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\begin{document}

\title{The effects of Erysiphe quercicola inoculation on the phyllosphere
microbiome of Heveae brasiliensis in Hainan Province, China}



\author[1]{Jiaxin Shan}%
\author[2]{Hua Wu}%
\author[1]{Weiguo Miao}%
\author[1]{Jinyao Yin}%
\author[1]{Xiao Li}%
\author[1]{Chunhua Lin}%
\affil[1]{Hainan University}%
\affil[2]{Hainan Medical University}%


\vspace{-1em}



  
  \date{May 20, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Rubber tree powdery mildew, a major fungal leaf disease of Heveae
brasiliensis trees caused by obligate parasitic fungi (Erysiphe
quercicola), is among the most important diseases affecting rubber
planting areas worldwide. Phyllosphere microbiomes are currently a new
research hotspot in molecular ecology, and their biological community is
extremely rich. This study used high-throughput sequencing and other
molecular techniques to analyze the structure and diversity of dominant
fungi and bacteria in the communities of rubber tree leaves (N=16) in
four representative rubber-producing regions in Hainan Province, China,
after the occurrence of white powder disease. The sampled area had high
species richness and stable biodiversity. This study mainly focused on
(i) the dominant bacterial and fungal phyla and genera of the sampled
regions; (ii) differences in the phyllosphere microbial community
structure and relative abundance between healthy leaves and powdery
mildew Level 3-diseased leaves within the same region; and (iii)
differences in the phyllosphere microbial community structure and
relative abundance between healthy leaves and diseased leaves, as well
as their correlations with environmental factors, in different regions.
This work is innovative in three respects: (i) distinguishing the
dominant populations of phyllosphere microbes for rubber trees with
powdery mildew via high-throughput detection technology to determine the
impact of powdery mildew on these microbes; (ii) exploring the effects
of pathogenic bacteria on phyllosphere microbes and hosts from a
relatively macro perspective; and (iii) investigating the effects on
phyllosphere microbial communities before and after the infection of
obligatory parasite leaf pathogenic bacteria. This project is among the
first conducted in China's representative rubber-producing areas to
study Erysiphe's influence on rubber tree leaf microorganisms. These
findings provide data support to better understand the biological
evolution of powdery mildew diseases and establish new strategies for
their ecological control in rubber tree plantations.%
\end{abstract}%



\sloppy


\textbf{INTRODUCTION}

\emph{Heveae brasiliensis} , or the rubber tree, is a tall perennial
native to the Amazon basin. The rubber tree has been introduced to more
than 40 countries and regions in tropical and subtropical areas, where
it plays a pivotal role in the economic development of plantations
(Lieberei, 2007). As a major producer and consumer of natural rubber,
China began to plant rubber trees within its territory in 1906. In 1954,
Chinese researchers made a breakthrough in the large-scale cultivation
of rubber trees in the subtropics (latitude 18\selectlanguage{ngerman}°N and above), leading
China to become the fourth largest producer of rubber globally, despite
previously having no rubber plantations at all. Currently, there are
five natural rubber plantation bases in China established in Hainan,
Yunnan, Guangdong, Guangxi, and Fujian provinces. The experiment
reported in the present study was conducted at plantations in Hainan.

Rubber tree powdery mildew is one of the most damaging and widespread
foliar diseases of rubber trees. This disease affects the profit of the
natural rubber industry by causing defoliation and reductions in latex
yield. In severe cases, rubber production can be reduced by 45\%
(Liyanage et al., 2016). As the most serious epidemic disease affecting
China's rubber plantations, powdery mildew occurs in various rubber
planting areas every year. For example, the Xishuangbanna land
reclamation area suffered major damage due to powdery mildew in 2017,
delaying rubber tapping by nearly 2 months and reducing rubber
production by tens of thousands of tons, resulting in losses totaling
hundreds of millions of yuan (Liu et al., 2018). It is known that
phenological and meteorological factors can jointly influence powdery
mildew disease. Under optimum conditions, the conidia can repeatedly
infect the host tree throughout the year, leading to greatly reduced
photosynthesis, which results in slower growth and substantially
decreased latex yield (Liyanage et al., 2017). At present, plantation
managers rely on chlorothalil and sulfur powder for mildew prevention
and control. Although the application of these agents is effective to
some extent, chlorothalil and sulfur powder cannot fundamentally prevent
disease outbreaks, and their use causes environmental pollution.

The pathogen responsible for rubber tree powdery mildew is\emph{Erysiphe
quercicola} . \emph{E. quercicola} is an obligate parasitic fungal
pathogen that cannot be cultured in vitro without host tissue. The
pathogen spreads easily through the air and causes serious damage to
rubber trees, notably their leaves, as well their inflorescences, buds,
and other tissues. The conidia and hyphae of powdery mildew form a white
powder that appears on infected leaves, buds, and shoots. Later on,
light yellow spots appear on infected leaves, causing the leaves to
twist, buckle, or otherwise become distorted in shape and fall off.

Phyllosphere microorganisms are intimately related to plant growth and
the occurrence of plant diseases (Liu et al., 2022). The phyllosphere
microbial community is determined by various factors such as leaf age,
canopy position, season, and chemical spraying (Jager et al., 2001). Two
important indicators for inferring the phyllosphere's microecology are
its community structure and metabolic functions (Liu et al., 2022). The
regulation of phyllosphere microbial communities has opened a new and
alternative approach to the biological control of foliar diseases. In
this respect, the structural dynamics of microorganisms on leaf surfaces
have great significance for shaping the near-surface environment and
ecology (Li et al. 2021). Although the phyllosphere provides relatively
stable conditions for the growth and reproduction of its microorganisms,
the phyllosphere living environment is harsh. To better adapt to this
habitat adversity, the phyllosphere microbial community relies on its
diversity and complexity as evinced by its viable but non-culturable
(VBNC) features. Although the phyllosphere environment is hostile, its
microbial communities are still highly diverse, consisting of bacteria,
filamentous fungi, yeasts, algae, and protozoans. However, bacteria are
the main microorganisms constituting the phyllosphere. The community's
diversity, dispersal, and development on the leaf surface are mainly
associated with physiological and biochemical changes in the host leaf,
its living environment, and its level of immunity (Liu et al., 2022).
Many phyllosphere microorganisms have co-evolved with their hosts or
epiphytes, and thus play key roles in plant productivity and health by
affecting leaf function and lifespan, seed mass, apical growth,
flowering, and fruit development, as well as by assisting in the removal
and degradation of environmental pollutants (Stone et al., 2018).

The community structure and diversity of phyllosphere microorganisms
influence the characteristics and strength of the ecological functions
of leaves. The phyllosphere's microecological dynamic equilibrium is
central to the composition of its microbial community. The impacts of
phyllosphere microbes upon their host plants, surrounding atmospheric
conditions, and microbial interactions have been studied. The results
suggest that global climate change has altered phyllosphere microbial
communities, with potential cascading effects on plant function and
evolution and ecosystem functioning (Vacher et al., 2016). In contrast,
little research has been conducted on smaller scales, especially in
regard to the relationship between phyllosphere microbes and their hosts
and pathogens following powdery mildew infection in a cash crop such as
rubber trees. To address this knowledge gap, the present study employed
MiSeq high-throughput sequencing (i) to investigate the similarities and
differences in the composition of the phyllosphere microbial community
of rubber trees in Hainan between regions where powdery mildew occurs
and where it does not; and (ii) to understand the effects of powdery
mildew on the phyllosphere microbial community of rubber tree leaves and
the changes in each microbial community. The overarching aim of this
study was to provide an empirical basis for the biological control of
powdery mildew and further elucidate the evolution of powdery mildew in
rubber trees.

\textbf{MATERIALS AND METHODS}

\textbf{Leaf Samples}

To study the structure and diverse differences of the phyllosphere
microbial communities of rubber trees with powdery mildew in different
regions of Hainan, four representative rubber plantation farms were
selected as sampling sites, namely, Baisha (BS), Danzhou (DZ), Wanning
(WN), and Wuzhishan (WZS). For each plantation, leaf samples were
collected in April 2021 (during the phenological stage when leaves
appeared pale green) from infected rubber trees (diameter at breast
height: 25--35 cm) diagnosed with a Level 3 powdery mildew infection
(i.e., white spots covering more than 33\% of the leaf area of the tree)
(Qin et al., 2015).

The five-point sampling method---i.e., the diagonal line's midpoint was
first set as the central sampling point, then four equi-spaced
additional points along it were set---was applied to collect samples
from each rubber farm, using three trees per point, with four leaves
from each tree placed in one sterile bag as a sample. Three replications
were set and marked as \_1, \_2 and \_3. Uninfected leaves of the same
size (at Level 0) were collected from non-infected healthy trees using
the same method to serve as a blank control (denoted as \_CK).

The sample number, time, and place of collection, in addition to the
latitude, longitude, altitude, and ambient temperature and humidity on
the day of leaf sampling were recorded (Table S1).

\textbf{Extraction of DNA from Phyllosphere Microbiota}

\begin{enumerate}
\tightlist
\item
  First, 6.0 g of rubber leaves was transferred into a sterile conical
  flask containing 100 mL 0.1 mol/L phosphate buffer solution (pH=7.0),
  and then 100 \selectlanguage{greek}μ\selectlanguage{english}L Tween 80 was added.
\item
  Each sample was shaken with ultrasonic oscillation for 8 minutes, and
  then shaken at a speed of 200 rpm for 30 minutes at 25\selectlanguage{ngerman}°C.
\item
  After 2 minutes of ultrasonic oscillation, sterilized forceps were
  used to remove the leaves on the super-clean worktable.
\item
  The microorganisms in the conical flask were collected using suction
  filtration with a 0.45-\selectlanguage{greek}μ\selectlanguage{english}m microporous membrane.
\item
  DNA was extracted from each sample using the MP Biomedicals FastDNA\selectlanguage{ngerman}®
  Spin Kit for Soil (CA, USA).
\item
  The concentration and purity of DNA were verified using the NanoDrop
  2000C (Thermo Scientific, USA) to A260/A280 = 1.8--2.0, and stored at
  \selectlanguage{english}-20degC until use.
\end{enumerate}

\textbf{Amplification and Sequencing of 16S and Internal Transcribed
Spacer (ITS) DNA of Phyllosphere Microbiota}

Using the DNA of the sample as a template, the bacterial 16S rDNA gene
and fungal ITS genes were polymerase chain reaction (PCR)-amplified with
universal primers (Lee et al., 2012).

Primer sequences:\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
Primers & Sequences (5'-3')\tabularnewline
16S-338F & ACTCCTACGGGAGGCAGCA\tabularnewline
16S-806R & GGACTACHVGGGTWTCTAAT\tabularnewline
ITS-1F & CTTGGTCATTTAGAGGAAGTAA\tabularnewline
ITS-2043R & GCTGCGTTCTTCATCGATGC\tabularnewline
\bottomrule
\end{longtable}

PCR-amplified products were detected using 1.0\% agarose gel
electrophoresis. The ensuing products were purified and sent to Shanghai
Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China) for MiSeq
high-throughput sequencing.

\textbf{Sequence Data Processing and Statistical Analysis}

(1) The DNA matrix was calculated. The UPARSE program (Edgar, 2013) was
employed to divide the operational taxonomic units (OTUs) and cluster
all the sequences considered very similar (i.e., with a minimum 97\%
identity threshold). The RDP-Classifier software v2.11
(https://sourceforge.net/projects/rdp-classifier/) was used to classify
and annotate the sequences of each leaf sample, with the confidence
parameter set to 50\%. Microorganisms corresponding to sequences with a
genetic distance of less than 3\% are generally considered to belong to
the same microbiota (Wang et al., 2007).

(2) The data were homogenized, and the number of OTUs at different
taxonomic levels (genus and phylum) were calculated and their
rarefication curves plotted. To assess the alpha diversity of sequences
in each sample, the Chao1, Ace, Shannon, and Simpson indexes were used.

(3) Phyllosphere microbiota in leaf samples from different regions were
subjected to principal component analysis (PCA) (Gewersand et al., 2021)
and nonmetric multidimensional scaling (NMDS) multivariate analyses (the
correlations used in the PCA were linear).

(4) A Kruskal--Wallis (KW) sum-rank test was performed using the linear
discriminant analysis effect size (LEfSe) algorithm to compare the
distribution of OTUs between the leaves of rubber trees in different
regions.

\textbf{RESULTS Basic Composition and Structure of the Phyllosphere
Bacteria of Rubber Trees with Powdery Mildew}

Four samples from each site region (BS, DZ, WZS, and WN), for a total of
16 tree-level leaf samples, were subjected to MiSeq high-throughput
sequencing of the phyllosphere microbial DNA of hosts with powdery
mildew. A total of 567,903 high-quality sequence fragments were read
after processing the raw data, with the number of sequences in a single
sample ranging from 30,261 to 44,775, with an average of 35,494. A total
of 520 OTUs were detected in the four regions after implementing the
quality control protocol. Across all regions, there were 36 overlapping
OTUs, constituting 6.92\% of the total. This indicated that, although
all the samples were collected from a rubber powdery mildew phyllosphere
environment, there were significant differences in OTU levels among the
four regions (Figure 1).

The rarefication curves showed differences in the diversity of the
different sample phyla. The flattening of the rarefication curves for
each sample indicated that the amount of sequenced data was reasonably
sufficient, with a robust sequencing depth encompassing nearly all phyla
in the samples (Figure S1).

The community composition of each sample was tallied at various
taxonomic levels, and a total of 24 phyla, 49 classes, 100 orders, 172
families, and 256 genera of bacteria were identified. Apart from WZS\_3,
the other samples were dominated at the phylum level
by\emph{Cyanobacteria} , \emph{Poteobacteria} , and
\emph{Actinobacteria} . The dominant phyla in individual regions also
included \emph{Firmicutes}and \emph{Bacteroidetes} , which had different
relative abundances across regions (Figure 2-1, 2-2). Excluding WZS\_3,
in the 15 samples the relative abundance of \emph{Cyanobacteria} ranged
from 71.24\% to 98.29\%, that of \emph{Proteobacteria} from 1.55\% to
23.13\%, and that of \emph{Actinobacteria} from 0.82\% to 1.23\%. The
relative abundances of \emph{Cyanobacteria} , \emph{Proteobacteria} ,
and\emph{Actinobacteria} in WZS\_3 were 0.04\%, 28.92\%, and 10.59\%,
respectively.

The dominant genera in BS were Cyanobacteria\_norank (``norank'' is used
when there is no scientific name for this level in the taxonomic
genealogy), Mitochondria\_norank, and \emph{Rhodococcus} ; in DZ,
Cyanobacteria\_norank, Mitochondria\_norank, and
\emph{Curtobacterium}dominated; in WN, Cyanobacteria\_norank,
\emph{Pseudomonas} , and\emph{Pantoea} dominated; and in WZS,
Cyanobacteria\_norank,\emph{Rhodococcus} , and \emph{Pantoea} dominated
(Figure 2-1, 2-2). In these regions, the most dominant communities in
healthy rubber tree leaves (Level 0) consisted of Cyanobacteria\_norank,
and likewise for the dominant communities of infected leaves (Level 3).
The relative abundances (mean values) are shown in Table S2. Among
subdominant genera, the subdominant genera of both uninfected and Level
3-infected leaves in BS were Mitochondria\_norank and \emph{Rhodococcus}
; the subdominant genera in DZ were Mitochondria\_norank (uninfected
leaves) and \emph{Curtobacterium} (Level 3-infected leaves); the
subdominant genera in WN were Mitochondria\_norank, \emph{Bacillus}
(uninfected leaves), \emph{Pseudomonas} , and \emph{Pantoea} (Level
3-infected leaves); and the subdominant genera in WZS were
\emph{Rhodococcus}(uninfected leaves) and Acidobacteria\_norank (Level
3-infected leaves). The relative abundances of subdominant genera in
healthy leaves and Level 3 leaves from the four regions are listed in
Table S2.

In summary, the composition of the dominant genera varied little between
healthy leaves and Level 3-infected leaves. Although other dominant
genera were different among regions, their relative abundances were not
high. Therefore, the composition of genus-level communities of the three
levels of infected and healthy leaves of rubber trees at the same
growing site was similar, except for some differences in members'
relative abundances, while community composition at the genus level
differed markedly among regions.

\textbf{Diversity Index Analysis of Phyllosphere Bacteria of Rubber
Trees with Powdery Mildew}

The member abundance and diversity of the phyllosphere microbiome
community were studied by analyzing the diversity of individual samples
(alpha diversity) using various statistical indexes (Table S3).

The OTU statistics were analyzed at a 97\% similarity level, and the OTU
numbers for the 16 samples ranged from 24 to 324. Using the Ace index
and Chao index, the total number of species in the phyllosphere
microbiome was estimated to be 34--329 and 29--329, respectively. The
Shannon index and Simpson index estimated samples' microbial diversity
at 0.14--5.09 and 0.01--0.96, respectively. The coverage of the 16
samples exceeded 99\%, confirming that the sequencing results accurately
represented the microorganisms in rubber tree leaves. Despite their
distinct algorithms, the Ace index and Chao index generally yielded
consistent results and did not differ considerably in terms of measured
OTU numbers. Both the Shannon index and Simpson index revealed a ranking
of WZS \textgreater{} WN \textgreater{} DZ \textgreater{} BS for the
alpha diversity in the microbiota of the four regions.

\textbf{PCA and NMDS Multivariate Analyses of Phyllosphere Bacteria in
Leaf Samples from Different Regions}

PCA indicated that the microorganism composition of DZ and BS samples
was similar, likely due to their geographical proximity to each other.
The samples from WN and WZS were clearly distinguishable from each
other, except for the WZS\_3 sample, which was more dispersed but still
close to clustering (Figure 3). These results indicated that bacterial
communities differed significantly between the four regions, which
suggests that different geographical locations are influential in
accounting for the variation in community composition and structure of
phyllosphere bacteria in rubber tree leaves.

NMDS showed that, except for the WZS\_3 sample, samples that had close
geographical proximity or similar climates shared more similarities in
composition, given the clustering found (Figure 3). For example, the DZ
and BS sites are a short distance apart, and both have a dry climate,
whereas the WN and WZS sites are nearer to each other and have a wet
climate. These results further suggest that different geographical
locations or climate types can lead to the separation of distinct
microbial communities, and that samples with geographical proximity or
similar climate types can generate prominent clustering results.

\textbf{Analysis of Phyllosphere Bacteria Taxa LEfSe in Samples from
Different Regions}

A KW sum-rank test was performed using the LEfSe algorithm to compare
the distribution of OTUs between the leaves of rubber trees in different
regions. These results showed that five OTUs were distributed in BS,
three in DZ, five in WN, and 24 in WZS. \emph{Cyanobacteria} were the
most abundant taxon in BS, Oxalobacteraceae in DZ, Pseudomonadales in
WN, and both \emph{Proteobacteria} and \emph{Acidobacteria} in WZS
(Figure 4).

The plotted cladogram analysis also revealed which community taxa had
significantly different impacts on distinguishing samples by region
(Figure 5). These taxa were \emph{Cyanobacteria} in
BS,\emph{Methylobacterium} in DZ, \emph{Firmicutes} in WN,
and\emph{Proteobacteria} and \emph{Acidobacteria} in WZS.

\textbf{Correlation Analysis Between Clustering of Phyllosphere
Bacterial OTUs and Environmental Factors}

Correlations between the environmental factors (temperature, humidity,
and altitude) at each sampling location and their OTUs were calculated
and tested. The OTUs and environmental factors clustered separately
(Figure S2). These results confirmed that OTU280, OTU257, OTU146, OTU27,
OTU437, OTU196, OTU385, OTU30, and OTU510 were significantly correlated
with temperature and clustered into one large branch; OTU430 was
significantly correlated with temperature and humidity and was in this
large branch as well; and OTU144 was significantly correlated with
temperature and humidity, but was in a separate branch. Altitude had no
effect on the OTUs. Notably, OTU144 was highly correlated with
temperature and humidity, OTU196 and OTU30 were highly correlated with
temperature alone, while OTU 430 was moderately correlated with humidity
alone.

\textbf{Basic Composition and Structure of the Phyllosphere Fungal
Community of Rubber Trees with Powdery Mildew}

A total of 593,237 high-quality sequence fragments were obtained from
the 16 samples of rubber tree powdery mildew fungi via MiSeq
high-throughput sequencing. The number of sequences in a single sample
ranged from 30,129 to 44,619, with an average of 37,077, and a total of
1406 OTUs were detected. Their average sequence length was 293.01 bp,
with 57.38\% of the sequences being 301--320 bp in size and 26.99\%
being 241--260 bp. The samples' dilution curves showed differences in
their fungal diversity. The general flattening of these dilution curves
indicated that the amount of sequenced data was robust, and that the
depth of sequencing largely covered all species in the rubber tree leaf
samples (Figure S1).

A total of 1398 OTUs were detected in the four regions after quality
control, with a ranking of WZS \textgreater{} WN \textgreater{} BS
\textgreater{} DZ (Figure 1). There were 90 overlapping OTUs across the
four regions, accounting for 6.44\% of the total number of OTUs in all
pooled samples. This indicated that although the samples were all
sourced from the rubber powdery mildew phyllosphere, there were stark
differences in OTU levels among the four rubber tree-growing regions.

The community composition of each sample was calculated at different
taxonomic levels, for which a total of six phyla, 26 classes, 69 orders,
157 families, and 351 genera of fungi were identified. At the phylum
level, the community composition of samples from all four regions was
similar, with \emph{Ascomycota} and \emph{Basidiomycota} dominating,
though their relative abundances varied across regions (Figure 2-1). The
relative abundance of \emph{Ascomycota} ranged from 43.76\% to 99.80\%,
and that of \emph{Basidiomycota} ranged from 0.17\% to 10.91\% in the 16
samples (Figure 2-2).

The dominant genera in all four regions consisted of \emph{Erysiphe}
and\emph{Cladosporium} . In addition, the dominant fungal taxa of the
regions' healthy leaves differed (Figure 2-2). The dominant genera in
the Level 3 leaves of the samples from the four regions are listed in
Table S4. In addition, the healthy leaves (Level 0) and Level 3 leaves
in the four regions also included a number of less abundant community
members. The relative abundance of fungi (others) whose taxonomic status
was unclear or not yet identified ranged from 1.04\% to 10.58\% (Table
S4).

In summary, apart from WZS, the dominant fungal genera in the other
three regions for both Level 3-infected leaves and healthy leaves
consisted of \emph{Erysiphe} and \emph{Cladosporium} , with one to three
different subdominant genera per region, albeit all at low relative
abundances. Therefore, the two levels of infected and healthy leaves of
rubber trees growing at the same site differed in the relative abundance
of phyllosphere microbiome but not in the genus-level community
composition, whereas the latter varied across the four regions. Although
powdery mildew had little effect on the structure of the phyllosphere
fungal community, it did affect the relative abundance of each
community.

\textbf{Diversity Index Analysis of the Phyllosphere Fungal Flora of
Rubber Trees with Powdery Mildew}

The fungal OTU statistics were analyzed at the 97\% similarity level,
and the OTU numbers for the 16 samples ranged from 71--692. As shown in
Table S5, the Ace and Chao indexes estimated the total number of species
to be 121--723 and 120--713, respectively. Both the Shannon and Simpson
indexes indicated that the alpha diversity of fungal communities in the
leaves of the four regions was ranked as follows: WZS \textgreater{} BS
\textgreater{} DZ \textgreater{} WN.

\textbf{LEfSe Analysis of Phyllosphere Fungal Taxa in Leaf Samples from
Different Regions}

A KW sum-rank test was applied using the LEfSe algorithm to compare the
distribution of OTUs between the leaves of rubber trees in different
regions. These results revealed 11 OTUs that were exclusively
distributed in BS, three OTUs that were exclusively distributed in DZ,
22 OTUs that were exclusively distributed in WN, and three OTUs that
were exclusively distributed in WZS. \emph{Trichosphaeriales} was the
most abundant taxon in BS, \emph{Sporidiobolaceae} was the most abundant
taxon in DZ, both \emph{Dothideales} and \emph{Dothioraceae} were the
most abundant taxa in WN, and \emph{Chaetomiaceae} was the most abundant
taxon in WZS (Figure 4). The plot cladogram results also revealed the
community members that significantly influenced the delimitation of
samples in different regions (Figure 5).

\textbf{Hierarchical Clustering Tree of Phyllosphere Fungal Samples from
Different Regions}

A hierarchical clustering tree was constructed based on a beta diversity
distance matrix to compare similarities and differences among multiple
samples (Figure 6). The results showed that the community composition of
the WN\_1, WN\_2, and WN\_3 samples was similar, and clustered into a
single branch. The similarity between WZS\_1 and WZS\_2 was also high,
and both DZ\_1 and DZ\_2 clustered together. Clearly, the similarity of
the community composition of the WZS\_CK, WN\_CK, BS\_CK, and DZ\_CK
samples was not high, and the similarity with the other three samples in
the region was low, with significant differences.

\textbf{Correlation Analysis of OTU Clustering of Leaf Fungi with
Environmental Factors}

The environmental factors (temperature, humidity, and altitude) sampled
at each location were tested to determine their correlation with OTUs,
and the OTUs and environmental factors clustered separately (Figure S2).
OTU1391, OTU202, OTU953, OTU985, OTU1073, and OTU769 were significantly
correlated with temperature and humidity and clustered into one group;
OTU420, OTU419, OTU173, and OTU856 were significantly correlated with
temperature and clustered into one branch; OTU652, OTU758, OTU1289, and
OTU12 were significantly correlated with altitude and clustered into one
group; OTU223, OTU76, OTU1066, and OTU96 were significantly correlated
with altitude, forming one cluster; and OTU919 was significantly
correlated with temperature. Notably, among them, OTU76 and OTU1066 were
strongly correlated with altitude, OTU1391 was strongly correlated with
humidity, and OTU420, OTU856, and OTU1073 were strongly correlated with
temperature.

\textbf{DISCUSSION}

Much research has focused on the relative macroscopic behavior of
phyllosphere microorganisms, and on the behavior of phyllosphere
microorganisms when non-specific parasitic bacteria infest plants.
However, there are no reports on obligate parasitic bacteria. In work by
Liu et al. (2022) on the community composition of phyllosphere
microorganisms of female and male ash trees (\emph{Fraxinus} ), the core
phyllosphere microbiota was consistent, with the dominant phyla
being\emph{Cyanobacteria} and \emph{Proteobacteria} ; however, some
differences were identified at the genus level, with the
genus\emph{Arsenophonus} present in female ash only. As in the present
study, Guo (2009) collected samples from several sites and found that
the phyllosphere microorganisms of \emph{Populus tremula} mainly
consisted of bacteria, followed by actinomycetes and fungi; however, the
populations and numbers of phyllosphere bacteria differed between sites.
Recently, by analyzing the structure of the phyllosphere fungal
communities of dominant tree species in broadleaf red pine forests in
Changbai Mountains, Wang et al. (2022) found that the dominant phyla
were \emph{Ascomycota} and \emph{Basidiomycota} and the dominant classes
were \emph{Dothideomycetes} and \emph{Taphrinomycetes} , and that the
canopy phyllosphere fungal communities of the six dominant tree species
differed significantly in composition. Some researchers have also
explored the complexity in host--microbe interactions and suggested that
the rational design and use of microbial tools, such as phyllosphere
probes, have broad potential for applications in economic production
activities, such as agriculture, viticulture, forestry, and biofuels,
and even for improving human health (Whitaker et al., 2019).

Sampling was based on the fact that geographical location and its
relative environment are decisive factors in the community composition
of interstitial microorganisms. Therefore, samples were collected from
four representative areas in Hainan Province, China: WN in eastern
Hainan, WZS and BS in central Hainan, and DZ in western Hainan. Sample
WZS\_3 from Wuzhishan was markedly different when compared with sample
WZS\_1 or WZS\_2, and the sequencing results of its bacterial community
composition showed that a portion of the microorganisms came from the
soil, which might be related to the changeable climate in the field. It
was difficult to distinguish whether the samples were affected by the
nearby environment before sampling.

Only Level 3-infected leaves were collected because under field
conditions, Level 3 infections are the most common, Level 4 (entire leaf
covered with spots) infections mostly occur in greenhouse conditions,
while Level 2 (scattered spots on the surface) infections normally occur
on older leaves, or when the powdery mildew spots have faded, and only
form at the beginning or at the end of the powdery mildew period, when
the leaves age faster under higher temperatures. In addition, there were
differences in the relative abundances of the communities of Level
3-infected leaves in each region, which might be associated with the
number of environmental influences in the field. As a result, the mean
values were taken for comparison with uninfected healthy leaves (Level
0).

In this study, state-of-the-art molecular biotechnology was used to
investigate the phyllosphere microorganisms of rubber trees with powdery
mildew, to identify their dominant populations at the phylum and genus
levels, and to determine whether the incidence of powdery mildew disease
affected the phyllosphere microbial community structure and the relative
abundances of their taxa members. Because one plantation site was
sampled per region, the following inferences about regional differences
were made with caution.

\textbf{Structure and Diversity of the Phyllosphere Bacterial Community
of Rubber Tree Powdery Mildew}

The dominant community at the phylum level was \emph{Cyanobacteria} ,
with a relative abundance ranging from 71.24\% to 98.29\%. This
dominance can presumably be explained by the strong viability
of\emph{Cyanobacteria} and their strong symbiosis with some eukaryotes.
Because of its widespread presence on the leaf surface of rubber trees,
this paper speculates that genera of this bacterial phylum may have
colonized the leaf surface via wind dispersal and then multiplied
rapidly, thereby fixing nitrogen to help replenish the leaf with
nitrogen. In the long term, \emph{Cyanobacteria} has evolved in a
mutually beneficial symbiosis with host leaves, enabling it to occupy an
overwhelmingly dominant position in the phyllosphere bacterial
community. The increased nitrogen supplies more nutrition for the leaf,
which then provides a better parasitic environment for the causal agents
of powdery mildew and allows the three actors---the rubber tree
leaf,\emph{Cyanobacteria} , and \emph{Erysiphe} ---to coexist
peacefully.

The genus-level community composition and relative abundance of healthy
leaves and Level 3-infected leaves at the same site were not
significantly different, while community composition and relative
abundance at the genus level were significantly different among the four
representative regions. This could suggest that \emph{Erysiphe} had
little effect on the overall phyllosphere bacterial community structure,
though they may affect the relative abundances of the members of each
community. The correlation between OTUs and environmental factors in the
four regions demonstrated that certain OTUs were significantly
correlated with the ambient temperature and humidity, while the altitude
had a negligible influence on OTUs.

\textbf{Structure and Diversity of Phyllosphere Fungal Communities of
Rubber Tree Powdery Mildew}

The dominant phyla in all four regions were \emph{Ascomycota}
and\emph{Basidiomycota} . At the genus level, \emph{Erysiphe}
and\emph{Cladosporium} were dominant, with differing subdominant genera
between regions.

\emph{Erysiphe} was still present in healthy leaves, and so it is
speculated that they persist in healthy leaves which do not develop the
disease. Compared with these healthy leaves, the relative abundance
of\emph{Erysiphe} on Level 3-infected leaves was significantly higher in
all four sampled regions. The relative abundance of
\emph{Cladosporium}increased significantly in DZ and decreased
significantly in the other three regions. In both BS and WN, the
abundance of most fungal taxa declined as \emph{Erysiphe} became more
abundant, which suggested competitive interactions between them.

The fungal community composition and relative abundance varied
significantly at the genus level among regions; however, it was similar
between Level 3-infected and healthy leaves within the same region. This
suggested that powdery mildew did not affect the structure of fungal
communities but only the relative abundance of taxa members in each
community.

The taxonomic status of many bacteria and fungi in this study has not
been identified, so further analysis of the specific relationships
between powdery mildew and these taxa is challenging. Advances in
biotechnology tools will eventually lead to the development and
utilization of these difficult-to-cultivate microorganisms, enabling
further research.

\textbf{Innovation}

1. Studies on rubber tree powdery mildew infections and the causal
pathogenic bacteria are common in the literature. However, research
using high-throughput detection techniques to determine the dominant
taxa in the community of phyllosphere microorganisms on rubber trees
with powdery mildew, and the effect of powdery mildew on these
phyllosphere microorganisms, have not yet been reported. This study did
so for the first time in order to provide data support for more
effective new ideas for the biocontrol of powdery mildew in rubber tree
plantations.

2. Most previous reports investigated the relationship between powdery
mildew and hosts from a molecular perspective, while this work assessed
the influence of pathogenic bacteria on the phyllosphere microorganisms
of host leaves from a relatively macroscopic perspective. The results
confirm that there is little, if any, difference between the
phyllosphere microorganism populations of diseased leaves (Level 3) and
healthy leaves at the same plantation site. Based on this finding, it
can be inferred that phyllosphere microorganisms may exist in a
satisfactory symbiotic relationship with the host plant as well as its
pathogenic bacteria. The findings of this study can also confirm, from a
fresh perspective, that \emph{Erysiphe} is a obligate parasitic fungi.
In the hostile phyllosphere environment, phyllosphere microorganisms
need to maintain robust symbiotic associations with hosts and pathogens
to survive and evolve, thus leading to a relatively stable evolutionary
relationship between rubber trees, \emph{Erysiphe} , and their attached
phyllosphere microorganisms in tropical and subtropical regions. In the
future, this research team will further investigate the interactions
between the host, host pathogens, and phyllosphere microorganisms.

3. Few studies have evaluated the effects of foliar pathogens on the
phyllosphere microbial community before and after plant infestation, and
even fewer studies have examined the impact of obligate parasitic fungi
on phyllosphere microorganisms. For example, Dai (2022) investigated the
microbial diversity of tobacco leaves infested with
\emph{Streptomyces}and concluded that the relative abundance of
\emph{Alternaria} in healthy leaves increased from the first to the
third collection, while the relative abundances of \emph{Pseudomonas} ,
\emph{Sphingomonas} , and\emph{Methylobacterium} from the same location
increased as leaves aged. Huang et al. (2021) reported on the
phyllosphere microbial composition and diversity of tobacco leaves
infested with subseptate strains of\emph{Phytophthora} spp. and found
that the relative abundances of\emph{Didymella} and \emph{Boeremia}
(\emph{Ascomycota} ) fungi and\emph{Pseudomonas} and \emph{Pantoea}
(\emph{Ascomycota} ) bacteria were higher in diseased leaves than in
healthy leaves, with healthy tissue harboring a richer and more diverse
fungal community. The above-mentioned studies uncovered consistent
changes in the abundance and species of microorganisms in the
phyllosphere after the pathogenic infection of their hosts. The present
study is the first to gauge the effect of the powdery mildew's obligate
parasitic fungi,\emph{Erysiphe} , on the phyllosphere microorganisms of
rubber trees in representative plantation areas in China.

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\textbf{Figure legends}

\textbf{Fig. 1. Venn diagram illustrating the number of unique and
shared OTUs (operational taxonomic units) from the bacterial (a) and
fungal (b) community in the phyllosphere of rubber trees}

a. A total of 520 OTUs were detected in the four regions: 102 OTUs in
BS, 113 OTUs in DZ, 81 OTUs in WN, and 479 OTUs in WZS. The proportions
of unique OTUs in the four regions were as follows: 3.27\% in BS, 1.54\%
in DZ, 0.77\% in WN, and 67.69\% in WZS. Across all regions, there were
36 overlapping OTUs, constituting 6.92\% of the total.

b. A total of 1398 OTUs were detected in the four regions: 420 OTUs in
BS, 295 OTUs in DZ, 500 OTUs in WN, and 875 OTUs in WZS. The proportions
of unique OTUs in the four regions were as follows: 11.09\% in BS,
1.93\% in DZ, 13.23\% in WN, and 44.49\% in WZS. There were 90
overlapping OTUs across the four regions, accounting for 6.44\% of the
total number of OTUs in all pooled samples.

This indicated that although the samples were all sourced from the
rubber powdery mildew phyllosphere, there were stark differences in the
OTU levels among the four regions.

\textbf{Fig. 2-1. Heat maps of the relative abundances of bacterial and
fungal community members in the rubber phyllosphere at the phylum and
genus level}

Blue blocks indicate high correlation, green blocks indicate medium
correlation, and the lighter-colored blocks indicate low correlation.

a. Heat map of the relative abundance of bacterial community members in
rubber phyllosphere at the phylum level.

b. Heat map of the relative abundance of bacterial community members in
rubber phyllosphere at the genus level.

c. Heat map of the relative abundance of fungal community members in
rubber phyllosphere at the phylum level.

d. Heat map of the relative abundance of fungal community members in
rubber phyllosphere at the genus level.

\textbf{Fig. 2-2. Relative abundances of bacterial and fungal community
members in the rubber phyllosphere at the phylum and genus level}

a. The relative abundance of bacterial community members in rubber
phyllosphere at the phylum level.

b. The relative abundance of bacterial community members in rubber
phyllosphere at the genus level.

c. The relative abundance of fungal community members in rubber
phyllosphere at the phylum level.

d. The relative abundance of fungal community members in rubber
phyllosphere at the genus level.

\textbf{Fig. 3. Principal component analysis (PCA) and non-metric
multi-dimensional scaling (NMDS) plots of the bacterial community in the
rubber phyllosphere}

a. PCA plot of the bacterial community in the rubber phyllosphere. PC1
contributed the most significantly (91.93\%), whereas PC2 explained just
4\% of the variation.

The DZ and BS samples (closer geographically close) are clustered
together in the PCA, while the WN and WZS samples (farther
geographically) can be clearly distinguished from them. There are
significant differences in bacterial communities among the different
regions.

b. NMDS of the bacterial community in the rubber phyllosphere. Except
for WZS\_3 samples, samples with a closer geographical distance or
similar climate type had higher composition similarity and tended to
cluster together.

\textbf{Fig. 4. Linear discriminant analysis effect size (LEfSe) of
differences in bacterial and fungal OTUs in the rubber tree phyllosphere
in different regions}

a. LEfSe of differences in bacterial OTUs in the rubber tree
phyllosphere in the four sampled regions.

b. LEfSe of differences in fungal OTUs in the rubber tree phyllosphere
in the four sampled regions.

The threshold on the logarithmic LDA score for discriminative features
was set to 2.0. BS = Baisha, DZ = Danzhou, WN = Wanning, WZS =Wuzhishan.

\textbf{Fig. 5. Analysis of bacteria (a) and fungi (b) with significant
effects in different regions}

The plotted cladogram results revealed those community members which
significantly influenced the delimitation of samples in the four
regions.

Different circles represent different classification levels. Levels from
the inside to the outside represent phylum, class, order, and family in
turn. Yellow nodes are groups that have no important role, and other
color nodes are groups that play an important role in the corresponding
region.

\textbf{Fig. 6. Hierarchical clustering tree of the fungal community in
the rubber phyllosphere}

The branch length represents the phylogenetic distance between samples;
the more similar the samples, the closer they are positioned to each
other. Branches with the same color represent the same location of
sampled rubber leaf tissue.

\textbf{Competing Interests Statement}

The authors declare no conflict of interest.

\textbf{Author Contributions}

\textbf{Weiguo Miao:} Conceptualization (lead); writing -- review and
editing; Resources. \textbf{Jiaxin Shan:} Writing -- original draft
(lead); Writing -- review and editing (equal); Investigation (equal);
Data Curation (equal). \textbf{Hua Wu:} Writing -- original draft
(equal); Investigation (equal); Data Curation (equal). \textbf{JinYao
Yin:} Writing -- review and editing (equal); Methodology
(equal).\textbf{Xiao Li:} Formal Analysis (equal); Methodology
(equal).\textbf{Chunhua Lin:} Resources (equal).

\textbf{Acknowledgements}

This study was financially supported by the Hainan Province Science and
Technology Special Fund (No. ZDYF2021XDNY142 YSPTZX202018); the National
Natural Science Foundation of China (NSFC, No. 31660033); the Hainan
Provincial Natural Science Foundation of China (No. 321RC470); and the
Hainan Yazhou Bay Seed Laboratory (No. B21HJ0905). We thank LetPub
(www.letpub.com) for linguistic assistance and pre-submission expert
review.

\textbf{Data Availability Statement}

This manuscript has no associated data.

\textbf{Hosted file}

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