Plant Science 193–194 (2012) 96–102
Contents lists available at SciVerse ScienceDirect
Plant Science
journal homepage: www.elsevier.com/locate/plantsci
Review
Novel techniques and findings in the study of plant microbiota: Search for plant
probiotics
Aleš Berlec ∗
Department of Biotechnology, Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia
a r t i c l e
i n f o
Article history:
Received 16 January 2012
Received in revised form 11 April 2012
Accepted 20 May 2012
Available online 26 May 2012
Keywords:
Plant-associated microbiota
Microbial composition
Culture-independent methods
Metagenomics
a b s t r a c t
Plants live in intimate relationships with numerous microorganisms present inside or outside plant
tissues. The plant exterior provides two distinct ecosystems, the rhizosphere (below ground) and the phyllosphere (above ground), both populated by microbial communities. Most studies on plant microbiota
deal with pathogens or mutualists. This review focuses on plant commensal bacteria, which could represent a rich source of bacteria beneficial to plants, alternatively termed plant probiotics. Plant commensal
bacteria have been addressed only recently with culture-independent studies. These use next-generation
sequencing, DNA microarray technologies and proteomics to decipher microbial community composition and function. Diverse bacterial populations are described in both rhizosphere and phyllosphere
of different plants. The microorganisms can emerge from neighboring environmental ecosystems at
random; however their survival is regulated by the plant. Influences from the environment, such as pesticides, farming practice and atmosphere, also affect the composition of microbial communities. Apart
from community composition studies, some functional studies have also been performed. These include
identification of broad-substrate surface receptors and methanol utilization enzymes by the proteomic
approach, as well as identification of bacterial species that are important mediators of disease-suppressive
soil phenomenon. Experience from more advanced human microbial studies could provide useful information and is discussed in the context of methodology and common trends. Administration of microbial
mixtures of whole communities, rather than individual species, is highlighted and should be considered
in future agricultural applications.
© 2012 Elsevier Ireland Ltd. All rights reserved.
Contents
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Plant-associated microbiota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Established mechanisms of action of plant-associated microbiota and their applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Application of new techniques in the study of plant-associated microbiota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Recent findings on plant-associated microbiota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Lessons to be learned from human studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
1. Plant-associated microbiota
Microorganisms can be found in almost all ecological niches.
Plants can provide a variety of nutrients and are therefore attractive hosts for microorganisms. Microorganisms are found on plant
surfaces (epiphytes) or inside plant tissues (endophytes) [1]. Plants
provide three markedly different environments for the microbiota. The first is the rhizosphere, where microorganisms are
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http://dx.doi.org/10.1016/j.plantsci.2012.05.010
associated with roots or with soil, which is under the influence
of plant and contains numerous plant exudates [2]. The second
is the endosphere, inside plant tissues [3]. The third is the phyllosphere which encompasses the surface of stem and leaves. The
phyllosphere is considered a hostile environment for microorganisms, since the availability of nutrients is limited, exposure
to sun irradiation is strong and water availability varies [4].
Despite those conditions, the phyllosphere hosts a microbial population of remarkable complexity, as has been recognized for more
than a decade [5]. Plant-associated microorganisms are generally
considered as pathogens, mutualists or commensals. Pathogens
have been the most thoroughly studied due to their economical
A. Berlec / Plant Science 193–194 (2012) 96–102
importance. They account for most of the knowledge gathered on
plant-associated bacteria [6]. Mutualists benefit the plant; rhizobial associations of leguminous plants and nitrogen-fixing bacteria
are an example [7]. This review will focus mostly on commensals which, by definition, provide no obvious harm or benefit to
the plant. However, some recent studies will be presented that
show that the commensals are not only a random collection of
environmental passersby, but are regulated by the plants [8–10].
Some studies also show that commensal diversity is relatively constant (even at different geographical locations) and different from
that of neighboring ecosystems [10], while this is not true for the
genus Methylobacterium [11] and the community of Tamarix tree
[12], which were shown to be site determined. Microorganisms are
also passed from generation to generation of plants and not just
through environmental exchange [13]. I propose that commensals
can have an activity beneficial to plants; however the mechanisms
by which they act are yet unknown. They could constitute a rich
source of plant-beneficial microorganisms. Commensal action is
largely dependent on the status of the plant and the stresses to
which it is subjected. The plant itself can, under specific conditions,
benefit from the vast pool of microbial genes and proteins, which
may provide a competitive advantage. Therefore it is a rational
strategy to harbor a large diversity of microbiota. The array of plantassociated microorganisms can also influence the plant evolution,
as described by the hologenome theory, which treats the organism
and its microbiota as a unified subject in evolution [13,14].
2. Established mechanisms of action of plant-associated
microbiota and their applications
The effects of microorganisms on plants are well established
for several microorganism–plant pairs, and interference with plant
health and growth has been reported [15–18]. Beneficial microbiota can compete with pathogens for space and nutrients, or
produce microbicidal agents and thereby improve plant health.
Another way of influencing plant health is to improve its stress
tolerance; bacteria can, for example, increase the ability of plants
to resist frost injury by competing with ice nucleation bacteria [4].
Microorganisms affect plant growth by manipulating plant regulatory pathways, by the production of plant growth hormones, and by
increasing the availability of nutrients from the environment [18].
In order to explain these mechanisms of action, a complex
interaction between microbiota and plants can be envisaged. Even
though the nature of such interactions is very diverse, they are
all based on the exchange of chemical signals (i.e., metabolites,
substrates. . .) between the two partners. As a result of the interaction, partners acquire new traits and properties [19]. Co-evolution
of plants and microbiota is also evident on the genetic level. Genes
of individual species evolve in response to the genes of the partner
species, a phenomenon that can be described as symbiogenetics
[19]. Plants have adapted to hosting microbiota and provide suitable niches for microbial colonization. Microbial genes and their
products can enable plants to by-pass the evolution of plant’s own
genes, e.g., for new metabolic pathways. This mechanism can also
be considered as a partial substitution for sexual genetic integration
[19], or even horizontal gene transfer.
Individual microbial strains that are part of the plant-associated
microbiota can be used in agriculture and in ecosystem management (phytoremediation) and several reviews have recently been
published on that topic [15,17,18,20,21]. Microorganisms that can
exert beneficial effects on plants could be, in analogy to humans,
termed plant probiotics. Some general requirements for a microorganism to be beneficial (probiotic) have been suggested [18]. The
ability to readily colonize the plant is a prerequisite for potential
commercial application. Additionally, the microorganism should
97
exert beneficial effects on crops but not on weeds and should not
make plants more susceptible to biotic or abiotic stresses [18].
Plant probiotics could be used to reduce the use of chemicals
(fertilizers, pesticides) in agriculture. This could lead to improved
quality at reduced costs and could provide the basis for a more
sustainable agriculture [21]. Patents and potential applications of
beneficial endophytes have recently been reviewed, focusing on
their growth and stress tolerance [20]. In a review of plant growthpromoting rhizobacteria, individual species are described, together
with their mechanisms of action and potential applications [15]. A
few species of genus Pseudomonas are applied commercially for
the prevention of fungal diseases, bacterial disease fire blight and
mild frost injury [22]. Although Gram-negative bacteria receive
most attention, Gram-positive bacteria also play an important role
[17]. Plant-associated gram-positive bacteria belong to phyla Firmicutes and Actinobacteria and can also exert beneficial effects. In
addition, their property of forming spores can be a technical advantage in formulation development (dry powder) and in effective
delivery to plants [17]. Several reviews address the problem of the
reproducibility of beneficial results in field studies [15,16], which
currently limits broader usage. Inability to colonize plant tissues to
a sufficient level or variable environmental conditions have been
suggested as possible reasons [15,16].
3. Application of new techniques in the study of
plant-associated microbiota
The study of plant-associated microbiota has traditionally been
focused on single, culturable bacterial species and their interaction with plants. This approach provides valuable data but is
of low throughput and neglects the bacteria that are unable to
grow in culture. Culture-independent techniques started with
direct cloning of the environmental DNA [23]. Several PCR-based
techniques have been developed to provide information on the
community composition (reviewed in [24]). The latter can be
deduced from the different patterns of amplified DNA separated by various electrophoretic approaches. The information can
be upgraded by excising and sequencing the bands of interest. PCR-based techniques include restriction fragment length
polymorphism (RFLP), terminal restriction fragment length polymorphism (T-RFLP), single strand conformation polymorphism
(SSCP), denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE), and have already
been applied in plant-associated microorganism community studies [25–29]. PCR-based methods suffer the drawbacks of PCR
amplification, including sensitivity to inhibitory compounds, sensitivity to template concentration, primer mismatch sensitivity,
variable amplification efficiency, etc. [24]. PCR-based methods also
do not provide information on the quantity of an individual DNA in
the original sample [24].
Contemporary culture-independent techniques are PCRindependent and are aimed at high-throughput, good
reproducibility of the results and cost-effectiveness. The development of next-generation sequencing techniques has enabled
the acquisition of a vast amount of nucleotide sequence data on
un-culturable organisms at a relatively low price [30,31]. In parallel
with sequencing technologies, new software, e.g., QIIME [32], has
been developed to handle the data obtained. This has given a
boost to metagenomics or community genomics [33], the specific
genomics of a community of organisms that dwell in a specific
ecosystem. The result is a metagenome, where individual genes
are not necessarily annotated to individual organisms, but belong
to the community of the ecosystem in question. Metagenomics
can provide information on the phylogeny of organisms in a particular ecosystem, their heterogeneity and evolution. Functions of
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A. Berlec / Plant Science 193–194 (2012) 96–102
corresponding proteins can be guessed at, on the basis of homology. Assembling nucleotide reads into a contiguous sequence can
identify neighboring genes—gene clusters. Enzymes of pathways
for small molecule biosynthesis can be putatively identified and
new small-molecule products predicted (e.g., antibiotics) [33].
To obtain reliable metagenomic data, construction of a good
metagenomic library is of great importance. Advances in the
metagenomics of plant-associated microorganisms have been
made recently, especially in enriching microorganisms from plant
tissues [34]. Further improvement of the techniques for the preparation of DNA samples that are representative of the community is
needed. Further, the increase of throughput and the decreased cost
of nucleotide sequencing has made the data analysis a limiting step
in the metagenomics. Handling of vast amount of data requires
an increase in computational resources and improved algorithms.
Ideally, a metagenome would represent a complete reconstruction of all the genomes in the community, which is currently
unattainable due to limiting sequencing capacity and difficulties
with DNA isolation and recovery, particularly from species with
low abundance [35]. Ignorance of the size of the metagenome
prevents calculation of the coverage, i.e., representativity of the
data. Recently determined metagenomes therefore constitute only
a random subset of the genomes in the sample [36].
Metagenomics can be combined with stable-isotope probing
(SIP) to provide functional data on the metabolic activity of individual microorganisms in the community [37]. Only some members
of the community can metabolize isotope-labeled substrate and
incorporate it into their DNA, which can in turn be separated by
ultracentrifugation. The technique can be exploited for the search
of novel enzymes and bioactive compounds [37]. In plants, SIP can
help to identify plant-associated microorganisms that actively use
plant metabolites, as in the case of rice rhizosphere methanogenic
archaea [38].
Next-generation sequencing has, to a certain extent, already
replaced the DNA microarray technology [39]. The latter has
nevertheless been applied successfully in the study of microbial
community composition, in the form of a high-density 16S rRNA
microarray termed PhyloChip [40] which was also used in the study
of plant-associated microbiota [41]. The microarray can indicate
only the presence or absence of specific species in the sample. Properties of specific species, their genomes and protein functions need
to be evaluated by other methods.
Proteomics is another research field that has seen a great
advance in recent years. Classic separation of proteins by
two-dimensional polyacrylamide gel electrophoresis has been
improved by the introduction of fluorescent protein dyes in difference gel electrophoresis (DIGE) [42]. A further improvement
is the introduction of shotgun proteomics, in which proteins are
separated chromatographically, e.g., by a combination of cationexchange and reverse-phase chromatographies, as in the case of
multidimensional protein identification technology [43]. Separated
proteins are in all cases identified by (tandem) mass spectrometry.
New tools allow automated identification of unknown peaks by
combining the information from mass spectrometry fragmentation
patterns, isotope ratios and biochemical databases. Similarly to the
genomic approach, proteomics can also be applied to community
samples, resulting in so-called metaproteomics [44]. Proteomics
provides valuable information on the expressed proteins and not
just on the presence of genes. Expression of proteins can be monitored under various environmental conditions and differences can
be evaluated. However, the quality of the data depends on the
available genomic data, which is necessary for protein identification. Similarly, information on protein function depends on the
data obtained with other techniques or on homology-based predictions. Other -omics technologies, such as transcriptomics and
metabolomics could also be applied; the former would give an
insight into the genes that are actually expressed in the community
under study [45] and the latter would be particularly important for
understanding the communication between plant and microbiota.
Culture-independent techniques constitute a major breakthrough in the study of un-culturable bacteria. However, they
have certain limitations and cannot completely replace culturedependent techniques. These limitations include the inability to
assemble genomes of low frequency species, lack of data on community dynamics, difficulties with data interpretation due to large
natural community variations, difficulties with discerning interand intra-species differences and lack of functional data [46].
The last drawback is highly significant in establishing the role of
un-culturable bacteria. It may be circumvented by recombinant
expression of particular genes or gene clusters in culturable strains,
or by the study of homologous proteins. New approaches to culturing are still being pursued. They include the design of new growth
media with low nutrient levels and removal of potentially growthinhibiting compounds, prolonged incubation periods at relatively
low temperatures and consideration of obligate growth in bacterial
communities [46]. Some advances have already been made in culturing Archaea from the rhizosphere [47]. Future work will focus on
culturing Acidobacteria, Verrucomicrobia and Planctomycetes, which
have currently been described only by culture-independent methods [46].
4. Recent findings on plant-associated microbiota
The novel techniques described in the previous section have led
to some new findings on plant-associated microbiota, mainly on
microbial community composition. A representative set of such
studies will be presented. Of those, only a few studies are aimed
at identifying genes or species with defined function. Community
composition studies can be divided into (a) studies that compare
microbial populations of different plant species or plant parts, (b)
studies that assess the impact of external/environmental factors on
microbial community composition, and (c) studies that assess the
impact of the plant host on microbial community composition.
The bacterial community compositions in the phyllosphere of
56 tree species have been described and compared with the use
of the bar-coded pyrosequencing technique [10]. High levels of
bacterial diversity on individual trees were observed but total
bacterial abundance was similar in different tree species. Great
variability in community composition was observed between different species of trees. In contrast, trees from the same species had
similar community compositions, even if they grew at different
geographic locations. This indicates a strong and active influence
of plants on their phyllospheric bacterial composition. Plant influence was found largely to surpass the influence of the environment,
since community compositions of the air or neighboring plants are
markedly different, thus refuting the theory of simple transfer of the
bacteria from the surroundings. This, however, cannot be generalized, since the composition of phyllosphere microbiota of Tamarix
was found to be strongly influenced by the geographical location
[12].
In a similar study, the bacterial and fungal communities in the
rhizosphere and the endosphere of the tree Populus deltoides were
compared [9]. Endosphere communities were more variable from
sample to sample than those of the rhizosphere. However, all samples of endosphere communities were less diverse than those of the
rhizosphere, containing fewer different species. It was concluded
that the endosphere community is not just a subset of the rhizosphere, which again negates simple transfer from the environment,
and suggests more complex regulation. The opposite was found for
the rhizosphere composition of Carex arenaria, which is determined
by the composition of the surrounding bulk soil [48].
A. Berlec / Plant Science 193–194 (2012) 96–102
A new “metaproteogenomics” approach was introduced
whereby metagenomic data served as the basis for protein identification by mass spectrometry [8]. The phyllosphere bacterial
communities of soybean, clover, and Arabidopsis thaliana were
studied. High consistency of the communities between plants
species was observed, at least in terms of dominant genera, with
few changes over time. However, the variability of the communities
was lower than that in other environmental studies. The communities were dominated by alphaproteobacteria in all three plants,
with families of Sphingomonadaceae and Methylobacteriaceae in
particular. This observation was supported by proteomic data,
where the findings of broad substrate specific receptors TonB for
Sphingomonadaceae and of methanol utilizing enzymes for Methylobacteriaceae indicate the bacterial plant adaptation strategy [8].
Data obtained by proteomics on functions of specific proteins
extends the scope of the study from community composition to
identification of niche-specific genes. The use of the metagenome
for the identification of proteins by mass spectrometry is an important advance in the field; however the use of a metagenome from
a specific plant species for the protein identification in other plant
species [8] may be somewhat limited.
A few recent studies have addressed the influence of various
environmental factors on the composition of plant-associated communities. The impact of irrigation of tomato plants, with either
surface or ground water, on community composition of tomato
fruits was estimated [49]. Even though the bacterial composition
of surface and ground waters differed markedly, no significant
differences could be observed on the fruit surface; beta-, alphaand gamma-proteobacteria predominated under both irrigating
regimes. In a similar study, the influences of organic and conventional farming on the community composition of leaves and fruits
of apple tree were compared [50]. In contrast to the previous study,
significant differences were observed at the majority of time points;
however no human disease-causing bacteria were detected with
either regime.
The insecticide cypermethrin influences the phyllosphere community composition of cucumber, by increasing the total amount of
bacteria (predominantly Gram negative) and decreasing the number of fungi, suggesting that the insecticide serves as a nutrient for
certain Gram negative bacteria [27]. More detailed phylogenetic,
and possibly proteomic studies, should be performed to substantiate these results. The cucumber phyllosphere community was again
studied in relation to fungal infection of powdery mildew [26].
Infection caused an increase in total bacterial population, community diversity and structure. Similar observations on infection were
made with Japanese spindle (Euonymus japonicus); however the
changes included bacterial species different from those observed
on cucumber [26]. This indicates that the community response
to infection is plant specific. Livestock grazing was another factor observed to influence the microbial community of the grass
rhizosphere soil [51]. However, grazing intensity influenced total
bacterial biomass but not the diversity.
The influence of increased concentrations of atmospheric CO2 ,
as a consequence of environmental change, was estimated on
the rhizosphere communities of maize and soybean as model
plants [52]. Simulated increases in CO2 concentration affected
the composition of the archaeal community of soybean rhizosphere, but not the total archaeal abundance. This was not
observed in maize, which may be the consequence of the fact that
increased CO2 concentration does not influence photosynthesis in
maize [52].
To summarize, external factors can influence microbial communities to varying degrees. The influence is either direct or indirect
via the plant. Bacterial transfer, e.g., through irrigation or rain
splash, can occur, but the bacterial persistence is plant regulated
and species-dependent.
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Plant-associated bacteria can be strongly influenced by the
plants themselves. This can be observed by genetic modification
of the plant. Generation of soybean plants with no nodulation,
nodulation or hyper-nodulation genotypes resulted in the shift of
stem-associated bacterial diversity [53]. Genera Aurantimonas and
Methylobacterium were most strongly affected by the nodulation
phenotype. The mechanism of regulation is not known, but is probably influenced by the nutrient status of the plant [53].
The established route by which plants exert their influence
on the associated microbiome is through secretory compounds,
most often products of secondary metabolism. The regulation
of the rhizosphere microbiome is achieved through root exudates. In the model plant Arabidopsis thaliana, the root secretion
of malic acid attracts the beneficial bacterium Bacillus subtilis
FB17 in a dose-dependent manner [54]. Root exudates of eight
Arabidopsis ecotypes, which differ in their genetic content by
several percent [55], were compared by HPLC, and significant
differences in the compounds identified were observed. Root exudates influence the composition of the rhizosphere microbiome,
since different Arabidopsis ecotypes were shown to support microbiomes of different compositions and abundance in a reproducible
manner [25].
The majority of the studies of plant associated bacteria focus
on the community composition and abundance in general. Community composition studies at best provide information on
the representation of certain phyla and genera, but without
any specific implications. They are important in providing the
proof-of-principle that various factors influence the microbiome
composition. However, community studies that identify microbial
species or genes with specific functions are scarce. Besides the previously described metaproteomics study, which encompasses both
community composition and functional data [8], a recent metagenomic study of phyllospheres of tamarisk, soybean, A. thaliana,
clover and rice, identified microbial rhodopsins in the phyllospheres of all tested plants [56]. Microbial rhodopsins are similar
to animal rhodopsins, which are transmembrane proteins responsible for the perception of light in the retina. Microbial rhodopsins
serve as light-driven proton pumps in aquatic microorganisms, but
had not previously been described in terrestrial microbial habitats [57]. The rhodopsin absorption spectrum does not overlap that
of chlorophyll, and the bacteria therefore do not interfere with
photosynthesis. Rhodopsins could not be detected in rhizosphere
samples, indicating that they may be an adaptation of the leaf
microbiota [56]. It is not clear whether microbial rhodopsins could
be of benefit to the plant; one possible mechanism could, however,
be the masking of green light which can have a negative impact on
plant growth [56,58].
An important advance in identifying functional microbial
species from the plant-associated microbiome has recently been
achieved [41]. DNA microarray and metagenomic approaches were
used to study the microbial diversity of disease-suppressive soil.
The term disease-suppressive soil has been used to describe the
phenomenon that, in certain types of soil, crop plants suffer less
from soil pathogens [59]. This has been attributed to other resident microorganisms, since sterilization of the soil results in
loss of the suppressive effect. Several bacterial taxa were linked
to the disease-suppressive effect, most profoundly Pseudomonadaceae, Burkholderiaceae, Xanthomonadales and Lactobacilaceae.
A specific focus on the role of Pseudomonadaceae in suppressing the pathogenic fungus Rhizoctonia solani from infecting sugar
beet plants has resulted in the identification of a single Pseudomonas strain that could prevent infection by itself. It encodes
a non-ribosomal peptide synthetase, which was necessary for the
preventive activity and is presumably responsible for the production of a chlorinated lipopeptide [41]. The involvement of multiple
taxa in soil-suppressiveness indicates that the latter is usually not
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A. Berlec / Plant Science 193–194 (2012) 96–102
the consequence of a single strain, but rather of microbial consortia
in which microorganisms act synergistically [41].
The studies that we summarize indicate that the novel techniques have already contributed to new findings in the study of
plant microbiota, mostly by comparing community compositions
and, to a lesser extent, by providing new functional information.
5. Lessons to be learned from human studies
Detailed studies of plant microbiota, using culture-independent
and high-throughput techniques, are in progress and have already
produced exciting results, as described in previous sections. However, turning attention towards better established host-microbiota
systems, in which more studies have been conducted, may give
interesting insights. The human microbiome has received the most
research attention and could serve as a model for microbial community studies. Among other human microbiome studies, a set
of 178 reference microbial genomes has been determined [60].
Metagenomic sequencing of human gut microbiota from more than
a hundred individuals resulted in the determination of 3.3 million
non-redundant microbial genes [61]. Humans and plants obviously constitute completely different habitats and host unrelated
communities, which prevents any direct comparison. Despite that,
experience from human microbiome studies could be transferred
to plant research and could result in more efficient study design.
High inter-individual variation in microbial composition has
been observed in human studies. Sufficiently large samples were
therefore introduced [61] to obtain representative population data.
Larger samples should also be considered in plant studies. A substantial collection of reference genomes should be determined to
provide a solid basis for gene annotation. The minimal microbial
genome (set of genes required for survival in the ecosystem) and
minimal metagenome of the community (set of genes required for
normal homeostasis of the ecosystem) for a particular plant habitat
would help understand plant–microbiome interaction.
There are several research models that could be introduced
in plant microbiome research. Sterile plants could demonstrate
the overall impact of microbiota on plant functions. Gnotobiotic
conditions were used, e.g., to study the protective effect of Sphingomonas strains against infection with Pseudomonas syringae in
A. thaliana [62]. Comparison of microbiomes of healthy plants and
plants suffering from a disease could point to a possible intervention approach. This has already been recognized in a recent study of
disease-suppressive soil [41]. The study of knock-out mutant plants
would be necessary for deciphering the plant–microbial interactions.
Some parallels can be drawn between certain human and plant
microbiome studies. In humans, the microbiota is not a random collection of microorganisms from the environment. Despite
large variability between the microbiota of different individuals,
there are core microorganisms and genes that are usually present
(minimal metagenome) [61]. There is also relatively little temporal variability in a defined niche in a particular individual [63].
Nevertheless, microbial composition can be altered under certain
environmental influences, such as age, diet, hygiene or the use of
antibiotics [64–66]. Similar trends can be observed in plants. To
briefly repeat, the composition of microbiota of individual plant
has been shown to be relatively constant, which shows strong
regulation by the host [10]. In plants also, a number of environmental influences have been shown to affect the composition of
microbiota. These include agriculture (type of farming, grazing,
pesticides), climate change or severe infection, and were discussed
above [26,27,49–52].
There are several other provocative parallels between human
and plants that come in mind. The first are changes in modern
human lifestyle that include a rich diet with a lot of fat, exposure to numerous industrial chemicals and high hygiene standards;
these are all reflected in altered composition of microbiota. A plant
analogue of the modern lifestyle is agronomy, with pesticides, fertilizers and monocultural growth, conditions that differ from those
in the wild and could also influence microbiota. Studies of the
microbiota of “wild” (not domesticated) plant counterparts could
therefore provide a valuable resource of potentially beneficial commensals.
The second parallel is the use of antibiotics in the treatment of
infectious diseases in humans [65]. Antibiotics, as a side effect, act
detrimentally on beneficial bacteria and create room for pathogens.
Antibiotics are seldom used in plant protection, and their application is limited to streptomycin and oxytetracycline in the US [67];
however, a similar negative impact is anticipated. Pesticides are
not directed against plant microbiota, but can still influence their
growth. For example, herbicides can affect soil microbial diversity
and fungicides can target beneficial fungi in soil [68]. Antibiotics are
also frequently applied in farming as part of animal feed. It would
be important therefore to assess the joint impact of herbicides and
antibiotics on microbial diversity. The environmental influence of
the farm use of antibiotics has already been demonstrated by the
transfer of antibiotic resistance genes from animal manure bacteria
to soil bacteria [69].
The third parallel is in a general shift of focus from single
bacterial strains to bacterial communities. Changes in microbial
community composition can have a negative impact on the host.
Specific subpopulations of microbiota (clusters) could be linked to
a disease and potentially used in diagnostics [70]. Several human
diseases have been linked to perturbations in composition of
microbiota, including inflammatory bowel disease, obesity, atopic
diseases and some cancers [71]. The ability to restore normal microbiota has been used successfully in therapy. Clostridium difficile
intestinal infection has been successfully eradicated by the transplant of microbiota from a healthy donor [72]. The changes were not
simply transitional but relatively long-lasting. Obesity is another
condition in which significant differences in community composition between obese and lean individuals have been observed. It was
successfully managed by manipulation with intestinal flora [73].
This treatment strategy may also apply to plants. Administration
of entire bacterial communities should be considered, as a sort of
plant probiotic mixture.
Not only microorganism–host interactions are important, but
also microorganism–microorganism interactions. The extent of
horizontal gene transfer in the human microbiome has been
assessed [74]. An extensive network of more than 10,000 transferred genes in more than 2000 bacterial genomes has been
described. The transfer occurs preferentially between bacteria
in the same ecological niche. Transfer between phylogenetically
related neighboring bacteria from different ecosystems is less
likely.
Next to administration of microorganisms, other ways of interfering with microbiota composition should be taken into account.
The first is the use of new, specific antibiotics, but this is less likely
to receive general acceptance as it would contribute to the spread
of antibiotic resistance, similarly to the farm use of antibiotics.
The second is the introduction of compounds that would stimulate
the growth of beneficial microbiota, rather than the introduction
of bacteria themselves. By analogy with humans, these would be
plant prebiotics. This is a completely unexplored field that deserves
attention.
We speculate that studies of plant microbiota could well
result in the introduction of novel agricultural practices based on
plant probiotics and microbial community management. Further
advances in nucleotide sequencing techniques and further lowering of costs could enable accessible and relatively inexpensive
A. Berlec / Plant Science 193–194 (2012) 96–102
monitoring of microbial communities. This could result in tailoring
agricultural interventions to specific fields, analogous to personalized medicine in humans.
Acknowledgements
This study was supported by the Slovenian Research Agency
Grant No. P4-0127. The author is grateful to Prof. Roger Pain and
Prof. Borut Štrukelj for critical reading of the manuscript.
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