long-term effect of epigenetic study

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Introduction
Chen et al. 2022
PGPB (plant growth-promoting bacteria)
- key to engineering microbiomes for application
in agriculture
- difficult for PGPB inocula to survive
Figure 1. A new mechanism in which PGPB affect
DNA methylation in roots to promote plant growth
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Introduction
DNA methylation
- In plants, de novo methylation is catalysed by
DRM2 (DOMAINS REARRANGED METHYLTRANSFERASE)
- DNA methylation-maintaining enzymes
1). CG methylation maintained by MET1
(methyltransferase 1)
2). CHG methylation by CMT2 and CMT3
(plant-speci?c chromomethylases)
3). CHH methylation by DRM2 or CMT2
- DNA demethylation is catalyzed by ROS1
(repressor of silencing 1), DME (DMEMTER), DML
(DEMETER-like protein)
- H A, T or C (not G)
- D A, T or G (not C)
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Introduction
Royal Botanic Gardens
Phytolacca americana L
- a Mn/Cd hyperaccumulator which has great
potential for bioremediation of heavy metal
(HM)-contaminated soils
Previous study
- isolated two PGPB, Bacillus sp. PGP5 and
Arthrobacter sp. PGP41
- Phenotypic plasticity ? major role in
responding to different environments
? investigate the influence of PGPB inocula on
rhizosphere microbiome and the role of DNA
methylation by PGPB
Figure 2. Pokeweed (Phytolacca americana L.)
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Materials and methods
Chen et al. 2022
Experimental design
- both control and zebularine (Zeb)-treated P.
americana
- bulk soils, sterilized (Ste)-soils, or soils
with inoculum (strain PGP5 or PGP41)
- harvested at 0, 3, 7, 15, 21, and 30 days after
transplantation
- Analysis samples
? Variation in the rhizosphere microbiome ?
amplicon and metagenome sequencing
? Changes in rhizosphere roots ? transcriptional
and epigenetic levels
Figure 3. Schematic representation of the
experimental design
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Materials and methods
Eurofins
WGBS (Whole-genome bisulphite sequencing)
- method used to determine the DNA methylation
patterns of an entire genome at single-nucleotide
resolution
- chemical treatment of DNA with sodium bisulfite
converts unmethylated cytosines into uracils
- DNA is subjected to a PCR assay, where all
uracils are converted to thymidines
Figure 4. Principle of hole-genome bisulfite
sequencing
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Rhizosphere microbiome assembly is mainly driven
by plant development
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by roots
- high abundances of both inocula at day 3
- the inocula (PGP41 and PGP5) failed to thrive
in soils
Figure 5. The relative abundances of strains
PGP41 (A) and PGP5 (B)
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Rhizosphere microbiome assembly is mainly driven
by plant development
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by roots
- the highest a-diversity at day 0, the lowest at
day 3
- there was no difference between CK, PGP41 and
PGP5 for the pattern
Figure 6. Changes in a-diversity indices,
including Chao1, Shannon, and Simpson
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Rhizosphere microbiome assembly is mainly driven
by plant development
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by roots
- Overlaps (day 7) on the edge between early (07
days) and late phases (1530 days)
- trends of plant development-dependent shifts of
the rhizosphere microbiome
Figure 7. ß-diversity analyses principal
coordinate analyses (left) and pairwise
correlation analyses (right)
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Rhizosphere microbiome assembly is mainly driven
by plant development
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by roots
- identified 13 OTUs (operational taxonomic
units) correlated with root residence time
? relationships between root and inocula stabilze
microbiome community
Figure 8. Bacterial biomarkers (I) and Heatmap
based on relative abundances of biomarkers (J)
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Variations in the rhizosphere microbiome induced
by inocula are limited to the early phase
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by inocula
- Microbiome communities change depending on
inocula at early phase (day 3)
Figure 9. Axonomic differences in rhizosphere
microbiomes for comparisons of inocula
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Variations in the rhizosphere microbiome induced
by inocula are limited to the early phase
Chen et al. 2022
Taxonomic variation in the rhizosphere
microbiome induced by inocula
- (D) is network of the non-inoculated microbiome
- (E) is network of the PGP41-inoculated
microbiome
- persistent effects of recruitment by roots
mainly influence the rhizosphere microbiome in
the early phase
Figure 10. Co-occurrence networks of the
non-inoculated and PGP41-inoculated microbiome
in early (top) and late (bottom) phase
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Variations in the rhizosphere microbiome induced
by inocula are limited to the early phase
Chen et al. 2022
Functional variation in the rhizosphere
microbiome
- In PCA, day 3 samples were separated but not
day 30
- In day 3, all genes annotated with KEGG
categories show variation than day 30
- significant variation for carbohydrate
metabolic categories or amino acid metabolic
categories
Figure 11. (A) PCA in the microbiome induced by
inoculation, (B) Distributions of coefficients of
variation for KEGG
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Variations in the rhizosphere microbiome induced
by inocula are limited to the early phase
Chen et al. 2022
Functional variation in the rhizosphere
microbiome
- PGP41- and PGP5-inoculated microbiomes compared
to CK at day 3
- significantly different abundances (PGP5 55,
PGP41 77)
Table. Symbols and means to COG categories
symbol function of protein groups
S function unknown
L replication, recombination and repair
R general function prediction
M cell wall/ membrane/ envelope biogenesis
K transcription
T signal transduction mechanism
P inorganic ion transport and metabolism
E amino acid transport and metabolism
G carbohydrate transport and metabolism
O posttranslational modification, protein turnover and chaperone
U intracellular trafficking, secretion and vesicular transport
Q secondary metabolites biosynthesis
V defense mechanism
N cell biosynthesis, transport and metabolism
H coenzyme transport and metabolism
Figure 12. Abundance of significantly changed COG
(Clusters of Orthologous Groups) categories
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Variations in the rhizosphere microbiome induced
by inocula are limited to the early phase
Chen et al. 2022
Functional variation in the rhizosphere
microbiome
- similar abundances between samples at day 30
compared to day 3
- functional-level variation in the rhizosphere
microbiome was limited to the early phase
Figure 13. Heatmaps depicting the average
abundances of significantly changed COG categorie
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Microbiome-induced changes in root gene
expression are selectively maintained
into the late phase
Chen et al. 2022
Changes in gene expression profiles in roots
induced by the rhizosphere microbiome
- RNA sequencing between plants grown in
inoculated and non-inoculate soil (early and late
phase)
- change in gene expression elicited by
inoculation and/or the altered rhizosphere
microbiome in the early phase
Figure 14. Variation in transcript profiles
(left) and venn diagram of DEGs (right) between
the early and late phase
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Microbiome-induced changes in root gene
expression are selectively maintained
into the late phase
Chen et al. 2022
Changes in gene expression profiles in roots
induced by the rhizosphere microbiome
WGCNA (the weighted gene coexpression network
analysis)
used to determine modules of DEGs with highly
correlated expression patterns and associations
of root gene expression with rhizosphere
microbiomes
- ME (Module eigengene) is a key indicator of
gene expression patterns within a gene module
- Eight modules (P lt 0.05) were significantly
associated with PCoA2 or PCoA3
Figure 15. WGCNA showing significant correlation
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Microbiome-induced changes in root gene
expression are selectively maintained
into the late phase
Chen et al. 2022
Changes in gene expression profiles in roots
induced by the rhizosphere microbiome
- the expression of DEGs in roots(x-axis) was
highly related to the rhizosphere
microbiome(y-axis)
- significantly enriched functions in the late
phase were also detected in the early phase
? microbiome-induced changes in root gene
expression were selectively maintained into the
late phase
Figure 16. A scatterplot of gene significance
(GS) versus module membership (MM)
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Modification of DNA methylation in response
to inoculation affects gene expression in roots
Chen et al. 2022
Expression pattern of genes involved in
maintaining DNA methylation
- abundances of DNA methylation maintaining gene
is decreased at day 3 (early phase) but not day
30 (late phase)
- WGBS profiling of DNA methylation, to test
whether inoculation affected DNA methylation in
roots
- differentially methylated regions (DMRs) were
identified -gt focus on CHH context
Figure 17. (Left) Heatmap of genes involved in
maintaining DNA methylation. Red, increased
transcript abundance blue, decreased transcript
abundance. (Right) Numbers of DMRs detected in
different contexts through WGBS
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Modification of DNA methylation in response
to inoculation affects gene expression in roots
Chen et al. 2022
Variation in DNA methylome profiles and
correlations with gene expression
- when compare to day 3, hypomethylation is
dominant both PGP5 and PGP41 at day 30
- DNA methylation modification induced by
inoculation might be involved in regulation of
gene expression
Figure 18. Numbers (left) and differential
expression levels (right) of hyper- or
hypomethylated DMRs
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Modification of DNA methylation in response
to inoculation affects gene expression in roots
Chen et al. 2022
Variation in DNA methylome profiles and
correlations with gene expression
- test the influence of DMRs on gene expression.
- At both day 3 and day 30, strong positive or
negative relationships were detected
(R gt 0.7 and P lt 0.001)
Figure 19. Scatter plots of the changes (log2
fold change) in DNA methylation (Y-axis) against
the changes in gene transcript abundance
(X-axis). (E) day 3 and (F) day 30
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Modification of DNA methylation in response
to inoculation affects gene expression in roots
Chen et al. 2022
Variation in DNA methylome profiles and
correlations with gene expression
- GO analyses of DMRs in the late phase
- ?regulation of transcription, ?regulation of
hormone levels, ?defense response, ?nucleotide
binding, and ?the G protein-coupled receptor
signaling pathway
- all of these functions are related to gene
expression regulation
? at least, gene transcription was partially
controlled by DNA methylation induced by
PGP5/PGP41
Figure 20. GO enrichment analyses of
DMR-associated genes
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
Chen et al. 2022
Comparison of inoculum-induced growth promotion
of P. americana in sterilized soils vs.
unsterilized soils
- previous result inocula (PGP41 and PGP5) were
present in the rhizosphere soils at early stage
but at late stage no colonization of inocula in
roots.
- to test whether variation in the rhizosphere
microbiome is necessary for PGP by PGPB, used
sterilized soils
Figure 21. Aerial part of P. americana under
different treatments at Day 3 (A) and Day 30 (B)
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
Chen et al. 2022

Comparison of inoculum-induced growth promotion
of P. americana in sterilized soils vs.
unsterilized soils
- inoculation of each strain (PGP41, PGP5)
significantly promoted plant growth in sterilized
soils
? neither changes in the rhizosphere microbiome
nor colonization of inocula in roots is necessary
for plant growth promotion
Figure 22. The weights and lengths of shoots and
roots of P. americana at Day 3 (C, n 3) and Day
30 (D, n3)
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
Chen et al. 2022
DNA methylation inhibitor disrupt P. americana
growth promotion induced by inocula
- investigate the role of DNA methylation in
inoculation-induced growth promotion of P.
americana
(Zeb which is a DNA methylation inhibitor)
Figure 23. Aerial part of P. americana under
different treatments at day 3 (A) and day 30 (B)
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
Chen et al. 2022
DNA methylation inhibitor disrupt P. americana
growth promotion induced by inocula
- genes involved in maintaining DNA methylation
and randomly selected from the overlapping DEGs
and DMRs
- Zeb treatments could disrupt the
inoculation-induced gene expression patterns by
altering the DNA methylation patterns
Figure 24. Heatmaps based on relative transcript
abundances of genes involved in maintaining DNA
methylation (C) and genes randomly selected from
the overlapping DEGs and DMRs (D)
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
DNA methylation inhibitor disrupt P. americana
growth promotion induced by inocula
- Day 3, no significant difference in biological
phenotypes with or without Zeb
- Day 30, comparing to with Zeb, no significant
difference without Zeb
? inoculation-induced growth promotion of P.
americana is at least partially mediated by
change in DNA methylation
Figure 25. Comparison of inoculation-induced P.
americana growth promotion with and without Zeb
treatment at day 3 (E, n 3) and day 30 (F, n
8).
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Changes in DNA methylation are involved
in inoculation-induced growth promotion of P.
americana
DNA methylation inhibitor disrupt P. americana
growth promotion induced by inocula
- additional test investigate growth promotions
of P. americana induced by inoculations at 60
days after inoculation
? altered DNA methylation elicited by the
inoculum in the early phase has a long-term
effect after the inoculum was eliminated in soils
Figure 26. inoculation-induced P. Americana
growth promotion by strains PGP41 and PGP5 were
detected at day 60 (n 8)
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Discussion Conclusions
Changes in DNA methylation and growth-promoting
effects in plants induced by microbial treatments
- The treatment of inocula has an impact
primarily in the early root zone, but its
influence diminishes over time.
- Roots influenced by inocula determine the
abundance of rhizosphere microbiota over time
- DNA methylation altered by inocula in the early
stage continues to regulate gene expression even
after the disappearance of inocula
- This sustained effect can significantly impact
plant growth promotion (PGP)
Figure 27. Schematic representation of the
two-step interaction between PGPB and plants
mediated by DNA methylation and root recruitment