesis that \emph{Pectobacterium} and \emph{Dickeya} were
randomly distributed was rejected (Chi-squared test: DF= 1; p\textless{}
0.05), meaning that \emph{Pectobacterium} and \emph{Dickeya} co-occurred
less often than expected under random distribution. The hypothesis
that\emph{D. solani and D. dianthicola} were randomly distributed along
the transect was also rejected in each of the 16 \emph{Dickeya-}
positive fields (Chi-squared tests: DF= 1; p\textless{} 0.05) but one
(field \#13; DF= 1; p= 0.24). These field data showed a clustering of
taxa at the field levels, both for genera (\emph{Dickeya}
and\emph{Pectobacterium} ) and species (\emph{D. solani} and \emph{D.
dianthicola} ). This bias in the symptomatic plants can result from a
non-random distribution of the taxa among populations in tuber seeds
or/and soils and surface waters before plant infection, or from
competitive exclusion during the infection process of potato plants and
tubers. In the following, we focused on the two species \emph{D.
solani}and \emph{D. dianthicola} to compare experimentally their fitness
in the course of plant and tuber infection, and in particular to test
the hypothesis of competitive exclusion.

\textbf{3.2 \emph{Dickeya dianthicola} exhibited a fitness advantage
over \emph{D. solani} in potato plants.}

Plant assays were performed in the greenhouse to compare the incidence
of blackleg symptoms after inoculation by \emph{D. dianthicola}
or\emph{D. solani} on non-wounded potato plants.
Five\emph{D.~dianthicola} strains (RNS11-47-1-1A, CFBP1888, CFBP2982,
CFBP2015, MIE34) and five \emph{D. solani} strains (3337 =
RNS08-23-3-1A, IPO2222, RNS05-1-2A, Ds0432.1, PPO9019) were used in
these assays.

In a first assay, each strain was inoculated individually on 15 plants
and the number of asymptomatic and symptomatic plants were counted at 61
days post inoculation (dpi). A Kruskal-Wallis test revealed differences
between \emph{D. solani} and \emph{D. dianthicola} in terms of symptom
incidence (k=7; DF=1; p=8 x 10\textsuperscript{-3}): \emph{D.
dianthicola} was found more virulent than \emph{D. solani} (percentages
of symptomatic plants of 61\% ± 10 versus 15\% ± 11; \textbf{Figure
3a).}

In a second plant assay, the five bacterial cultures (i.e., the five
strains) of each species were assembled to constitute two experimental
populations and each was inoculated on 15 plants. A mix of the two
species (10 strains) was also inoculated on 15 plants. The assay was
duplicated (2 x 15 plants per treatment). We compared symptom incidence
at 61 dpi. Kruskal-Wallis test revealed differences between the three
treatments, i.e., \emph{D. solani} strain mixture, \emph{D.
dianthicola}strain mixture and species mixture (k=6.1; DF=2; p=0.04).
Pairwise comparison (Post-hoc Tukey test) showed that \emph{D. solani}
was less virulent than \emph{D. dianthicola} (F=-2.5; p= 0.03) and the
species mixture (F=1.9; p= 0.10). However, symptom incidence caused by
the species mixture did not differ from those of the \emph{D.
dianthicola}mixture (F=-0.5; p= 0.86). Post-hoc Tukey p-values and mean
value (± SE) of the percentage of symptomatic plants inoculated by the
\emph{D. dianthicola} (53\% ± 7), \emph{D. solani} (23\% ± 3) and mixed
(47\% ± 0) populations are presented in the \textbf{figure 3b} . To
assess the dynamics of the appearance of symptomatic plants, we also
drew a disease progress curve for each replicate (\textbf{Figure S3a} )
and compared the areas under disease progress curve (\textbf{Figure S3b}
). Pairwise comparisons (Post-hoc Tukey tests) confirmed that \emph{D.
solani} was less virulent than \emph{D. dianthicola} (F=-336;
p\textless{}10\textsuperscript{-11}) and the species mixture (F=386;
p\textless{}10\textsuperscript{-11}).

To evaluate which pathogen had emerged at the beginning of the infection
process, hence to identify the most probable causative agent of the
observed symptoms, we used qPCR to quantify pathogen loads. When the two
species mixtures were inoculated separately, \emph{D. dianthicola}
and\emph{D. solani} reached the mean values ± SE of 2 x
10\textsuperscript{11} ± 1 x 10\textsuperscript{4} cells and 3 x
10\textsuperscript{9} ± 1 x 10\textsuperscript{2} cells per gram of
symptomatic stem tissues, respectively. In eight co-infected symptomatic
plants, quantifications of the pathogen abundance revealed an excess
of\emph{D. dianthicola} with a CI median value of
10\textsuperscript{-5}(\textbf{Figure 3c} ). The eight CI values
differed from one (Kruskal-Wallis test, k=9.5; DF=1; p= 2 x
10\textsuperscript{-3}), meaning that \emph{D.~dianthicola} outcompeted
\emph{D. solani} in blackleg tissues. Altogether, these data revealed a
fitness advantage of\emph{D. dianthicola} in terms of multiplication
within lesions in the aerial parts of the host in either the absence or
presence of the\emph{D. solani} invader.

\textbf{3.3 \emph{Dickeya dianthicola} exhibited a fitness advantage
over \emph{D. solani} in potato plants with wounded roots.}

To evaluate whether plant wounding could benefit to the \emph{D.
dianthicola} resident or to the \emph{D. solani} invader, pathogen
mixtures were inoculated in pots containing plants with wounded roots.
At 61 dpi, symptomatic and asymptomatic plants were counted among 15
plants per treatment. The assay was duplicated (2 x 15 plants per
treatment). Kruskal-Wallis test revealed differences between the three
treatments, i.e., \emph{D. solani} strain mixture, \emph{D.
dianthicola}strain mixture and species mixture (k=29.2; DF=2;
p=4.6x10\textsuperscript{-7}). Pairwise comparisons (post-hoc Tukey
tests) showed that the number of plants with symptoms differed following
inoculation by \emph{D. solani} from inoculation by \emph{D.
dianthicola} (F=-4.5; p=1.9x10\textsuperscript{-5}) and by a mixture
of\emph{D. dianthicola} and \emph{D. solani} (F=6.1;
p=2.7x10\textsuperscript{-9}). Mean ± SE of the percentage of
symptomatic plants reached 33\% ± 0 for \emph{D. solani} , 83\% ± 10
for\emph{D. dianthicola} and 93\% ± 7 for a mix of \emph{D.
dianthicola}and \emph{D. solani} , indicating a stronger virulence of
\emph{D. dianthicola} as compared to \emph{D. solani} (\textbf{Figure
S4a)} . Pairwise comparisons (post-hoc Tukey tests) of the areas under
the disease curves also confirmed that \emph{D. solani} was less
virulent than \emph{D. dianthicola} (F=-386;
p\textless{}10\textsuperscript{-11}) and than a mixture of \emph{D.
dianthicola} and \emph{D. solani} (F=386;
p\textless{}10\textsuperscript{-11}) (\textbf{Figure S3c-d)} . Because
the virulence measured using symptom incidence at the final time point
(61 dpi) and area under disease progress curve (from 1 to 61 dpi) gave
similar results when comparing the two pathogens, only the final point
of symptom incidence was retained for the analysis of the following
plant assays, in order to facilitate the presentation of the data.

In the 27 emerging lesions collected from co-infected plants, qPCR
quantification of the pathogens revealed an excess of \emph{D.
dianthicola} with a CI median value of 10\textsuperscript{-5}. These CI
values were different from one (Kruskal-Wallis test: k=19.5; DF=1;
p=10\textsuperscript{-5}; \textbf{Figure S3b)} .

Altogether, these experimental data revealed that the resident \emph{D.
dianthicola} was more effective at exploiting unwounded and wounded
potato host plants than the \emph{D.~solani} invader, \emph{i.e. D.
dianthicola} had a higher fitness regarding this component of its
ecological niche.

\textbf{3.4 \emph{Dickeya solani} exhibited a fitness advantage
over\emph{D. dianthicola} in potato tubers.}

We compared the \emph{D.~dianthicola} and \emph{D. solani} ecological
traits in potato tubers. Aggressiveness of the pathogens (i.e., disease
severity) was compared using five symptom classes and a disease severity
index (DSI) was calculated summarizing the observations of the symptom
classes on 10 tubers.

In a first tuber rotting assay, each strain was inoculated separately at
10\textsuperscript{7} or at 10\textsuperscript{5} CFU on each set of 10
tubers. The two different inoculum loads allowed comparing the capacity
of the pathogens to initiate maceration and exploit tubers in two
contrasting ecological conditions. The assay was performed five times,
so we collected symptom class information from 50 tubers for each
bacterial strain and for each inoculation load. Kruskal-Wallis tests
revealed differences between the two treatments, \emph{D. solani}
and\emph{D. dianthicola,} both a high (k=3.2; DF=1; p=0.07) or a low
(k=43.6; DF=1; p= 4 x 10\textsuperscript{-11}) pathogen load. The DSI
values were calculated for each set of 10 tubers and mean values ± SE
across the five replicates reached 63 ± 13 for \emph{D. solani} and 47 ±
4 for \emph{D. dianthicola} with an inoculum of 10\textsuperscript{7}CFU
per tuber (\textbf{Figure 4a} ) and 49 ± 8 for \emph{D. solani} and 7 ±
4 for \emph{D. dianthicola} with an inoculum of 10\textsuperscript{5}CFU
per tuber (\textbf{Figure 4d} ).

In a second tuber assay, we used strain mixtures for each of the two
species and an assembly of the two species to inoculate 10 tubers for
each of 10\textsuperscript{7} and 10\textsuperscript{5} CFU per tuber.
This assay was performed twice. Kruskal-Wallis tests revealed
differences between the three treatments, i.e., \emph{D. solani}
,\emph{D. dianthicola} and the species mixture both at a high (k=51.3;
DF=2; p=4.2x10\textsuperscript{-11}) and a low (k=22.4; DF=2;
p=1.3x10\textsuperscript{-5}) pathogen load. At both bacterial loads,
pairwise comparisons (Post-hoc Tukey tests) showed that aggressiveness
was different between \emph{D. solani} and \emph{D. dianthicola} (at a
high load: F=2.7; p=0.04; at a low load: F=8.6; p\textless{}
10\textsuperscript{-11}). Aggressiveness also differed between \emph{D.
solani} and the species mixture (at a high load: F=2.9; p=0.01; at a low
load: F=2.2; p=0.07). A DSI value was calculated for each set of 10
tubers. Mean value ± SE of the DSI values reached 83 ± 0 (\emph{D.
solani} ), 63 ± 3 (\emph{D. dianthicola} ) and 63 ± 8 (\emph{D.
solani}and \emph{D. dianthicola} ) with an inoculum of
10\textsuperscript{7} CFU per tuber (\textbf{Figure 4b} ) and 69 ± 14
(\emph{D. solani} ), 16 ± 6 (\emph{D. dianthicola} ) and 48 ± 10
(\emph{D. solani} and \emph{D. dianthicola} ) with an inoculum of
10\textsuperscript{5} CFU per tuber (\textbf{Figure 4e} ). Altogether,
these tuber assays revealed a higher aggressiveness of \emph{D. solani}
compared to \emph{D. dianthicola} and to the species mixture.

The qPCR analyses of 10 symptomatic tubers revealed that the abundance
of the \emph{D.~solani} and \emph{D. dianthicola} strain mixtures ranged
from 2 x 10\textsuperscript{9} ± 3 x 10\textsuperscript{9} to 9~x
10\textsuperscript{9} ± 9 x 10\textsuperscript{9} cells per gram of
rotted tissues (mean values ± SE). These data indicated no important
differences in the capacity to exploit tubers in terms of population
yield. In co-infection assays, qPCR quantification of the pathogens in
10 symptomatic tubers revealed an advantage in favor of
\emph{D.~solani}regardless of the initial load (CI median value = 5.7;
\textbf{Figure 4c and 4f)} \emph{.} The CI values were different from
one (Kruskal-Wallis tests: k=16.3; DF=1; p-value of 5 x
10\textsuperscript{-5} with a high load; k=7.8; DF=1; p= 0.05 with a low
load).

Overall, tubers constituted potato plant tissues in which \emph{D.
solani} initiated symptoms more efficiently (even with a low pathogen
load), caused more damage (higher disease severity index) and was more
competitive than \emph{D. dianthicola} (outcompeting \emph{D.
dianthicola} ). Remarkably, the disease severity caused by \emph{D.
solani} was decreased in the presence of \emph{D. dianthicola} .

\textbf{3.5 \emph{Dickeya solani} exhibited a fitness advantage
over\emph{D. dianthicola} in hyacinths.}

The symptom incidence and competition were further evaluated in
hyacinths, that represent important hosts as they constitute a reservoir
or/and primary or intermediate host of \emph{D. solani.} We expected a
higher symptom incidence and growth advantage of \emph{D. solani} on
hyacinth host as compared to \emph{D. dianthicola} . The five \emph{D.
dianthicola} and five \emph{D. solani} bacterial strains were inoculated
separately on eight plants per strain and the number of symptomatic and
asymptomatic plants were counted. At 61 dpi, a Kruskal-Wallis test
revealed differences between \emph{D. solani} and \emph{D.
dianthicola}in terms of symptom incidence (k=3.03; DF=1; p=0.08):
\emph{D. solani}was found more virulent than \emph{D. dianthicola} ;
means ± SE of the percentage of symptomatic plants reached 43\% ± 17 and
23\% ± 9, respectively (\textbf{Figure S5a)} .

In co-inoculation assays with species mixtures (\textbf{Figure S5b} ),
the qPCR quantification of the pathogens in five symptomatic tissues
showed that the calculated CI were different from one (Kruskal-Wallis
test: k=7.8; DF=1; p= 5 x 10\textsuperscript{-3}). The CI median value
of 4 x 10\textsuperscript{9} indicated a high competitive advantage
of\emph{D.~solani} over \emph{D. dianthicola} in rotted tissues of
hyacinths. Bulb plants thus appeared promoting competitive exclusion
of\emph{D. dianthicola} by \emph{D. solani} , which would lead to an
enrichment in \emph{D. solani} in the bulb plant agrosystems.

\textbf{3.6 Pectate lyases gene expression is higher in \emph{Dickeya
solani} than in \emph{D. dianthicola}}

The capacity of \emph{D. solani} to initiate rotting with a low
bacterial load suggested a differential expression of pectate lyase
genes between the two species. To test this hypothesis, the expression
levels of the \emph{pelA} , \emph{pelD} and \emph{pelE} genes were
quantified by RT-qPCR in the five \emph{D.~solani} and five \emph{D.
dianthicola} strains grown separately in a rich medium (in the absence
of pectin) and in emerging lesions of potato stems and tubers (see a
detailed protocol in SM2). The expression of two other virulence
genes,\emph{cbsE} and \emph{acsD,} which are not involved in the plant
cell wall degradation, but in iron-uptake, were also compared. Four
RT-qPCR measurements were performed per condition and gene. For each
gene, Kruskal-Wallis tests revealed differences between the six
treatments (rich medium, stems and tubers for the two species,
considering each strain as a replicate) for the different genes:
\emph{pelA} (k=17.1; DF=5 ; p=4x10\textsuperscript{-3}), \emph{pelD}
(k=25.1; DF=5 ; p=1x10\textsuperscript{-4})\emph{, pelE} (k=24.9; DF=5;
p=1x10\textsuperscript{-4})\emph{, cbsE} (k=20.3; DF=5 ;
p=1x10\textsuperscript{-3}) and \emph{acsD} (k=21.3; DF=5;
p=7x10\textsuperscript{-4}).

Pairwise post-hoc Tukey tests were used to compare gene expression
between \emph{D. solani} and \emph{D. dianthicola} . In the absence of
pectin (\textbf{Figure 5} ), the \emph{pelA} (F=864.3; p\textless{}
10\textsuperscript{-11}), \emph{pelD} (F=864.3; p\textless{}
10\textsuperscript{-11}) and \emph{pelE} (F=2.9; p= 4 x
10\textsuperscript{-3}) genes were expressed at a higher level
in\emph{D. solani} than in \emph{D. dianthicola} . The expression levels
of the \emph{cbsE} (F=0.377; p=0.99) and \emph{acsD} (F=-1.0; p=0.99)
genes were not significantly different between species (\textbf{Figure
S6} ). In the absence of pectin, a higher expression of pectate lyase
genes, especially \emph{pelE} , could be considered as an advantage for
initiating a rapid degradation of the plant cell wall polymers.

In symptomatic potato tubers and stems, some remarkable gene expression
patters could be noticed (\textbf{Figures 5 and S6} ). The expression
levels of \emph{pelD} and \emph{pelE} were higher in \emph{D.
solani}than in \emph{D. dianthicola} (\emph{pelD} : F=864.3;
p\textless{} 10\textsuperscript{-11} in tubers and F=4.5; p=
10\textsuperscript{-4}in stems; \emph{pelE} : F=4.5; p= 1.1 x
10\textsuperscript{-4} in tubers and F=8.1; p \textless{}
10\textsuperscript{-11} in stems). The\emph{pelA} (F=864.3; p\textless{}
10\textsuperscript{-11}) and\emph{cbsE} (F=3.4; p= 0.01) genes were
expressed at higher levels in\emph{D. solani} than in \emph{D.
dianthicola} stem tissues, but not in tubers (\emph{pelA} : F=-0.09; p=1
and \emph{cbsE} : F=0.67; p=0.99). The\emph{acsD} expression level did
not differed between the two species in diseased tubers (F=-1.5; p=0.9)
and stems (F=0.5 p=0.9). Overall, in plant symptoms, \emph{D. solani}
maintained a higher expression of the virulence genes \emph{pelD} and
\emph{pelE} compared to \emph{D. dianthicola} .

\textbf{3.7 \emph{Dickeya solani} genomics revealed two
\emph{vfmB}alleles at balanced frequencies}

We used a population genomic approach to investigate additional
ecological traits of the \emph{D. solani} invading population. We
studied SNPs and InDels in 76 \emph{D. solani} genomes (\textbf{Figure
S2} ), 56 of which were assembled after Illumina sequencing in this
study, while the 20 others had been previously acquired using the same
sequencing approach (Khayi et al., 2015). Out of the 76 genomes, 66
exhibited from 2 to 11 SNPs and InDels when compared to the \emph{D.
solani} 3337 reference genome (\textbf{Figure S2} ). In the nine others,
more than 100 SNPs were observed: some of these SNPs were clustered in
regions of the chromosome (RNS13-30-1A, PPO9134, PPO9019, RNS13-31-1A,
RNS13-48-1A, RNS15-102-1A, RNS07-7-3B) while others were distributed
along the genome (RNS05-1-2A and RNS10-105-1A).

Focusing on the 66 genomes exhibiting less than 12 SNPs compared to the
strain 3337, 45 non-synonymous variations were identified in whole
genomes (\textbf{Table S5)} . Two-third of them (30 out of 45) were
private to a single genome, while the 15 others were found in at least
two genomes. Among these 15 later, three variations were identical in
four strains, two others in five strains and one was present in 19
genomes (\textbf{Table S5 and Figure 6a)} . The most balanced
frequencies alternated a thymine (T) in 19 genomes and a cytosine (C)
residue in the other 48 genomes at the position 2,930,940 in the
reference \emph{D. solani} 3337 genome (\textbf{Figure 6a} ). The C to T
modification caused a proline (VfmB\textsubscript{Pro} allele) to serine
(VfmB\textsubscript{Ser} allele) change at the position 55 in the VfmB
protein.

A SNP-based tree of these 67 strains (\textbf{Figure 6b} ) revealed that
the \emph{D. solani} isolates carrying VfmB\textsubscript{Ser} were
placed in two different sub-clusters, one with only two
VfmB\textsubscript{Ser} \emph{D. solani} strains, EU3296 and Ds0432.1,
and the other mainly VfmB\textsubscript{Ser} strains. The
VfmB\textsubscript{Ser} allele was present in 25\% (19 out of 76) of all
analyzed \emph{D. solani} genomes. A similar percentage (27\%, 17 out of
63) was observed when only the French isolates were considered. Using
the isolation year of these 63 \emph{D. solani} isolates, we drew the
dynamics of the percentage of the VfmB\textsubscript{Ser} alleles, which
was found to fluctuate over the past decade (2005-2015) with a peak in
2013-2014 (\textbf{Figure 6c} ).

We also investigated the presence of the VfmB\textsubscript{Pro} and
VfmB\textsubscript{Ser} alleles in other \emph{Dickeya} species. The
alignments of VfmB proteins retrieved from genomic databases revealed
the occurrence of the VfmB\textsubscript{Pro} allele
in\emph{D.~dadantii} , \emph{D. chrysanthemi} and
\emph{D.~dianthicola}genomes, while the VfmB\textsubscript{Ser} allele
was found in \emph{D. zeae} genomes (\textbf{Figure S6} ). However, the
low number of genomes available let open the possibility of the
existence of additional alleles in each of these \emph{Dickeya} species.

\textbf{3.8 VfmB\textsubscript{Ser} strains were more aggressive than
VfmB\textsubscript{Pro} strains in soft-rot assays}

The modeling of the \emph{D. solani} VfmB\textsubscript{Pro} and
VfmB\textsubscript{Ser} protein structures predicted a conformational
difference in the beta-sheet structure of the virulence regulator VfmB
(\textbf{Figure 7a} ). This change is explained by the exceptional
conformational rigidity of proline that strongly affects secondary
structures such as alpha helices and beta sheets. The modeling data
prompted us to test whether
VfmB\textsubscript{Pro}-VfmB\textsubscript{Ser} variation could be
associated with a change in aggressiveness. To compare the
aggressiveness of \emph{D.~solani} VfmB\textsubscript{Ser} and
VfmB\textsubscript{Pro} isolates, we used genomic data to identify a set
of 8 isolates carrying either VfmB\textsubscript{Pro} (IPO2222, MIE35,
AM3a and 3337) or VfmB\textsubscript{Ser} (Ds0432.1, RNS10-27-2A, Sp1a
and M21a), in which the other variations were at different positions
(\textbf{Tables S3 and S4} ). Soft-rot assays using 10 inoculated potato
tubers per strain revealed that the set of the
VfmB\textsubscript{Ser}strains was more aggressive (Kruskal-Wallis test;
k=9.5; DF=1; p= 2 x 10\textsuperscript{-3}) than that of the
VfmB\textsubscript{Pro} strains (\textbf{Figure 7b} ).

To test the existence of differential expression of virulence genes in
tuber tissues, we compared transcriptomes of \emph{D. solani} IPO2222
(VfmB\textsubscript{Pro}) and Ds0432.1 (VfmB\textsubscript{Ser})
(\textbf{Figure 7c} ; \textbf{Table S6} ). The expression of four genes
found differentially expressed based on transcriptomics (\emph{pelE}
,\emph{impC} , \emph{cytA} and \emph{budA} ) was further investigated by
RT-qPCR in the same samples used for transcriptomics: they found to be
also upregulated (\textbf{Figure S8} ). Overall, 170 differentially
expressed genes (adjusted p-value \textless{}~0.05 and absolute log2
fold change \textgreater{} 2) were identified by comparative
transcriptomics. Most of them (150 genes) were upregulated in Ds0432.1
carrying the VfmB\textsubscript{Ser} allele (\textbf{Table S7} ). We
studied more specifically 35 well-characterized \emph{D.
solani}virulence genes (Raoul des Essarts et al., 2019). We observed an
enrichment of these virulence genes among the upregulated genes
in\emph{D. solani} Ds0432.1, while none of them was found among the
downregulated genes (\textbf{Table S8} ). These upregulated virulence
genes in \emph{D. solani} Ds0432.1 included the pectate lyase
genes\emph{pelB, pelC, pelD, pelE} and \emph{pelL,} the protease
genes\emph{ptrA} , \emph{prtB} and \emph{prtC,} and the T6SS-related
toxin/antitoxin genes \emph{hcp} (\textbf{Table S8} ). These upregulated
genes encompassed virulence determinants that are already known to be
regulated by the Vfm quorum-sensing in \emph{D. dadantii} (Nasser et
al., 2013).

\textbf{3.9 Fitness costs and gains associated with VfmB alleles in
potato stems and tubers}

We used the same eight isolates carrying either
VfmB\textsubscript{Pro}(IPO2222, MIE35, AM3a and 3337) or
VfmB\textsubscript{Ser} (Ds0432.1, RNS10-27-2A, Sp1a and M21a) to
constitute VfmB\textsubscript{Pro} and VfmB\textsubscript{Ser}
experimental populations for comparing their fitness in plant assays.

In soft-rot assays (\textbf{Figure 8a-b} ), each of the two experimental
populations and their mix was inoculated on 10 tubers and a symptom
class was assigned to each tuber. Two inoculation loads were used
(10\textsuperscript{7} CFU or 10\textsuperscript{5} CFU per tuber). This
assay was performed in triplicate (3 x 10 tubers per treatment).
Kruskal-Wallis tests revealed differences between the three treatments,
i.e., inoculation by \emph{D. solani} VfmB\textsubscript{Pro}, \emph{D.
solani} VfmB\textsubscript{Ser} and their mixture, and the differences
were significant at both high (k=17.6; DF=2;
p=1.5x10\textsuperscript{-4}) and low (k=7.2; DF=2; p=0.03) pathogen
loads. Whatever the bacterial load, pairwise comparisons (Post-hoc Tukey
tests) showed that aggressiveness (i.e. symptom severity) was different
between \emph{D. solani} VfmB\textsubscript{Pro} and \emph{D.
solani}VfmB\textsubscript{Ser} (at a high load: F=4.6; p=9.5 x
10\textsuperscript{-6}; at a low load: F=0.8; p= 0.01). The \emph{D.
solani} VfmB\textsubscript{Ser} population was more aggressive than
the\emph{D. solani} VfmB\textsubscript{Pro} population (DSI mean value ±
SE of 92 ± 2 for VfmB\textsubscript{Ser} vs 73 ± 3 for
VfmB\textsubscript{Pro} at a high load and 45 ± 2 for
VfmB\textsubscript{Ser} vs 26 ± 9 for VfmB\textsubscript{Pro} at a low
load; \textbf{Figure 8a-b)} . VfmB\textsubscript{Ser}
\emph{D.~solani}strains thus more efficiently damaged tubers than
VfmB\textsubscript{Pro} \emph{D.~solani} strains.

When the VfmB\textsubscript{Ser} and
VfmB\textsubscript{Pro}\emph{D.~solani} experimental populations were
co-infected in tubers, shotgun sequencing of the pathogens recovered
from symptoms allowed to calculate CI values (\textbf{Figure 8a-b} ).
With a load of 10\textsuperscript{7} CFU per tuber, the CI values (8
values; median = 1.3) were not different from one (Kruskal Wallis test;
k=0.8; DF=1; p= 0.4). With a load of 10\textsuperscript{5} CFU per
tuber, the CI values (3 values; median = 2) differed from one (Kruskal
Wallis test; k=4.4; DF=1; p= 0.04). In tubers, the \emph{vfmB} allele
thus appeared neutral or to confer a moderate advantage as compared to
the VfmB\textsubscript{Pro} allele.

In blackleg symptom assays (\textbf{Figure 8c} ), the \emph{D.
solani}VfmB\textsubscript{Pro} and \emph{D. solani}
VfmB\textsubscript{Ser}experimental populations and their mix were
inoculated on non-wounded plants and the number of symptomatic and
asymptomatic plants were counted. The assay was performed in triplicate:
two assays with 25 plants and one assay with 15 plants per treatment.
Kruskal-Wallis tests revealed no difference between the three
treatments, i.e., the \emph{D. solani} VfmB\textsubscript{Pro} strain
mixture, the \emph{D. solani}VfmB\textsubscript{Ser} strain mixture and
their mix (k=0.29; DF=2; p=0.86). Shotgun sequencing of bacteria
recovered from symptoms allowed calculation of CI values in 16
co-infected plants (\textbf{Figure 8c} ). These CI values were different
from one (Kruskal-Wallis test; k=6.6; DF=1; p= 9 10\textsuperscript{-3})
with a median CI of 14, showing a fitness advantage of the
VfmB\textsubscript{Pro} allele in emerging lesions in the stems.

Altogether, the plant assays indicated that the
VfmB\textsubscript{Ser}allele was associated to a higher aggressiveness
in the rotted tubers compared to the VfmB\textsubscript{Pro} allele.
This suggested that the VfmB\textsubscript{Ser} allele could more
efficiently initiate maceration of tubers in the field and storage
conditions. In contrast, the VfmB\textsubscript{Ser} allele seemed to
confer a lower competitive fitness than the VfmB\textsubscript{Pro}
allele when \emph{D. solani}proliferates in rooted tubers and,
particularly, in stem symptoms. Such opposite gains across different
conditions could contribute to the maintenance of balanced frequencies
of the two alleles in \emph{D. solani} populations.

\textbf{4 Discussion}

Two successive invasions of \emph{Dickeya} potato pathogens occurred in
Europe: first \emph{D. dianthicola} in the middle of the
20\textsuperscript{th} century, this pathogen being now considered as
endemic, and second, \emph{D. solani} at the beginning of the
21\textsuperscript{th} century. \emph{Dickeya solani} and \emph{D.
dianthicola} cause similar symptoms on potato plants, so that they are
expected to compete for the same resources. Over ten years, our
epidemiologic surveys revealed a successful establishment of \emph{D.
solani} together with a maintenance of \emph{D.~dianthicola} . Our
experiments contributed to explain such puzzling co-existence by
contrasted advantages in different parts of the plants and therefore
partially different ecological niches.

By comparing ecological traits of \emph{D. solani} and \emph{D.
dianthicola} , using multiple strains representative of the population
diversity, we indeed found contrasted behaviors in these species with
respect to aerial parts versus tubers of \emph{S.~tuberosum} . The
resident \emph{D. dianthicola} more efficiently exploited host stems
after an inoculation of the wounded and unwounded roots than did the
invader \emph{D. solani, i.e.,} causing higher symptom incidence, and
exhibiting greater proliferation and relative fitness in competition
assays. In contrast, \emph{D. solani} more efficiently initiated the
rotting process (especially at a low bacterial inoculum) and
outcompeted\emph{D. dianthicola} in tubers, with potential consequences
on tubers in the fields and during storage. Our experimental assays
suggested that tubers represent an entry route of the \emph{D. solani}
invader into the potato agrosystems.

The capacity of \emph{D. solani} to cause rooting at a lower bacterial
load than \emph{D. dianthicola} is likely at least partly due to a
higher expression of the \emph{pel} enzymes, especially PelE that acts
as an initiator of the plant cell wall degradation (Duprey et al.,
2016). By comparing the expression of some \emph{pel} genes in emerging
lesions in potato stems and tubers, we observed a higher expression of
the virulence genes \emph{pelD} and \emph{pelE} in \emph{D.
solani}compared to \emph{D. dianthicola.} Remarkably, by comparing
\emph{pel}genes in several \emph{Dickeya} species, Duprey et al. (2016)
showed that \emph{D. solani} evolved specific regulatory sequences that
contributes to a different expression level of the \emph{pelD}
and\emph{pelE} genes compared to \emph{D. dianthicola} . The
\emph{pelA}gene is truncated in \emph{D. dianthicola} (Duprey et al.,
2016; Raoul des Essarts et al., 2019), but full-length and expressed in
\emph{D. solani} (as shown in this study), reinforcing their virulence
arsenal. Other metabolic traits could also contribute to the fitness
advantage of\emph{D. solani} for exploiting tubers: comparative
transcriptomics revealed a higher expression of the glyoxylate shunt in
\emph{D. solani}than in \emph{D. dianthicola,} a pathway that
contributes to exploit alternative carbon sources when sugar
availability is low (Raoul des Essarts et al., 2019).

Beside the tripartite interaction between potato plant host, \emph{D.
solani} and \emph{D. dianthicola} , additional environmental (soil and
climate) and biological factors (microbiota
including\emph{Pectobacterium} species, other hosts and non-host plants)
may facilitate or limit \emph{D. solani} establishment (Charkowsky 2018;
Shyntum et al., 2019; Toth et al., 2011). We showed that\emph{D.~solani}
efficiently outcompeted \emph{D. dianthicola} in hyacinths, in line with
the epidemiologic data supporting the bulb plants as potential
intermediate hosts with an important role in the recurrent invasion of
potato agrosystems (Chen, Zhang, \& Chen, 2015; Slawiak et al., 2009;
van der Wolf et al., 2014). Prophylactics may allow circumventing the
propagation of \emph{D. solani} from an agrosystem to another.
Competition and facilitation processes have been well studied in
pathogenic fungi (Al-Naimi, Garrett, \& Bockus, 2005; Abdullah et al.,
2017; Gladieux et al., 2015; Zhan \& McDonald, 2013). Another factor
that could reduce competition between the two\emph{Dickeya} species is
their natural low abundance in soils and surface waters, as well as in
tuber seeds that are subjected to prophylactic diagnosis. A small
population size belonging to a single species could proliferate in a
plant individual without any interactions with another \emph{Dickeya} or
\emph{Pectobacterium} pathogen species. These effects linked to size
population and dispersal are expected to delay invasion. In line with
this hypothesis, the observed slow increase of the percentage of
\emph{Dickeya} -positive fields over one decade (2004-2015) suggested
that the \emph{Dickeya} invasion was still ongoing. Among the emerging
literature on microbial invasion, the\emph{D. solani} pathogen appears
as a good example illustrating how different ecological components
(here, the plant host and a resident pathogen) should be considered to
understand the biological invasion by a bacterial pathogen (Cadotte et
al., 2018; Germain, Mayfield, \& Gilbert, 2018).

The genome sequencing data indicating low diversity in \emph{D.
solani}suggest a bottleneck during introduction in Europe. The dispersal
modes (either horizontally via soil, surface water, insects and some
agricultural practices or vertically by asymptomatically contaminated
tuber seeds) could contribute to further bottlenecks in \emph{D.
solani}(Charkowsky 2018; Toth et al., 2011). Selection on some genes may
also have further reduced genetic diversity through selective sweeps
across the whole genomes as these bacteria are clonal. Allelic changes
related to quorum-sensing systems were already observed in different
plant and animal pathogens along the host-colonization process (Feltner
et al., 2016; Guidot et al., 2014; Tannières, Lang, Barnier, Shykoff,
Faure, 2017), indicating that balancing selection contributed to
maintain their variability. Remarkably, we observed balanced frequencies
of two alleles in the VfmB protein involved in the Vfm-type
quorum-sensing in\emph{Dickeya} bacteria. The chemical structure of the
Vfm signal is not known, but it has been involved in tuber rotting and
upregulation of some virulence genes including pectate lyases
(\emph{pel} genes), proteases (\emph{prt} genes) and cellulases
(\emph{cel} genes) (Nasser et al., 2013; Potrykus et al., 2018). Using
tuber assays, we observed a slightly higher aggressiveness in
VfmB\textsubscript{Ser} strains compared to VfmB\textsubscript{Pro}
strains. Using transcriptomics of\emph{D. solani} pathogens recovered
from tuber symptoms, we confirmed an enrichment of upregulated genes,
including \emph{pel} and \emph{prt}genes, in the VfmB\textsubscript{Ser}
strain Ds0432.1 compared to VfmB\textsubscript{Pro} strain IPO2222.
Because of the role of the VfmB protein in Vfm signaling is not
completely elucidated, it was premature to go deeper into the
mechanistic characterization of the VfmB\textsubscript{Ser} and
VfmB\textsubscript{Pro} alleles. In a near future, the reconstruction of
allelic mutants and comparison with the wild strain with otherwise the
same genetic background should help characterizing the role of VfmB in
Vfm quorum-sensing and ecology of\emph{D. solani} .

In this work, we strongly suggested that the
VfmB\textsubscript{Ser}strains were more aggressive than the
VfmB\textsubscript{Pro} strains in potato tubers, but not more virulent
in potato stem assays, and that the VfmB\textsubscript{Ser} strains were
less competitive than the VfmB\textsubscript{Pro} strains in tuber and
stem symptoms. Such an environment-dependent advantage of
VfmB\textsubscript{ser} and VfmB\textsubscript{Pro} alleles in plant
infection assays predicts balancing selection in natural populations.
The VfmB\textsubscript{ser}allele could thus provide an advantage when
competition is reduced at the beginning of the establishment in potato
agrosystems and under a high dispersal condition. In contrast,
VfmB\textsubscript{ser} could be outcompeted by VfmB\textsubscript{Pro}
when \emph{D. solani} is already established. Our epidemiologic data
revealed up and down variation of VfmB\textsubscript{ser} relative
abundance in field populations over the past decade, in agreement with
an increase of competition between\emph{D. solani} VfmB alleles in the
more recent sampling year. There is a very low number of SNPs/InDels
(\textless{}12) in the genomes beyond those in Vfm, however, functional
genetics will be required to fully validate the causal role of the Vfm
alleles.

In conclusion, this study using complementary approaches, multiple
strains representative of the population diversity and multiple
ecological conditions, brings novel insights allowing a better
understanding of the pattern and causes of the \emph{D.~solani} invasion
into potato production agrosystems, and the reasons
why\emph{D.~dianthicola} nevertheless persisted. More broadly, this
study contributes to our understanding the ecological determinants of
pathogen invasion and of the conditions for the maintenance of endemic
competitors.

\textbf{ACKNOWLEDGEMENTS}

PB was supported by a PhD grant from Université Paris-Sud (Université
Paris-Saclay), KR was supported by a PhD grant from FN3PT/inov3PT with
the support of ANRT (N°2016/0800). KGC thanks the financial support from
the University of Malaya (FRGS grant FP022-2018A and HIR grant
H-50001-A000027). This work has benefited from the facilities and
expertise of the high throughput sequencing platform and the plant
culture facilities at I2BC (Gif-sur-Yvette). This work was supported by
CNRS (SE2016-2017-2018), French Federation of Seed Potato Growers
(FN3PT/inov3PT), Agence Nationale de la Recherche (ANR-15-CE21-0003) and
LabEx Saclay Plant Sciences-SPS (ANR-10-LABX-0040-SPS).

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\textbf{DATA ACCESSIBILITY}

DNA sequences: Genbank accessions VYSC00000000; VZQE00000000;
VZQF00000000; VZQG00000000; VZQH00000000; VZQI00000000; VZQK00000000;
VZQJ00000000; VZQL00000000; VZQM00000000

\textbf{AUTHOR CONTRIBUTION}

DF, PB, VH conceived experiments; JC, EM, PD, AL, AB and VH performed
field sampling and molecular diagnosis; PB characterized fitness traits
in \emph{D. solani} and \emph{D.~dianthicola} ; PB, KR and EM
characterized fitness traits in \emph{D. solani} \emph{vfmB} variants;
PB performed RNA analyses (RT-qPCR and transcriptomics); YJ, KWH, KGC,
AL and PB prepared DNA samples and perforemd sequencing; SK
compared\emph{D. solani} genomes; PB, KR and DF performed statistical
analyses; DF, TG, PB, VH, SR wrote the manuscript.

\textbf{CONFLICT OF INTEREST}

No potential conflict of interest was disclosed.

\textbf{ORCID}

Denis Faure orcid.org/0000-0002-5379-8867

\textbf{Figure legends}

\textbf{Figure 1 Symptoms caused by \emph{Dickeya} pathogens.} Symptoms
(white arrows) caused by \emph{Dickeya solani} and \emph{Dickeya
dianthicola} on potato stems (\textbf{a}) and hyacinths (\textbf{b}).
The five symptom classes (0 to 4) used to compare the aggressiveness
of\emph{Dickeya solani} and \emph{Dickeya dianthicola} on potato tubers
(\textbf{c}).

\textbf{Figure 2 \emph{Dickeya} and \emph{Pectobacterium} prevalence
from potato fields exhibiting blackleg symptoms.} Percentage
of\emph{Pectobacterium}-containing and \emph{Dickeya}-containing fields
(\textbf{a}) and that of \emph{D. solani}-containing fields and \emph{D.
dianthicola}-containing fields (\textbf{b}) were calculated each year
from 2004 to 2015 (with the exception of 2006). (\textbf{c}) Number and
relative abundance of the \emph{Pectobacterium}, \emph{D.
dianthicola}and \emph{D. solani} isolates collected in 19 symptomatic
fields sampled from 2013 to 2016. A hierarchical clustering paired group
method delineated four pathogen population groups, i.e.
\emph{Pectobacterium}only (I: 3 fields), \emph{D. solani} and
\emph{Pectobacterium} (II: 9 fields), \emph{D. dianthicola} and
\emph{Pectobacterium} (III: 3 fields), and \emph{D. dianthicola, D.
solani} and \emph{Pectobacterium}(IV: 4 fields).

\textbf{Figure 3 Symptom incidence and fitness of \emph{Dickeya
dianthicola} and \emph{D. solani} in potato plants.} In \textbf{a}, mean
value and standard error (SE) of the percentage (\%) values of plants
exhibiting blackleg symptoms, which were measured after inoculation of
each of the five \emph{D. solani} strains (3337, IPO2222, RNS05-1-2A,
Ds0432.1, PPO9019) and five \emph{D. dianthicola} strains
(RNS11-47-1-1A, CFBP1888, CFBP2982, CFBP2015, MIE34) on 15 plants. The
p-value of the Kruskal-Wallis test comparing of the symptomatic classes
between the two species is indicated below the graph. In \textbf{b},
mean value and SE between two replicates of the percentages (\%) of
plants exhibiting blackleg symptoms which was measured on 15 plants
inoculated by \emph{D. dianthicola} and \emph{D. solani} populations and
their mix. The p-values of the pairwise comparisons (Post-hoc Tukey
tests) of the symptomatic classes are indicated below the graph, when p
\selectlanguage{english}[?] 0.1. In \textbf{c}, competitive index (CI) values between \emph{D.
solani} and \emph{D. dianthicola} populations were calculated in eight
emerging lesions of co-infected plants and revealed a competitive
advantage of \emph{D.~dianthicola}: the CI median (= 2.4
10\textsuperscript{-5}) is represented by a thick bar; p-values
resulting from Kruskal-Wallis tests testing difference from one are
indicated. Legend: * for 0.05\textless{}p\selectlanguage{english}[?]0.1; ** for
0.01\textless{}p\selectlanguage{english}[?]0.05 and *** for p \selectlanguage{english}[?]0.01.

\textbf{Figure 4 Aggressiveness and fitness of \emph{Dickeya
dianthicola} and \emph{D. solani} in potato tubers.} Rotting assays were
conducted by inoculating each tuber by either
10\textsuperscript{7}colony-forming units (CFU) (in \textbf{a},
\textbf{b} and \textbf{c}) or 10\textsuperscript{5} CFU of pathogens (in
\textbf{d}, \textbf{e} and\textbf{f}). In \textbf{a}, \textbf{b},
\textbf{d} and \textbf{e}, each disease severity index (DSI) value was
calculated using symptom classes observed on 10 tubers. In \textbf{a}
and \textbf{d}, mean values and standard errors (SE) of DSI values were
measured for each of the five\emph{D. solani} strains (3337, IPO2222,
RNS05-1-2A, Ds0432.1, PPO9019) and five \emph{D. dianthicola} strains
(RNS11-47-1-1A, CFBP1888, CFBP2982, CFBP2015, MIE34) using five
(\textbf{a}) and two (\textbf{d}) independent experiments. The p-values
of the Kruskal-Wallis tests comparing symptom classes are indicated
below the graphs. In \textbf{b}and \textbf{e}, mean values and standard
errors of DSI values were measured twice for each of the experimental
populations of \emph{D. dianthicola, D. solani} and the mixture of the
two. The p-values of the pairwise Tukey tests comparing the symptomatic
classes are indicated, when p \selectlanguage{english}[?] 0.1. In \textbf{c} and \textbf{f}, the
competitive index (CI) between \emph{D. solani} and \emph{D.
dianthicola} populations was calculated in 10 co-infected symptomatic
tubers: the median values (indicated by a thick bar) reached 5.7
(\textbf{c}) and 5.8 (\textbf{f}) and the CI values were statistically
different from one (Kruskal-Wallis test; p = 5 10\textsuperscript{-5}
and p = 0.05 respectively), revealing a competitive advantage of
\emph{D.~solani}. Legend: * for 0.05\textless{}p\selectlanguage{english}[?]0.1; ** for
0.01\textless{}p\selectlanguage{english}[?]0.05 and *** for p \selectlanguage{english}[?]0.01.

\textbf{Figure 5 Expression of the pectate lyase genes
\emph{pelA},\emph{pelD} and \emph{pelE}.} The expression level of the
\emph{pelA},\emph{pelD} and \emph{pelE} genes was evaluated in each of
the five\emph{D. solani} strains (3337, IPO2222, RNS05-1-2A, Ds0432.1,
PPO9019) and five \emph{D. dianthicola} strains (RNS11-47-1-1A,
CFBP1888, CFBP2982, CFBP2015, MIE34), grown in three conditions: a rich
culture medium in the absence of pectin (exponential growth phase) and
symptomatic tubers (at 5 days post infection) and emerging lesions in
stems. Relative expression was measured four times and normalized using
the \emph{rpoB} and \emph{yafS} gene expression. In the graphs, the mean
values and standard error (SE) of gene expression from all strains of a
given species are indicated, as well as p-values of pairwise comparisons
by Tukey tests. Legend: * for 0.05\textless{}p\selectlanguage{english}[?]0.1; ** for
0.01\textless{}p\selectlanguage{english}[?]0.05 and *** for p \selectlanguage{english}[?]0.01.

\textbf{Figure 6 Population genomics of \emph{Dickeya solani}.}
In\textbf{a}, scan of 67 \emph{D. solani} genomes revealed that the
genome position 2,930,940, (according the \emph{D. solani} 3337 genome),
in the\emph{vfmB} gene, was the most balanced non-synonymous variation,
with alternated VfmB\textsubscript{Pro} (71\%) and
VfmB\textsubscript{Ser}(29\%) alleles. In \textbf{b}, single nucleotide
polymorphism (SNP)-based tree of \emph{D. solani} strains using
PHYLOViZ; the name of the French isolates is indicated in blue font; the
VfmB\textsubscript{Ser} and VfmB\textsubscript{Pro} strains used in the
plant assays are underlined. In \textbf{c}, dynamics of the
VfmB\textsubscript{Ser} allele (\%) among the \emph{D. solani} isolates
along the sampling period 2005-2015 in France.

\textbf{Figure 7 Characterization of the VfmB alleles.} In \textbf{a},
using the \emph{Escherichia coli} AidB protein (the PDB accession is
3DJL) as a model, the Phyre2-predicted structure of the VfmB protein
showed conformational differences in the beta-sheet associated with the
VfmB\textsubscript{Pro} and VfmB\textsubscript{Ser} alleles; the Pro55
and Ser55 positions are in red color in the VfmB representations
obtained using the EzMol web server. In \textbf{b}, mean values and
standard error (SE) of disease severity index (DSI) values, which were
calculated by recording symptom classes on 10 tubers infected by
10\textsuperscript{7} CFU of each of the \emph{D. solani} strains
carrying either VfmB\textsubscript{Pro} (IPO2222, MIE35, AM3a and 3337)
or VfmB\textsubscript{Ser} (Ds0432.1, RNS10-27-2A, Sp1a and M21a); the
p-value of the Kruskal-Wallis test comparing the four
VfmB\textsubscript{Pro} and four VfmB\textsubscript{Ser} strains using
symptom classes is indicated below the graph. In \textbf{c}, comparative
transcriptome of \emph{D. solani} 3337 (VfmB\textsubscript{Pro}) and
Ds0432.1 (VfmB\textsubscript{Ser}) recovered from soft-rot lesions in
potato tubers; upregulated virulence genes were enriched in Ds0432.1
(VfmB\textsubscript{Ser}) as illustrated by the \emph{pelB, pelC, pelC,
hcpA} and \emph{prtA} genes (closed circles).

\textbf{Figure 8 Aggressiveness, symptom incidence and fitness assays of
two \emph{Dickeya solani} experimental populations expressing the VfmB
alleles.} Soft-rot assays were conducted by inoculating each tuber by
either 10\textsuperscript{7} colony-forming units (CFU) (\textbf{a}) or
10\textsuperscript{5} CFU (\textbf{b}) of the VfmB\textsubscript{Pro}and
VfmB\textsubscript{Ser} \emph{D. solani} populations and a mixture of
the two. In \textbf{a} and \textbf{b}, each disease severity index (DSI)
value (measuring aggressiveness) was calculated using symptomatic
classes observed on 10 tubers; the assays were performed in triplicate.
The p-values of the pairwise Tukey tests comparing the symptom classes
are indicated, when p \selectlanguage{english}[?] 0.1. In \textbf{c}, percentage (\%) of plants
exhibiting blackleg symptoms was measured on plants inoculated by the
VfmB\textsubscript{Pro} and VfmB\textsubscript{Ser} \emph{D.
solani}populations and a mixture of the two. These assays measuring
symptom incidence were performed in triplicate. Kruskal-Wallis test
revealed no difference between the three treatments using symptom
classes (p = 0.86). In \textbf{a, b} and \textbf{c}, competitive index
(CI) values of VfmB\textsubscript{Pro} and VfmB\textsubscript{Ser}
populations were calculated using allele counts based on shotgun
sequencing of bacterial populations recovered from co-infected tissues.
Median values of CI are represented as thick lines and reached 1.7 (8
repeats in \textbf{a}), 2.0 (3 repeats in \textbf{b}) and 14.0 (16
repeats in \textbf{c}) in the three treatments. Statistical differences
between CI values and 1 (Kruskal-Wallis test) revealed that neither
\emph{D. solani}VfmB\textsubscript{Pro} or \emph{D. solani}
VfmB\textsubscript{Ser} had significant advantage in tubers inoculated
with a high load (p = 0.3 in\textbf{a}), but \emph{D. solani}
VfmB\textsubscript{Pro} was more competitive in tubers inoculated with a
low load (p = 0.04 in\textbf{b}) and in stems (p = 9 x
10\textsuperscript{-3} in \textbf{c}). Legend: * for
0.05\textless{}p\selectlanguage{english}[?]0.1; ** for 0.01\textless{}p\selectlanguage{english}[?]0.05 and *** for p \selectlanguage{english}[?]0.01.\selectlanguage{english}
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