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Articleshttps://doi.org/10.1038/s41588-017-0012-9
1DOE Joint Genome Institute, Walnut Creek, CA, USA. 2Department of Biology, University of North Carolina, Chapel Hill, NC, USA. 3Howard Hughes Medical Institute, Chevy Chase, MD, USA. 4Institute of Microbiology, ETH Zurich, Zurich, Switzerland. 5Department of Horticulture, Virginia Tech, Blacksburg, VA, USA. 6International Centre for Genetic Engineering and Biotechnology, Trieste, Italy. 7Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA. 8Department of Microbiology, University of Tennessee, Knoxville, TN, USA. 9Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA. 10School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA. 11Max Planck Institute for Developmental Biology, Tübingen, Germany. 12School of Natural Sciences, University of California, Merced, Merced, CA, USA. 13The Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA. 14Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA. Present address: 15Department of Biology, Stanford University, Stanford, CA, USA; 16The Grassland College, Gansu Agricultural University, Lanzhou, Gansu, China; 17BD Technologies and Innovation, Research Triangle Park, NC, USA. Asaf Levy and Isai Salas Gonzalez contributed equally to this work. *e-mail: [email protected]; [email protected]; [email protected]
The microbiota of plants and animals have coevolved with their hosts for millions of years1–3. Through photosynthesis, plants serve as a rich source of carbon for diverse bacterial com-
munities. These include mutualists and commensals, as well as pathogens. Phytopathogens and growth-promoting bacteria have considerable effects on plant growth, health, and productivity4–7. Except for intensively studied relationships such as root nodula-tion in legumes8, T-DNA transfer by Agrobacterium9, and type III secretion–mediated pathogenesis10, the molecular mechanisms that govern plant–microbe interactions are not well understood. It is therefore important to identify and characterize the bacterial genes and functions that help microbes thrive in the plant environment. Such knowledge should improve the ability to combat plant diseases and harness beneficial bacterial functions for agriculture, with direct effects on global food security, bioenergy, and carbon sequestration.
Cultivation-independent methods based on profiling of marker genes or shotgun metagenome sequencing have considerably improved the overall understanding of microbial ecology in the plant environment11–15. In parallel, reduced sequencing costs have enabled the genome sequencing of plant-associated bacterial iso-lates at a large scale16. Importantly, isolates enable functional valida-tion of in silico predictions. Isolate genomes also provide genomic and evolutionary context for individual genes, as well as the poten-tial to access genomes of rare organisms that might be missed by
metagenomics because of limited sequencing depth. Although metagenome sequencing has the advantage of capturing the DNA of uncultivated organisms, multiple 16S rRNA gene surveys have reproducibly shown that the most common plant-associated bac-teria are derived mainly from four phyla13,17 (Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes) that are amenable to cultivation. Thus, bacterial cultivation is not a major limitation in sampling of the abundant members of the plant microbiome16.
Our objective was to characterize the genes that contribute to bacterial adaptation to plants (plant-associated genes) and those genes that specifically aid in bacterial root colonization (root- associated genes). We sequenced the genomes of 484 new bacte-rial isolates and single bacterial cells from the roots of Brassicaceae, maize, and poplar trees. We combined the newly sequenced genomes with existing genomes to create a dataset of 3,837 high-quality, non-redundant genomes. We then developed a computational approach to identify plant-associated genes and root-associated genes based on comparison of phylogenetically related genomes with knowledge of the origin of isolation. We experimentally validated two sets of plant-associated genes, including a previously unrecognized gene family that functions in plant-associated microbe–microbe compe-tition. In addition, we characterized many plant-associated genes that are shared between bacteria of different phyla, and even between bacteria and plant-associated eukaryotes. This study represents
Genomic features of bacterial adaptation to plantsAsaf Levy 1, Isai Salas Gonzalez2,3, Maximilian Mittelviefhaus4, Scott Clingenpeel 1, Sur Herrera Paredes 2,3,15, Jiamin Miao5,16, Kunru Wang5, Giulia Devescovi6, Kyra Stillman1, Freddy Monteiro2,3, Bryan Rangel Alvarez1, Derek S. Lundberg2,3, Tse-Yuan Lu7, Sarah Lebeis8, Zhao Jin9, Meredith McDonald2,3, Andrew P. Klein2,3, Meghan E. Feltcher2,3,17, Tijana Glavina Rio1, Sarah R. Grant 2, Sharon L. Doty 10, Ruth E. Ley 11, Bingyu Zhao5, Vittorio Venturi6, Dale A. Pelletier7, Julia A. Vorholt4, Susannah G. Tringe 1,12*, Tanja Woyke 1,12* and Jeffery L. Dangl 2,3,13,14*
Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then com-pared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and the other serving in microbe–microbe competition between plant-associated bacteria. We also identified 64 plant-associated pro-tein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. This work expands the genome-based understanding of plant–microbe interactions and provides potential leads for efficient and sustain-able agriculture through microbiome engineering.
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a comprehensive and unbiased effort to identify and characterize candidate genes required at the bacteria–plant interface.
ResultsExpanding the plant-associated bacterial reference catalog. To obtain a comprehensive reference set of plant-associated bacterial genomes, we isolated and sequenced 191, 135, and 51 novel bacte-rial strains from the roots of Brassicaceae (91% from Arabidopsis thaliana), poplar trees (Populus trichocarpa and Populus deltoides), and maize, respectively (Methods, Table 1, Supplementary Tables 1–3). The bacteria were specifically isolated from the interior (endo-phytic compartment) or surface (rhizoplane) of plant roots, or from soil attached to the root (rhizosphere). In addition, we isolated and sequenced 107 single bacterial cells from surface-sterilized roots of A. thaliana. All genomes were assembled, annotated, and deposited in public databases and in a dedicated website (“URLs,” Supplementary Table 3, Methods).
A broad, high-quality bacterial genome collection. In addition to the newly sequenced genomes noted above, we collected 5,587 bacterial genomes belonging to the four most abundant phyla of plant-associated bacteria13 from public databases (Methods). We manually classified each genome as plant-associated, non-plant-associated (NPA), or soil-derived on the basis of its unambiguous isolation niche (Methods, Supplementary Tables 1 and 2). The plant-associated genomes included organisms isolated from plants or rhizospheres. A subset of the plant-associated bacteria was also annotated as ‘root-associated’ when isolated from the rhizoplane or the root endophytic compartment. Genomes from bacteria isolated from soil were considered as a separate group, as it is unknown whether these strains can actively associate with plants. Finally, the remaining genomes were labeled as NPA genomes; these were iso-lated from diverse sources, including humans, non-human animals, air, sediments, and aquatic environments.
We carried out stringent quality control to remove low-quality or redundant genomes (Methods). This led to a final dataset of 3,837 high-quality and nonredundant genomes, including 1,160 plant-associated genomes, 523 of which were also root-associated. We grouped these 3,837 genomes into nine monophyletic taxa to allow comparative genomics analysis among phylogenetically related genomes (Fig. 1a, Supplementary Tables 1 and 2, Methods, “URLs”).
To determine whether our genome collection from cultured isolates was representative of plant-associated bacterial communi-ties, we analyzed cultivation-independent 16S rDNA surveys and metagenomes from the plant environments of Arabidopsis11,12,
barley18, wheat, and cucumber14 (Methods). The nine taxa analyzed here account for 33–76% (median, 41%; Supplementary Table 4) of the total bacterial communities found in plant-associated envi-ronments and therefore represent a substantial portion of the plant microbiota, consistent with previous reports13,16,19.
Increased carbohydrate metabolism and fewer mobile elements in plant-associated genomes. We compared the genomes of bac-teria isolated from plant environments with those from bacteria of shared ancestry that were isolated from non-plant environments. We assumed that the two groups should differ in the set of accessory genes that evolved as part of their adaptation to a specific niche. Comparison of the size of plant-associated, soil, and NPA genomes showed that plant-associated and/or soil genomes were signifi-cantly larger than NPA genomes (P < 0.05, PhyloGLM and t-tests; Supplementary Fig. 1a, Supplementary Table 5). We observed this trend in six to seven of the nine analyzed taxa (depending on the test), representing all four phyla. Pangenome analyses of a few genera with plant-associated and NPA isolation sites showed that pangenome sizes were similar between plant-associated and NPA genomes (Supplementary Fig. 2).
Next, we examined whether certain gene categories are enriched or depleted in plant-associated genomes versus in their NPA coun-terparts, using 26 broad functional gene categories (Supplementary Table 6). We used the PhyloGLM test (Fig. 1b) and t-test (Supplementary Fig. 3) to detect enrichment. Two gene categories demonstrated similar phylogeny-independent trends suggestive of an environment-dependent selection process. The “Carbohydrate metabolism and transport” gene category was expanded in the plant-associated organisms of six taxa (Fig. 1b). This was the most expanded category in Alphaproteobacteria, Bacteroidetes, Xanthomonadaceae, and Pseudomonas (Supplementary Fig. 3). In contrast, mobile genetic elements (phages and transposons) were underrepresented in four plant-associated taxa (Fig. 1b and Supplementary Fig. 3). Plant-associated genomes showed increased genome sizes despite a reduction in the number of mobile elements that often serve as vehicles for horizontal gene transfer and genome expansion. A comparison of root-associated bacteria to soil bacteria showed less drastic changes than those seen between plant-associ-ated and NPA groups, as expected for organisms that live in more similar habitats (Fig. 1b and Supplementary Fig. 3).
Identification and validation of plant- and root-associated genes. We sought to identify specific genes enriched in plant- and root-associated genomes compared with NPA and soil-derived
Table 1 | Novel and previously sequenced genomes used in this analysis
Taxon Taxonomic rank Novel sequenced PA genomes
Scanned genomes
Genomes used in analysis
PA NPA Soil RA
Alphaproteobacteria1 Class 126 784 610 368 199 43 169
Burkholderiales1 Order 85 612 433 160 209 64 86
Acinetobacter1 Genus 4 926 454 7 442 5 3
Pseudomonas1 Genus 75 506 349 169 137 43 61
Xanthomonadaceae1 Family 15 264 147 110 26 11 26
Bacillales2 Order 54 664 454 97 185 172 54
Actinobacteria 13 NA 69 504 394 164 142 88 89
Actinobacteria 23 NA 19 845 587 29 526 32 18
Bacteroidetes4 Phylum 37 481 409 56 293 60 17
Total 484 5,586 3,837 1,160 2,159 518 5231Proteobacteria. 2Firmicutes. 3Actinobacteria phylum. PA, plant-associated bacteria; NPA, non-plant-associated bacteria; soil, soil-associated bacteria; RA, root-associated bacteria; NA, not available (an artificial taxon).
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GenusFamilyOrderProteo.Bacteroidetes
Actino. Actinobacteria 2*
Alphaproteobacteria
Proteo. β-proteo.
Proteo. γ-proteo. γ-proteo. AcinetobacterProteo.
Firmic. Bacilli Bacillales
Actino.PseudomonasProteo.
>10.5–1<0.5
>–0.5–1 to –0.5<–1
PhyloGLM estimate
GenusFamilyOrderProteo. AlphaproteobacteriaBacteroidetes
Actino. Actinobacteria 2*Proteo.
Proteo.Proteo.
Firmic. Bacillales
Actino.Proteo.
Non-significant
More genesin PA/RA
More genesin NPA/soil
PA vs. NPA
RA vs. soil
ClassificationNPA (n = 2,159)PA (n = 1,160)RA (n = 523)soil (n = 518)
Acinetobacter (n = 454)
Actinobacteria 1 (n = 394)Actinobacteria 2 (n = 587)
Bacillales (n = 454)
Bacteroidetes (n = 409)
Burkholderiales (n = 433)
Pseudomonas (n = 349)
Alphaproteobacteria (n = 610)
Xanthomonadaceae (n = 147)
Taxonomic groups
a
b
Tree scale: 0.1
0.5 M0.3 M
50 K
0.1 M
0.5 M
1.0 M # genes
# genes
Phylum Class
Phylum Class
2.0 M1.5
M1.0
M0.5 M
Carbohydrates
Signal transd
uction
Coenzymes
Amino acids
Cell wall,
cell m
embrane
Transcrip
tion
General functi
on
Translatio
n
Inorganic ions
Motili
ty
Secondary m
etabolites
Replicatio
n, repair,
recomb.
EnergyLip
ids
Nucleotid
es
Post-tra
nslatio
n
Cell divi
sion
Defense
RNA processi
ng
Chromatin
Unknown
Extrace
llular s
tructu
res
Tra�cking, se
cretio
n
Cytoskeleton
Prophages, transp
osons
1.0 M
0.5 M0.1 M
Carbohydrates
Signal transd
uction
Coenzymes
Amino acids
Cell wall,
cell m
embrane
Transcrip
tion
General functi
on
Translatio
n
Inorganic ions
Motili
ty
Secondary m
etabolites
Replicatio
n, repair,
recomb.
EnergyLip
ids
Nucleotid
es
Post-tra
nslatio
n
Cell divi
sion
Defense
RNA processi
ng
Chromatin
Unknown
Extrace
llular s
tructu
res
Tra�cking, se
cretio
n
Cytoskeleton
Prophages, transp
osons
XanthomonadaceaeXanthomon.
Pseudom.Pseudomon.
Burkholderiales
Actinobacteria 1*Pseudomon.
γ-proteo.
Moraxel.
PseudomonasPseudom.
Xanthomonadaceae
Pseudomon.
Xanthomon.
γ-proteo.
γ-proteo.γ-proteo.
Actinobacteria 1*
Burkholderialesβ-proteo.
Bacilli
AcinetobacterMoraxel.Pseudomon.
Fig. 1 | The genome dataset used in analysis, and differences in gene category abundances. a, The maximum-likelihood phylogenetic tree of 3,837 high-quality and nonredundant bacterial genomes, based on the concatenated alignment of 31 single-copy genes. The outer ring shows the taxonomic group, the central ring shows the isolation source, and the inner ring shows the root-associated (RA) genomes within plant-associated (PA) genomes. Taxon names are color-coded according to phylum: green, Proteobacteria; red, Firmicutes; blue, Bacteroidetes; purple, Actinobacteria. See “URLs” for the iTOL interactive phylogenetic tree. b, Differences in gene categories between plant-associated and NPA genomes (top) and between root-associated and soil-associated genomes (bottom) of the same taxon. Both heat maps indicate the level of enrichment or depletion based on a PhyloGLM test. Significant cells (color-coded according to the key) represent P values of < 0.05 (FDR-corrected). Pink-red cells indicate significantly more genes in plant-associated and root-associated genomes in the top and bottom heat maps, respectively. Histograms at the top and right of each heat map represent the total number of genes compared in each column and row, respectively. Asterisks indicate non-formal class names. “Carbohydrates” denotes the carbohydrate metabolism and transport gene category. Full COG category names for the x-axis labels are presented in Supplementary Table 6. Note that cells representing high absolute estimate values (dark colors) are based on categories of few genes and are therefore more likely to be less accurate. Phylum names are color-coded as in a. Xanthomon., Xanthomonadales; Pseudomon., Pseudomonadales; Pseudom., Pseudomonadaceae; Moraxel., Moraxellaceae.
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genomes, respectively (Supplementary Fig. 4, Methods). First, we clustered the proteins and/or protein domains of each taxon on the basis of homology, using the annotation resources COG20, KEGG Orthology21, and TIGRFAM22, which typically comprise 35–75% of all genes in bacterial genomes23. To capture genes that do not have existing functional annotations, we also used OrthoFinder24 (after benchmarking; Supplementary Fig. 5) to cluster all protein sequences within each taxon into homology-based orthogroups. Finally, we clustered protein domains with Pfam25 (Methods, “URLs”). We used these five protein/domain-clustering approaches in parallel comparative genomics pipelines. Each protein/domain sequence was additionally labeled as originating from either a plant-associated genome or an NPA genome.
Next, we determined whether protein/domain clusters were sig-nificantly associated with a plant-associated lifestyle by using five independent statistical approaches: hypergbin, hypergcn (two ver-sions of the hypergeometric test), phyloglmbin, phyloglmcn (two phylogenetic tests based on PhyloGLM26), and Scoary27 (a stringent combined test) (Methods). These analyses were based on either gene presence/absence or gene copy number. We defined a gene as sig-nificantly plant-associated if at least one test showed that it belonged to a significant plant-associated gene cluster, and if it originated from a plant-associated genome. We defined significant NPA, root-associated, and soil genes in the same way. Significant gene clusters identified by the different methods had varying degrees of overlap (Supplementary Figs. 6 and 7). In general, we noted a high degree of overlap between plant-associated and root-associated genes and overlap between NPA and soil-associated genes (Supplementary Fig. 8). Overall, plant-associated genes were depleted from NPA genomes from heterogeneous isolation sources (Supplementary Figs. 9 and 10). Principal coordinates analysis with matrices that contained only the plant-associated and NPA genes derived from each method as features increased the separation of plant-associated from NPA genomes along the first two axes (Supplementary Fig. 11). We provide full lists of statistically significant plant-associated, root-associated, soil-associated, and NPA proteins and domains accord-ing to the five clustering techniques and five statistical approaches for each taxon in Supplementary Tables 7–15 (also see “URLs”).
To validate our predictions, we assessed the abundance patterns of plant-associated and root-associated genes in natural environ-ments. We retrieved 38 publicly available plant-associated, NPA, root-associated, and soil-associated shotgun metagenomes, includ-ing some from plant-associated environments that were not used for isolation of the bacteria analyzed here14,28,29 (Supplementary Table 16a). We mapped reads from these culture-independent metagenomes to plant-associated genes found with all statisti-cal approaches (Methods, Supplementary Figs. 12–16). Plant-associated genes in up to seven taxa were more abundant (P < 0.05, t-test) in plant-associated metagenomes than in NPA metagenomes (Fig. 2a, Supplementary Table 16b). Root-associated, soil-associ-ated, and NPA genes, in contrast, were not necessarily more abun-dant in their expected environments (Supplementary Table 16b).
In addition, we selected eight genes that were predicted to be plant-associated by multiple approaches (Supplementary Table 17a) for experimental validation via an in planta bacterial fitness assay (Methods). We inoculated the roots of surface-sterilized rice seedlings (n = 9–30 seedlings per experiment) with wild-type Paraburkholderia kururiensis M130 (a rice endophyte30) or a knock-out mutant strain for each of the eight genes. We grew the plants for 11 d and then collected and quantified the bacteria that were tightly attached to the roots (Methods, Supplementary Table 17b). Mutations in two genes led to fourfold to sixfold reductions in colo-nization (false discovery rate (FDR)-corrected Wilcoxon rank sum test, q < 0.1) relative to that by wild-type bacteria (Fig. 2b), without an observed effect on growth rate (Supplementary Fig. 17). These two genes encode an outer-membrane efflux transporter from the
nodT family and a Tir chaperone protein (CesT), respectively. It is plausible that the other six genes assayed function in facets of plant association not captured in this experimental context.
Functions for which coexpression of and cooperation between different proteins are needed are often encoded by gene operons in bacteria. We therefore tested whether our methods could cor-rectly predict known plant-associated operons. We grouped plant-associated and root-associated genes into putative plant-associated and root-associated operons on the basis of their genomic proxim-ity and orientation (Supplementary Fig. 4, Methods, “URLs”). This analysis yielded some well-known plant-associated functions, such as those of the nodABCSUIJZ and nifHDKENXQ operons (Fig. 2c,d). Nod and Nif proteins are integral for biological nitrogen cycling and mediate root nodulation31 and nitrogen fixation32, respectively. We also identified the biosynthetic gene cluster for the precursor of the plant hormone gibberellin33,34 (Fig. 2e). Other known plant-associ-ated operons identified are related to chemotaxis35, secretion systems such as T3SS36 and T6SS37, and flagellum biosyntheis38–40 (Fig. 2f–i).
Thus, we identified thousands of plant-associated and root-associated gene clusters by using five different statistical approaches (Supplementary Table 18) and validated them by means of compu-tational and experimental approaches, broadening our understand-ing of the genetic basis of plant–microbe interactions and providing a valuable resource to drive further experimentation.
Protein domains reproducibly enriched in diverse plant-asso-ciated genomes. Plant-associated and root-associated proteins and protein domains conserved across evolutionarily diverse taxa are potentially pivotal to the interaction between bacteria and plants. We identified 767 Pfam domains as significant plant-asso-ciated domains in at least three taxa, on the basis of multiple tests (Supplementary Table 19a). Below we elaborate on a few domains that were plant-associated or root-associated in all four phyla. Two of these domains, a DNA-binding domain (pfam00356) and a ligand-binding (pfam13377) domain, are characteristic of the LacI transcription factor (TF) family. These TFs regulate gene expres-sion in response to different sugars41, and their copy numbers were expanded in the genomes of plant-associated and root-associated bacteria in eight of the nine taxa analyzed (Fig. 3a). Examination of the genomic neighbors of lacI-family genes identified strong enrichment for genes involved in carbohydrate metabolism and transport in all of these taxa, consistent with their expected regula-tion by a LacI-family protein41 (Supplementary Fig. 18). We ana-lyzed the promoter regions of these putative regulatory targets of LacI-family TFs, and identified three AANCGNTT palindromic octamers that were statistically enriched in all but one taxon, and which may serve as the TF-binding site (Supplementary Table 20). These data suggest that accumulation of a large repertoire of LacI-family-controlled regulons is a common strategy across bacterial lineages during adaptation to the plant environment.
Another domain, the metabolic domain aldo-keto reductase (pfam00248), was enriched in the genomes of plant-associated and root-associated bacteria from eight taxa belonging to all four phyla investigated (Fig. 3b). This domain is involved in the metabolic con-version of a broad range of substrates, including sugars and toxic carbonyl compounds42. Thus, bacteria that inhabit plant environ-ments may consume similar substrates. Additional plant-associated and root-associated proteins and domains that were enriched in at least six taxa are described in Supplementary Fig. 19.
We also identified domains that were reproducibly enriched in NPA and/or soil-associated genomes, including many domains of mobile genetic elements (Supplementary Fig. 20).
Putative plant protein mimicry by plant- and root-associated proteins. Convergent evolution and horizontal transfer of protein domains from eukaryotes to bacteria have been suggested for some
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Bacillales Pseudomonas
Xanthomonadaceae
Alphaproteobacteria
Bacteroidetes
Actinobacteria 1
Alphaproteobacteria, Bradyrhizobium sp. ARR65
Burkholderiales, Burkholderia kururiensis M130G118DRAFT_01458
NodZ
g
A PA gene according to hypergbin
A PA gene according to phyloglmbin
A PA gene according to Scoary
BraARR65DRAFT_00043940
Alphaproteobacteria, Rhizobium etli bv. mimosae IE4771
mlr6364
mlr6365
mlr6366
mlr6367
mlr6368
mlr6368
mlr6370
Alphaproteobacteria, Rhizobium leguminosarum bv. viciae 3841
mcpB
cheY
cheW
cheA
Xanthomonadaceae, Xanthomonas axonopodis pv. vasculorum NCPPB 900
IE4771_PB00363 (gene id2585987913)
RL4028
h Burkholderiales, Variovorax sp. Root411Ga0102102_11238
ImpH
ImpF
ImpG
ImpE
Hcp
ImpM
ImpL
ImpK
ImpJ
Alphaproteobacteria, Ensifer medicae WSM1115 iSinmedDRAFT_3917
d
nifH
nifD
nifK
nifE
nifN
nifX
c
e
f
NolO
nifQ
cheR
cheB
cheW
T3SS protein U
T3SS protein V
HpaB
YscJ/HrcJ fam
ily
HpaA
HpaP
T3SS protein QT3SS protein RT3SS protein S
T3SS protein D
HrpB2
HrpB1
HrpE
HrpB4
T3SS protein L
T3SS protein N
HrpB7
T3SS protein T
T3SS protein C
VasG
VgrG
FlgF
FlgBFlgC
FlgGFlgAFlgIM
otEFlgHFliLFliP
Flagellin
Flagellin
Flagellin
Flagellin
FlgE
FlgK
FlgL
flaFflbTflgD
fliI
flhA
fliR
Hum
an g
ut (n
= 3
)O
cean
(n =
1)A
rctic
sal
t lak
e (n
= 3
)A
t soi
l (n
= 2)
At r
hizo
. (n
= 4)
Whe
at rh
izop
lane
(n =
3)
Whe
at s
oil (
n =
2)
Cuc
umbe
r soi
l (n
= 2)
Cuc
um. r
hizo
plan
e (n
= 3
)Po
plar
soi
l (n
= 5)
Popl
ar rh
izos
pher
e (n
= 5
)Po
plar
end
osph
ere
(n =
5)
NPA
, all
(n =
7)
Soil,
all
(n =
11)
PA, a
ll (n
= 2
0)
RA, a
ll (n
= 11
)
log 10
(CFU
/g o
f roo
t)
5.05.56.06.57.07.58.0
Nor
mal
ized
# re
ads
a
b
Nodulation
Nitrogenfixation
Ent-kaurene biosynthesis(gibberelin precursor)
Chemotaxis
Type III secretion systemGa0097773_106954
Type VI secretion system
Flagellum biosynthesis
–1
3
4
5
1
2
3
1
2
3
4
0
1
2
3
4
–4
–2
0
2
0
3.5
4.5
5.5
Mean valueMedian value
P = 0.03
P = 0.001
P = 0.006
P = 0.046
P = 0.004
P = 0.0006
P = 0.045
NodJ
NodI
NodU
NodS
NodC
NodB
NodA
Metagenome samples: NPA Soil PA RA (also PA)
Hum
an g
ut (n
= 3
)O
cean
(n =
1)A
rctic
sal
t lak
e (n
= 3
)A
t soi
l (n
= 2)
At r
hizo
. (n
= 4)
Whe
at s
oil (
n =
2)W
heat
rhiz
opla
ne (n
= 3
)C
ucum
ber s
oil (
n =
3)C
ucum
. rhi
zopl
ane
(n =
3)
Popl
ar s
oil (
n =
5)Po
plar
rhiz
osph
ere
(n =
5)
Popl
ar e
ndos
pher
e (n
= 5
)N
PA, a
ll (n
= 7
)PA
, all
(n =
20)
Soil,
all
(n =
11)
RA, a
ll (n
= 11
)
Wild
type
G118DRAFT
_05604
G118DRAFT
_03668
Fig. 2 | Validation of predicted plant-associated genes by multiple approaches. a, Plant-associated (PA) genes, which were predicted from isolate genomes, were more abundant in PA metagenomes than in NPA metagenomes. Reads from 38 shotgun metagenome samples were mapped to significant PA, NPA, RA, and soil-associated genes predicted by Scoary. P values are indicated for the significant differences between PA and NPA genes or RA and soil-associated genes in each taxon (two-sided t-test). Full results and an explanation for normalization are presented in Supplementary Fig. 14. b, Results of a rice root colonization experiment using wild-type Paraburkholderia kururiensis M130 or knockout mutants for two predicted plant-associated genes. Two mutants showed reduced colonization compared with the wild type: G118DRAFT_05604 (q-value = 0.00013, Wilcoxon rank sum test), which encodes an outer membrane efflux transporter from the nodT family, and G118DRAFT_03668 (q-value = 0.0952, Wilcoxon rank sum test), a Tir chaperone protein (CesT). Each point represents the average count of a minimum of three to six plates derived from the same plantlet, expressed as colony-forming units (CFU) per gram of root. c–i, Examples of known functional plant-associated operons captured by different statistical approaches. The plant-associated genes are highlighted by shaded bars, colored according to the key. c, Nod genes. d, NIF genes. e, Ent-kaurene (gibberelin precursor). f, Chemotaxis proteins in bacteria from different taxa. g, Type III secretion system. h, Type VI secretion system, including the imp genes (impaired in nodulation). i, Flagellum biosynthesis in Alphaproteobacteria. Labels show the gene symbol or the protein name for which such information was available.
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microbial effector proteins that are secreted into eukaryotic host cells to suppress defense and facilitate microbial proliferation43–45. We searched for new candidate effectors or other functional plant-protein mimics. We retrieved a set of significant plant-associated and root-associated Pfam domains that were reproducibly predicted by multiple approaches or in multiple taxa, and we cross-referenced these with protein domains that were also more abundant in plant genomes than in bacterial genomes (Methods). This analysis yielded 64 plant-resembling plant-associated and root-associated domains (PREPARADOs) encoded by 11,916 genes (Supplementary Fig. 21, Supplementary Table 21). The number of PREPARADOs was four-fold higher than the number of domains that overlapped repro-ducible NPA/soil-associated domains and plant domains (n = 15). The PREPARADOs were relatively abundant in genomes of plant-associated Bacteroidetes and Xanthomonadaceae ( > 0.5% of all domains on average; Supplementary Fig. 22). Some PREPARADOs were previously described as domains within effector proteins, such as Ankyrin repeats46, regulator of chromosome condensation
repeat (RCC1)47, leucine-rich repeat (LRR)48, and pectate lyase49. PREPARADOs from plant genomes were enriched 3–14-fold (P < 10−5, Fisher’s exact test) as domains predicted to be ‘integrated effector decoys’ when fused to plant intracellular innate immune receptors of the NLR class50–53 (compared with two random domain sets; Methods, Supplementary Figs. 21 and 23, Supplementary Table 21). We found that 2,201 bacterial proteins that encode 17 of the 64 PREPARADOs shared ≥ 40% identity across the entire pro-tein sequence with eukaryotic proteins from plants, plant-associ-ated fungi, or plant-associated oomycetes, and therefore are likely to maintain a similar function (Supplementary Fig. 24, Supplementary Tables 21 and 22). The varied phylogenetic distribution among this protein class could have resulted from convergent evolution or from cross-kingdom horizontal gene transfer between phylogenetically distant organisms subjected to the shared selective forces of the plant environment.
Seven PREPARADO-containing protein families were character-ized by N-terminal eukaryotic or bacterial signal peptides followed
0.000
0.002
0.004
0.006
0.008
0.010
0.000
0.001
0.002
0.003
0.004
0.005
Transcriptional regulator, LacI family
350
Periplasmic binding protein-like,ligand binding (pfam13377)
LacI, DNA-binding domain(pfam00356)
Actino. 1
Alphaprot.
Burkho. Pseud. Xanthom.
a
1 320
Aldo-keto reductase (pfam00248)b
Alphaprot. Bacillales
Bactero. Burkho. Pseud. Xanthom.
Frac
tion
of a
ll do
mai
ns
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.000
0.001
0.002
0.003
0.004
Bactero.
Frac
tion
of a
ll do
mai
ns
NPA
PA
RA
Soil
BacillalesActino. 1
Actino. 2
Actino. 2
1
Cla
ssifi
ed a
s si
gnifi
cant
Dis
trib
utio
n in
gen
omes
P = 3 × 10–12
P = 7 × 10–14
P = 1 × 10–8
P = 3 × 10–7
P = 1 × 10–8P = 6 × 10–7
P = 0.01
P = 0.003
P = 0.002
P = 0.001P = 0.04
P = 3 × 10–5
P = 2 × 10–27
P = 7 × 10–7
P = 3 × 10–49
P = 3 × 10–5
P = 0.004P = 0.03
P = 4 × 10–6
P = 3 × 10–14
P = 7 × 10–27
P = 0.03P = 0.002
P = 0.008
P = 0.001
Fig. 3 | Proteins and protein domains that were reproducibly enriched as plant-associated or root-associated in multiple taxa. We compared the occurrence of protein domains (from Pfam) between plant-associated (PA) and NPA bacteria and between root-associated (RA) and soil-associated bacteria. Color-coding is as in Fig. 1a. a, Transcription factors with LacI (Pfam00356) and periplasmic-binding protein domains (Pfam13377). These proteins are often annotated as COG1609. b, Aldo-keto reductase domain (Pfam00248). Proteins with this domain are often annotated as COG0667. We used a two-sided t-test to test for the presence of the genes in a and b in genomes that shared the same label and to verify the enrichment reported by the various tests. FDR-corrected P values are shown for significant results (q-value < 0.05). Colored circles indicate the number of different statistical tests ( ≤ 5) supporting plant, non-plant, root, or soil association of a gene or domain, with each circle representing one test. Gene illustrations above each graph represent random protein models. Note that a and b each contain two graphs because of the different scales. Actino., Actinobacteria; Alphaprot., Alphaproteobacteria; Burkho., Burkholderiales; Bactero., Bacteroidetes; Pseud., Pseudomonas; Xanthom., Xanthomonadaceae. Box-and-whisker plots show the median (center lines), 25th and 75th percentiles (box edges), extreme data points within 1.5 times the interquartile range from the box edge (whiskers), and outliers (isolated data points). Full results are in Supplementary Table 19.
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by a PREPARADO dedicated to carbohydrate binding or metabo-lism (Supplementary Table 21). One of these domains, Jacalin, is a mannose-binding lectin domain that is found in 48 genes in the A. thaliana genome, compared with three genes in the human genome25. Mannose is found on the cell wall of different bacterial and fungal pathogens and could serve as a microbial-associated molecular pattern that is recognized by the plant immune system54–61. We identified a family of ~430-amino-acid-long microbial proteins with a signal peptide followed by a functionally ill-defined endonu-clease/exonuclease/phosphatase family domain (pfam03372), and ending with a Jacalin domain (pfam01419). This domain architec-ture is absent in plants but is found in diverse microorganisms, many of which are phytopathogens, including Gram-negative and Gram-positive bacteria, fungi from the Ascomycota and Basidiomycota phyla, and oomycetes (Fig. 4). We speculate that these microbial lectins may be secreted to outcompete plant immune receptors for mannose-binding on the microbial cell wall, effectively serving as camouflage.
We thus discovered a large set of protein domains that are shared between plants and the microbes that colonize them. In many cases the entire protein is conserved across evolutionarily distant plant-associated microorganisms.
Co-occurrence of plant-associated gene clusters. We identified numerous cases of plant-associated gene clusters (orthogroups) that demonstrate high co-occurrence between genomes (“URLs”). When the plant-associated genes were derived by phylogeny-aware tests (i.e., PhyloGLM and Scoary), they were candidates for inter-taxon horizontal gene transfer events. For example, we identified a cluster predicted by Scoary of up to 11 co-occurring genes (mean pairwise Spearman correlation: 0.81) in a flagellum-like locus from sporadically distributed plant-associated or soil-associated genomes across 12 different genera in Burkholderiales (Fig. 5). Two of the annotated flagellar-like proteins, FlgB (COG1815) and FliN (pfam01052), are also encoded by plant-associated genes in Actinobacteria 1 and Alphaproteobacteria taxa. Six of the remaining genes encode hypothetical proteins, all but one of which are specific to Betaproteobacteria, suggestive of a flagellar structure variant that evolved in this class in the plant environment. Flagellum-mediated motility or flagellum-derived secretion systems (for example, T3SS) are important for plant colonization and virulence39,40,62,63 and can be horizontally transferred64.
Novel putative plant- and root-associated gene operons. In addi-tion to successfully capturing several known plant-associated oper-ons (Fig. 2c–i), we also identified putative plant-associated bacterial operons (“URLs”). Two previously uncharacterized plant-associated gene families were conspicuous. These genes are organized in mul-tiple loci in plant-associated genomes, each with up to five tandem gene copies. They encode short, highly divergent, high-copy-number proteins that are predicted to be secreted, as explained below. These two plant-associated protein families never co-occurred in the same genome, and their genomic presence was perfectly correlated with lifestyles of pathogenic or nonpathogenic bacteria of the genus Acidovorax (order Burkholderiales) (Fig. 6a). We named the gene families present in non-pathogens and pathogens Jekyll and Hyde, respectively, after the characters in Robert Louis Stevenson’s classic novel.
The typical Jekyll gene is 97 amino acids long, contains an N-terminal signal peptide, lacks a transmembrane domain, and, in 98.5% of cases, appears in non-pathogenic plant-associated or soil-associated Acidovorax isolates (Fig. 6a, Supplementary Fig. 25d, Supplementary Table 23a). A single genome may encode up to 13 Jekyll gene copies (Fig. 6a) distributed in up to nine loci (Supplementary Table 23a). We recently isolated four Acidovorax strains from the leaves of naturally grown Arabidopsis16. Even these nearly identical isolates carried hypervariable Jekyll loci that were substantially more divergent than neighboring genes and included copy-number variations and various mutations (Fig. 6b, Supplementary Fig. 25, Supplementary Table 24).
The Hyde putative operons, in contrast, are composed of two distinct gene families unrelated to Jekyll. A typical Hyde1 protein has 135 amino acids and an N-terminal transmembrane helix. Hyde1 proteins are also highly variable, as demonstrated by copy-number variation, sequence divergence, and intralocus transposon insertions (Fig. 6a,c, Supplementary Fig. 26a–c, Supplementary Table 23b). Hyde1 was found in 99% of cases in phytopathogenic Acidovorax. These genomes carried up to 15 Hyde1 gene copies distributed in up to ten loci (Fig. 6a, Supplementary Table 23b). In 70% of cases Hyde1 was located directly downstream from a more conserved ~300-amino-acid-long plant-associated protein-coding gene that we named Hyde2 (Fig. 6c,d, Supplementary Table 23d). We identified loci with Hyde2 followed by Hyde1-like genes in dif-ferent members of the Proteobacteria phylum. These contained a highly variable Hyde1-like protein family that maintained only the
Paenibacillus sp. PAMC 26794, Firmicutes
0.1
10021
36
23
30
91
89
84
46
100
100Oryza sativa japonica group
JacalinDirigent
Oryza sativa japonica group
Protein kinase, catalyticdomain
Arabidopsis thaliana
F-box associated 1
Arabidopsis thaliana
Endonuclease/exonuclease/phosphatase family Signal peptide, Gram– bacteria
Magnaporthe oryzae 70-15, Ascomycota
Aspergillus oryzae 3.042, Ascomycota
Fomitopsis pinicola FP-58527 SS1, Basidiomycota
Rhizoctonia solani AG-3 Rhs1AP, Basidiomycota
Signal peptide, Gram+ bacteriaSignal peptide, eukaryotes
Phytophthora parasitica, oomycetes
Leptonema illini DSM 21528, Spirochaetes
Streptomyces sp. 303MFCol5.2, Actinobacteria
Xanthomonas axonopodispv. citri str. 306, Proteobacteria
Bacteria: PA, NPA, soilPA fungiPA oomycetesPlants
XP_015619049
BAF14474
NP_191518.1
NP_176220.1
WP_017689535.1
XP_003714330.1
EIT77169.1
EPS95407.1
EUC62117.1
ETM02225.1
EHQ06050.1
WP_020125377.1
AAM38968.1
Fig. 4 | A protein family shared by plant-associated bacteria, fungi, and oomycetes that resemble plant proteins. A maximum-likelihood phylogenetic tree of representative proteins with Jacalin-like domains across plants and plant-associated (PA) organisms. Endonuclease/exonuclease/phosphatase-Jacalin proteins are present across PA eukaryotes (fungi and oomycetes) and PA bacteria. In most cases these proteins contain a signal peptide in the N terminus. The Jacalin-like domain is found in many plant proteins, often in multiple copies. The protein accession is shown above each protein illustration.
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Articles Nature GeNetics
Burkholderiales_OG0008862 (hyp.)
Burkholderiales_OG0008861 (FliN)Burkholderiales_OG0008863 (FlgA)
Burkholderiales_OG0008350 (hyp.)Burkholderiales_OG0009542 (hyp.)
Burkholderiales_OG0008351 (FlgB) Burkholderiales_OG0007689 (hyp.)
Burkholderiales_OG0007460 (hyp.)Burkholderiales_OG0010507 (hyp.)
Burkholderiales_OG0010506 (FliO)
Burkholderiales_OG0004311 (RHS)
ClassificationNPA
PA
RA
Soil
Tree scale: 0.1
Lim
noha
bita
ns_s
p._R
im28
Xyloph
ilus_
sp._L
eaf2
20
Bordetella_bronchiseptica_E014
Acidovorax_konjaci_DSM_7481
Bordetella_bronchiseptica_10580
Ralstonia_sp._AU12-08_(IVD)
Polar
omon
as_s
p._O
V174
Otto
wia
_thi
ooxy
dans
_DSM
_146
19
Alicycliphilus_denitrificans_BC
Cupriavidus_sp._AMP6
Comamonas_testosteroni_S44
Pelo
mon
as_s
p._R
oot1
444
Burkholderia_mallei_2002721280
Ralstonia_sp._25MFCol4.1
Rhiz
obac
ter_
sp._
OV
335
Janthinobacterium_sp._344
Ralstonia_solanacearum_23-10BR
Burkholderia_oklahomensis_BDU
Massilia_sp._LC238
Bordetella_bronchiseptica_D756
Rhiz
obac
ter_
sp._
Root
16D
2
Burkholderia_cepacia_383
Met
hylib
ium
_sp.
_Roo
t127
2
Burkholderia_mallei_BMQ
Variovorax_sp._770b2
Burkholderia_cenocepacia_MC0-3Burkholderia_thailandensis_USAMRU_Malaysia__20
Hyl
emon
ella
_gra
cilis
_Nia
gara
_R
Burk
hold
eria
_oxy
phila
_NBR
C_10
5797
Bordetella_sp._FB-8,_DSM_24873
Bordetella_avium_197N
Burkholderia_pseudomallei_NCTC_13178
Acidovorax_avenae_avenae_RS-1
Burk
hold
eria
_spr
entia
e_W
SM50
05
Alcaligenes_faecalis_faecalis_NCIB_8687
Burkholderia_pseudomallei_1106a
Oligella_urethralis_DNF00040
Cupriavidus_taiwanensis_STM6070
Burkholderia_ambifa
ria_MC40-6
Burk
hold
eria
_sp.
_JPY
251
Burkholderia_mallei_BMY
Ralstonia_solanacearum_M
olK2
Ralstonia_solanacearum_Rs-09-161
Taylorella_equigenitalis_MCE9
Acidovorax_sp._JHL-3
Burkholderia_multiv
orans_ATCC_17616
Burkholderi
a_sp
._lig3
0
Burkholderiales_bacterium_1_1_47
Duganella_sp._Leaf61
Burk
hold
eria
_kur
urie
nsis
_thi
ooxy
dans
_NBR
C_1
0710
7
Ralstonia_pickettii_27511
Burkholderia_pseudomallei_NAU20B-16
Verminephrobacter_eiseniae_EF01-2
Burk
hold
eria
_fun
goru
m_N
BRC_
1024
89
Sutterella_wadsworthensis_2_1_59BFAA
Acidovorax_sp._NO-1
Polar
omon
as_s
p._JS
666
Variovorax_sp
._Root434
Comamonas_granuli_NBRC_101663
Cupriavidus_taiwanensis_STM
6018
Bordetella_bronchiseptica_A1-7
Burkholderia_cenocepacia_869T2
Acidovorax_ebreus_TPSY
Comamonas_testosteroni_sv._Ba_CNB-1
Herbaspirillum_sp._YR522
Burkholderi
a_gla
dioli_BSR
3
Burkholderia_pseudomallei_MSHR5848
Bordetella_bronchiseptica_E010
Achromobacter_piechaudii_HLE
Parasutterella_excrementihominis_YIT_11859
Bordetella_holmesii_35009
Met
hylib
ium
_pet
role
iphi
lum
_PM
1
Acidovorax_delafieldii_DSM_64
Ralstonia_pickettii_OR214
Rhiz
obac
ter_
sp._
Root
29
Albi
dife
rax_
sp._O
V413
Variovorax_sp._Root318D1
Variovorax_paradoxus_B4
Achromobacter_xylosoxidans_NH44784-1996
Delftia_acidovorans_SPH-1
Burkholderia
_dolosa
_PC543_(L
MG_19
468)
Cupriavidus_sp._UYPR2.512
Chitinimonas_koreensis_DSM_17726
Bordetella_bronchiseptica_KM22
Burkholderia_multiv
orans_CGD2M
Ralstonia_pickettii_12DBurk
hold
eria_
bryo
phila
_376
MFS
ha3.1
Burkholderia_pseudomallei_668
Acidovorax_avenae_avenae_ATCC_19860
Taylorella_equigenitalis_14/56
Burk
hold
eria
_nod
osa_
DSM
_216
04
Acidovorax_caeni_DSM_19327
Acidovorax_oryzae_ATCC_19882
Massilia_alkalitolerans_DSM_17462
Burk
hold
eria
_ter
rae_
NBR
C_10
0964
Ralstonia_sp._UNC404CL21Col
Comamonas_testosteroni_ATCC_11996
Burkholderia_mallei_GB8_horse_4
Burk
hold
eria
_sp.
_MP-
1
Variovo
rax_sp
._OK605
Herbaspirillum_seropedicae_SmR1
Alcaligenes_sp._DH1f
Delftia_acidovorans_CCUG_15835
Hyl
emon
ella
_gra
cilis
_Can
ale-
Paro
la_D
4,_A
TCC_
1962
4
Pandoraea_sp._RB-44
Burk
hold
eria
_kur
urie
nsis
_M13
0
Pseu
dorh
odof
erax
_sp.
_Lea
f267
Ralstonia_solanacearum_Rs-10-244
Rhiz
obac
ter_
sp._
Root
1221
Variovorax_paradoxus_S110
Burkholderia_cenocepacia_H111
Burkholderia_cepacia_DDS_7H-2
Met
hylib
ium
_sp.
_CF4
68
Burkholderia_mallei_NCTC_10247
Massilia_timonae_CCUG_45783
Taylorella_asinigenitalis_MCE3
Collimonas_sp._OK242
Cupriavidus_sp._BIS7
Variovo
rax_s
p._350M
FTsu
5.1
Rhiz
obac
ter_
sp._
Root
404
Bordetella_trematum
_CCUG_13902
Herbaspirillum_seropedicae_Os45
Bordetella_bronchiseptica_1289
Com
amon
adac
eae_
bact
eriu
m_U
RHA0
028
Bordetella_pertussis_CHLA
-11
Ralstonia_eutropha_JMP134
Duganella_zoogloeoides_ATCC_25935
Burk
hold
eria
_sp.
_CCG
E100
2
Massilia_sp._Root418
Bordetella_holmesii_41130
Bordetella_pertussis_Tohama_I
Ralstonia_solanacearum_FQ
Y_4
Pandoraea_pnomenusa_RB38
Pelo
mon
as_s
p._R
oot6
62
Sutterella_wadsworthensis_3_1_45B
Ralstonia_solanacearum_Po82
Burk
hold
eria
_car
iben
sis_M
BA4
Sutterella_wadsworthensis_HGA0223
Janthinobacterium_sp._Marseille
Burkholderia_pseudomallei_MSHR6137
Burkholderia_pseudomallei_MSHR1043
Janthinobacterium_sp._CG3
Burkholderia_cenocepacia_K56-2Valvano
Burkholderia
_multiv
orans_CGD1
Noviherbaspirillum_sp._Root189
Basilea_psittacipulmonis_DSM_24701
Burk
holde
ria_s
p._W
SM22
30
Burkholderia_pseudomallei_MSHR5858
Burkholderia_vietnamiensis_G4
Cupriavidus_taiwanensis_LM
G_19424
Burkholderia_pseudomallei_NCTC_13179
Burkholderia_pseudomallei_MSHR520
Burk
hold
eria
_sp.
_BT0
3
Pelo
mon
as_s
p._R
oot1
237
Comamonas_aquatica_NBRC_14918
Ralstonia_solanacearum_CM
R15
Janthinobacterium_sp._RA13
Burkholderia_pseudomallei_BPC006
Burk
hold
eria
_ban
nens
is_N
BRC_
1038
71
Rubr
iviv
ax_b
enzo
atily
ticus
_ATC
C_B
AA
-35
Bordetella_bronchiseptica_E012
Burkholderia_pseudomallei_MSHR146
Burkholderia_sp._MSh1
Ralstonia_solanacearum_CFBP2957
Cupriavidus_sp._YR651
Achromobacter_xylosoxidans_AXX-A
Derxia_gummosa_DSM_723
Burkholderia_pseudomallei_1026b
Burk
holde
ria_p
heno
lirup
trix_
BR34
59
Massilia_sp._Leaf139
Rhod
ofer
ax_s
aiden
bach
ensis
_ED16
Variovorax_paradoxus_4MFCol3.1
Bordetella_pertussis_CS
Delftia_sp._Cs1-4
Janthinobacterium_sp._551a
Acidovorax_sp._Leaf160
Variovorax_paradoxus_349MFTsu5.1
Massilia_sp._Root133
Cupriavidus_necator_N-1,_ATCC_43291
Bordetella_holmesii_1058
Burkh
older
ia_glu
mae_B
GR1
Burkholderia_pseudomallei_576
Thiomonas_sp._FB-6,_D
SM_25805
Ralstonia_solanacearum_N
CPPB_282
Acidovorax_sp._KKS102
Taylorella_asinigenitalis_ATCC_700933
Ram
libac
ter_
sp._L
eaf4
00
Burk
hold
eria
_sp.
_UYP
R1.4
13
Comamonas_badia_DSM_17552
Ralstonia_solanacearum_G
MI1000
Herbaspirillum_massiliense_JC206
Polar
omon
as_s
p._YR5
68
Burkholderia_thailandensis_MSMB121
Burkholderia_pseudomallei_HBPUB10134a
Burkholderia_cenocepacia_gv._III_J2315
Janthinobacterium_agaricidamnosum_W1R3
Burkholderia_pseudomallei_1655
Bordetella_bronchiseptica_D993
Burkholderia_pseudomallei_HBPUB10303a
Massilia_sp._Root351
Pandoraea_sp._E26
Comamonas_testosteroni_TK102
Advenella_mimigardefordensis_DPN7,_DSM_17166_(MIMI)
Burkholderi
a_ce
nocepac
ia_DDS_2
2E-1
Lim
noha
bita
ns_s
p._R
im47
Burk
hold
eria
_sp.
_RPE
64
Collimonas_sp._OK307
Acidovorax_sp._Leaf76
Burkholderia_andropogonis_Ba3549
Oligella_urethralis_DSM_7531
Acidovorax_valerianellae_DSM_16619
Bordetella_holmesii_70147
Ralstonia_solanacearum_N
CPPB909
Burk
hold
eria
_sp.
_WSM
4176
Achromobacter_sp._Root170
Massilia_sp._Root1485
Burkholderia_thailandensis_H0587
Burkholderia_cepacia_GG4
Pelo
mon
as_s
p._R
oot1
217
Variovo
rax_sp
._CF313
Burk
hold
eria
_sp.
_JC
2949
Burkholderia_cepacia_Bu72
Acidovorax_radicis_N35
Pseudoduganella_violaceinigra_DSM_15887
Duganella_sp._Leaf126
Pseu
dorh
odof
erax
_sp.
_Lea
f265
Burkholderia_sp._WP42
Burk
hold
eria
_aci
dipa
ludi
s_N
BRC_
1018
16
Burkholderia_mallei_JHU
Burkholderia_thailandensis_E444
Burkholderia_pseudomallei_MSHR346
Acidovorax_sp._Leaf84
Burkholderia_cepacia_AMMD
Pusillimonas_noertemannii_BS8
Polar
omon
as_n
apht
halen
ivora
ns_C
J2
Polynucleobacter_necessarius_asymbioticus_QLW-P1DM
WA-1
Burkholderia_pseudomallei_Pakistan_9
Burkholderia_pseudomallei_MSHR5858
Bordetella_bronchiseptica_E013
Taylorella_equigenitalis_ATCC_35865
Burkholderia
_multiv
orans_DDS_15
A-1
Pandoraea_sp._SD6-2
Acidovorax_citrulli_tw6
Burk
hold
eria_
sp._C
h1-1
Burkholderia_thailandensis_MSMB43
Bordetella_holmesii_ATCC_51541
Taylorella_asinigenitalis_14/45
Thiomonas_sp._FB-C
d,_DSM
_25617
Burkholderia_mallei_SAVP1
Burkh
older
ia_sp
._A1
Burk
hold
eria
_phy
mat
um_S
TM81
5
Alicycliphilus_denitrificans_K601
Met
hylib
ium
_sp.
_CF0
59
Burkholderia_pseudomallei_MSHR305
Janthinobacterium_sp._OK676
Achromobacter_xylosoxidans_NBRC_15126,_ATCC_27061
Burkholderia_pseudomallei_HBPUB10134a
Bordetella_petrii_Se-1111R,_DSM_12804
Bordetella_holmesii_H
558
Delftia_sp._RIT313
Herbaspirillum_huttiense_putei_IAM_15032
Curvib
acte
r_gr
acilis
_ATCC_B
AA-807
Lautropia_mirabilis_A
TCC
_51599
Acidovorax_citrulli_DSM_17060
Burkholderia_pseudomallei_NCTC_13392
Burkholderia_vietnamiensis_WPB
Burkholderia_sp._KJ006
Pseu
dorh
odof
erax
_sp.
_Lea
f274
Burkholderia_pseudomallei_BEO
Burkholderia_pseudomallei_1710a
Burk
hold
eria
_fer
raria
e_N
BRC_
1062
33
Polar
omon
as_g
lacial
is_R3
-9
Ralstonia_solanacearum_SD
54
Comamonas_composti_DSM_21721
Acidovorax_sp._Leaf78
Burkholderi
a_gla
dioli_NBRC_13
700
Massilia_niastensis_DSM_21313
Acidovorax_sp._Root267
Duganella_sp._CF402
Comamonas_testosteroni_KF-1
Polynucleobacter_sp._MW
H-MoK4
Burk
hold
eria_
xeno
vora
ns_L
B400
Bordetella_bronchiseptica_D989
Pusillimonas_sp._T7-7
Burkholderia_sp._B14
Burkholderia_pseudomallei_MSHR338
Burkholderia_pyrrocinia_Lyc2
Giesbergeria_anulus_ATCC_35958
Herbaspirillum_sp._GW103Collimonas_sp._OK412
Bordetella_bronchiseptica_B18-5_(C3)
Polar
omon
as_s
p._CF3
18
Variovorax_paradoxus_295MFChir4
.1
Variovorax_sp
._Root473
Acidovorax_sp._Root70
Burkholderia_pseudomallei_MSHR5848Acidovorax_avenae_citrulli_AAC00-1
Duganella_sp._Root1480D1
Pandoraea_pnomenusa_3kgm
Acidovorax_wautersii_DSM_27981
Achromobacter_arsenitoxydans_SY8
Met
hylib
ium
_sp.
_YR6
05
Burkholderia_pseudomallei_K96243
Curvib
acte
r_lan
ceola
tus_
ATCC_14669
Acidovorax_citrulli_pslbtw65
Variov
orax
_para
doxus
_110B
Brac
hym
onas
_den
itrifi
cans
_DSM
_151
23
Burkholderia_pseudomallei_S13
Ram
libac
ter_
tata
ouin
ensis
_TTB
310
Burkholderia_mallei_NCTC_10229
Brac
hym
onas
_chi
rono
mi_
DSM
_198
84
Oxalobacter_formigenes_HOxBLS
Acidovorax_sp._Root219
Burk
hold
eria
_mim
osar
um_L
MG
_232
56
Massilia_lurida_CGMCC_1.10822
Herminiimonas_arsenicoxydans_ULPAs1
Janthinobacterium_sp._HH01
Burk
hold
eria
_sp.
_JC2
948
Burk
hold
eria
_gin
seng
isoli_
NBRC
_100
965
Oligella_ureolytica_DSM_18253
Burkholderia_pseudomallei_Pasteur
Acidovorax_sp._Root568
Burk
hold
eria_
phyt
ofirm
ans_
PsJN
Burkholderia_pseudomallei_MSHR511
Burk
hold
eria
_sp.
_YR2
81
Simplicispira_psychrophila_DSM_11588
Burkholderia_mallei_23344
Burk
holde
ria_s
p._JP
Y366
Burk
hold
eria
_mim
osar
um_N
BRC_
1063
38
Burkholderia
_dolosa
_AUO158
Burk
hold
eria_
dilw
orth
ii_W
SM35
56
Duganella_sp._Root336D2
Variovo
rax_sp
._Root4
11
Acidovorax_temperans_KY4
Comamonas_thiooxydans_DSM_17888
Bordetella_parapertussis_12822
Burkholderia_pyrro
cinia_CH-67
Chitinimonas_taiwanensis_DSM_18899
Ralstonia_solanacearum_U
W551
Variovo
rax_s
p._375M
FSha3
.1
Variov
orax
_sp._
URHB0020
Achromobacter_xylosoxidans_A8
Burkholderia_mallei_BMK
Cupriavidus_metallidurans_H1130
Burkholderia_cenocepacia_AU_1054
Collimonas_fungivorans_Ter331
Delftia_acidovorans_CCUG_274B
Burkholderia_cenocepacia_BC7
Achromobacter_piechaudii_ATCC_43553
Alcaligenes_faecalis_phenolicus_DSM_16503
Cupriavidus_sp._OV096
Ralstonia_sp._GA3-3
Herbaspirillum_frisingense_GSF30
Variovorax_sp
._EL159
Massilia_flava_CGMCC_1.10685
Burk
hold
eria
_hel
eia_
NBR
C_10
1817
Burk
hold
eria
_mim
osar
um_S
TM36
21
Duganella_sp._OV458
Burk
hold
eria_
caled
onica
_NBR
C_102
488
Extensimonas_vulgaris_CGMCC_1.10977
Burk
holde
ria_g
ram
inis_
C4D1M
Brackiella_oedipodis_DSM_13743
Ralstonia_pickettii_12J
Burkholderia_pseudomallei_1106b
Acidovorax_temperans_CB2
Limnobacter_sp._MED105 Acidovorax_sp._JS42
Polar
omon
as_s
p._JS
666_
UNC47MFT
su3.1
Hyd
roge
noph
aga_
sp._
PBC
Bordetella_holmesii_F627
Advenella_kashmirensis_W13003
Rose
atel
es_s
p._Y
R242
Alcaligenes_sp._EGD-AK7
Burkholderia_mallei_ATCC_23344
Comamonas_aquatica_DA1877
Burkholderia_cepacia_UCB_717,_ATCC_25416
Bordetella_bronchiseptica_RB50
Delftia_acidovorans_2167
Bordetella_hinzii_ATCC_51730
Achromobacter_sp._Root565
Oxalobacter_formigenes_OXCC13
Burk
hold
eria
_sp.
_YI2
3
Variovo
rax_s
p._278M
FTsu
5.1
Burkh
older
ia_ph
enoli
rupt
rix_A
C1100
Ralstonia_sp._5_2_56FAA
Ralstonia_eutropha_H16
Herbaspirillum_sp._CF444
Acidovorax_sp._Root217
Burkholderia_cepacia_RB-39
Burkholderia_pseudomallei_406e
Burk
hold
eria
_sp.
_SJ9
8
Achromobacter_sp._Root83
Ralstonia_sp._PBA
beta_proteobacterium_JGI_0001001-A11
Burkholderia_thailandensis_E264,_ATCC_700388
Variovorax_paradoxus_EPSVari
ovorax
_sp._1
60MFS
ha2.1
Janthinobacterium_lividum_PAMC_25724
Collimonas_sp._OK607
Achromobacter_xylosoxidans_X02736
Ralstonia_solanacearum_P673
Cupriavidus_metallidurans_CH34
Burk
hold
eria_
sp._U
RHA00
54
Ralstonia_sp._JGI_0001001-A05
Rhod
ofer
ax_f
errir
educ
ens_
T118
Acidovorax_sp._Root402
Janthinobacterium_lividum_RIT308
Burkholderia_cenocepacia_PC184
Acidovorax_sp._JHL-9
Com
amon
adac
eae_
bact
eriu
m_H
1
Acidovorax_sp._MR-S7
Bordetella_bronchiseptica_C4
Burk
holde
ria_s
p._W
SM22
32
Burk
hold
eria
_ter
rae_
BS00
1
Burkholderia_cenocepacia_HI2424
Massilia_consociata_BSC265
Ralstonia_sp._UN
CCL144
FliOFliN
C-term
FlgB
FliFFlgC
FliH
FlgDFlgE
FliPFliA
FlgA
FlgI
Methylibium sp. YR605
Burkholderia sp. Msh1
Ralstonia solanacearum P673
Spearman correlation
PA orthogroups, Burkholderiales (Scoary)
PA o
rtho
grou
ps, B
urkh
olde
riale
s (S
coar
y)
Burkholderiales
a
b
Clustered orthogroups1
0.8
0.6
0.4
0.2
0
–0.2
–0.4
–0.6
–0.8
–1
Flagellar genes
Achromobacter
Roseateles, RhizobacterMethylibium
Variovorax
Delftia
Acidovorax
Collimonas
Massilia
Duganella
Ralstonia
Burkholderia
Not a significant PA gene(Scoary)
Thiomonas_bhubanesw
arensis_DSM
_18181Thiom
onas_intermedia_K12
Thiomonas_arsenitoxydans_3A
sC
aldimonas_m
anganoxidans_ATC
C_BA
A-369 Le
ptot
hrix
_cho
lodn
ii_SP
-6
Burk
hold
eria
les_
sp._
JOSH
I_00
1Ru
briv
ivax
_gel
atin
osus
_IL
144
Azo
hrdr
omon
as_a
ustr
alic
a_D
SM_1
124
Burkholderia_rhizoxinica_HKI_454
Burkholderia_sp.B13
Burk
hold
eria
_sp.
_JPY
347
Burk
hold
eria
_sp.
_YR5
20Bu
rkho
lder
ia_s
p._L
eaf1
77
Burk
hold
eria
_sor
didi
cola
_S17
0Bu
rkho
lder
ia_g
rimm
iae_
R27
Burkholderia_pseudomallei_354e
Fig. 5 | Co-occurring plant-associated and soil-associated flagellum-like gene clusters are sporadically distributed across Burkholderiales. a, Left, a hierarchically clustered correlation matrix of all 202 significant plant-associated (PA) orthogroups (gene clusters) from Burkholderiales, predicted by Scoary. Right, the orthogroups present within and adjacent to the flagellar-like locus of different genomes. Gene names based on a BLAST search are shown in parentheses. Hyp., hypothetical protein; RHS, RHS repeat protein. Genes illustrated above and below the black horizontal line for each species are located on the positive and negative strand, respectively. b, The Burkholderiales phylogenetic tree based on the concatenated alignment of 31 single-copy genes. Colored circles represent the 11 orthogroups presented in a, with the same color-coding as in a. Genus names are shown next to pillars of stacked circles. RA, root-associated.
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A. caeni DSM 19327 (0,0,0)
Comamonas testosteroni ATCC 11996 (0,0,0)
A. sp. JS42 (0,0,0)
A. sp. MR-S7 (0,0,0)
A. ebreus TPSY (0,0,0)
A. temperans CB2 (0,0,0)
A. temperans KY4 (0,0,0)
A. sp. JHL-3 (0,0,0)
A. sp. JHL-9 (0,0,0)
Pathogen
Non-pathogen
PANPASoil
ba
A. sp. NO-1 (1,0,0)
A. sp. Root70 (10,0,0)
A. sp. KKS102 (10,0,0)
A. delafieldii DSM 64 (13,0,0)
A. sp. Root402 (10,0,0)
A. sp. Root568 (9,0,0)
A. sp. Leaf78 (10,0,0)
A. sp. Leaf76 (11,0,1)
A. sp. Leaf84 (12,0,2)
A. radicis N35 (13,0,0)
A. sp. Root267 (9,0,0)
A. sp. Root219 (7,0,0)
A. sp. Root217 (12,0,0)
A. avenae citrulli AAC00-1 (0,11,3)
A. citrulli DSM 17060 (0,15,4)
A. citrulli tw6 (0,15,3)
A. citrulli pslbtw65 (0,15,5)
A. oryzae ATCC 19882 (0,9,3)
A. avenae avenae RS-1 (0,15,8)A. avenaeT10_61 (0,11,6) A. avenae avenaeATCC 19860 (0,11,5)A. konjaci DSM 7481 (0,5,4)
A. valerianellae DSM 16619 (0,3,4)
A. sp. Leaf160 (0,0,0)
A. wautersii DSM 27981 (0,0,0)
d
100
100
100
77
100
100
100
100
100
100
Hyde2 Transposase
cHyde1
Jekyll
PAARHyde1-like Hyde2 Transposase
Pathogens
Non-pathogensand soil
Acidovoraxtree branches
Genomeclassification
Gene copynumber
(Jekyll, Hyde1, Hyde2)
Bacteriallifestyle
RNase G
Malate synthase
Acidovorax sp. Leaf191
Acidovorax sp. Leaf76
Acidovorax sp. Leaf78
Acidovorax sp. Leaf84
Acidovorax avenae subsp. citrulli AAC00-1, watermelon
Acidovorax citrulli tw6, watermelon
Acidovorax avenae T10_61, sugarcane
Acidovorax avenae avenae RS-1, rice
Acidovorax oryzae ATCC 19882, rice
P. syringae pv. actinidia ICMP 18883,kiwifruit
P. syringae pv. tomato DC3000, tomato
P. syringae ICMP 18804,kiwifruit
P. syringae Pph1448A,common bean
P. syringae PmaM6 (Psy38),cauliflower
P. syringae pv. tomato Max13,tomato
P. syringae pv. syringae B728a, green bean
Fig. 6 | Rapidly diversifying, high-copy-number Jekyll and Hyde plant-associated genes. a, A maximum likelihood phylogenetic tree of Acidovorax isolates based on concatenation of 35 single-copy genes. The pathogenic and non-pathogenic branches of the tree are perfectly correlated with the presence of Hyde1 and Jekyll genes, respectively. b, An example of a variable Jekyll locus in highly related Acidovorax species isolated from leaves of wild Arabidopsis from Brugg, Switzerland. Arrows indicate the following locus tags (from top to bottom): Ga0102403_10161, Ga0102306_101276, Ga0102307_107159, and Ga0102310_10161. c, An example of a variable Hyde locus from pathogenic Acidovorax infecting different plants (the host plant is shown after the species name). The transposase in the first operon fragmented a Hyde2 gene. Arrows indicate the following locus tags (from top to bottom): Aave_3195, Ga0078621_123525, Ga0098809_1087148, T336DRAFT_00345, and AASARDRAFT_03920. d, An example of a variable Hyde locus from pathogenic Pseudomonas syringae infecting different plants. Arrows indicate the following locus tags (from top to bottom): PSPTOimg_00004880 (a.k.a. PSPTO_0475), A243_06583, NZ4DRAFT_02530, Pphimg_00049570, PmaM6_0066.00000100, PsyrptM_010100007142, and Psyr_4701. Genes color-coded with the same colors in b–d are homologous, with the exception of genes colored in ivory (unannotated genes) and Hyde1 and Hyde1-like genes, which are analogous in terms of their similar size, high diversification rate, position downstream of Hyde2, and tendency to have a transmembrane domain. PAAR, proline-alanine-alanine-arginine repeat superfamily.
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short length and a transmembrane helix (Supplementary Fig. 26d). Hyde-carrying organisms included other phytopathogens, such as Pseudomonas syringae, in which the Hyde1-like-Hyde2 locus was again highly variable between closely related strains (Fig. 6d, Supplementary Table 23c). However, the striking Hyde genomic expansion was specific to the phytopathogenic Acidovorax lineage (Supplementary Table 23e). Notably, we observed that Hyde genes
often are directly preceded by genes that encode core structural T6SS proteins, such as PAAR, VgrG, and Hcp65, or are fused to PAAR (Fig. 6d, Supplementary Fig. 27a,b, Supplementary Table 23e). We therefore suggest that Hyde1 and/or Hyde2 might constitute a new T6SS effector family.
The high sequence diversity of Jekyll and Hyde1 genes suggests that the two plant-associated protein families encoded by these
a
b
log 10
CFU
/ml
E. coli +
Hyde2
(Aave
_0990)
E. coli +
Hyde1
(Aave
_0989)
E. coli +
Hyde1
(Aave
_319
1)
3
4
5
6
7
8
9
+ 0.5 mM IPTG
No IPTG
P = 0.0002
**
**
**
**
**
**
**–8
–6
–4
–2
0
2
Prey strains
log 10
(CFU
pre y
/CFU
neg)
AAC00-1 wt
AAC00-1 ∆T6SS
AAC00-1 ∆5-Hyde1
P = 2 × 10–7
P = 4 × 10–8
0.020.02
0.0050.003
0.0010.001
0.0460.042
0.0090.01
0.00010.0001
0.00070.001
E. coli +
GFP
L2 Novo
sphingobium
L11 Sphingomonas
L58 Pseu
domonas
L70 Sten
otrophomonas
L82 Fla
vobacte
rium
L98 Pseu
domonas
L130 Acin
etobacte
r
L405 Chrys
eobacte
rium
L434 Pseu
domonas
E. coli B
W25113
Fig. 7 | Hyde1 proteins of Acidovorax citrulli AAC00-1 are toxic to E. coli and various plant-associated bacterial strains. a, Toxicity assay of Hyde proteins expressed in E. coli. GFP, Hyde2-Aave_0990, and two Hyde1 genes from two loci, Aave_0989 and Aave_3191, were cloned into pET28b and transformed into E. coli C41 cells. Aave_0989 and Aave_3191 proteins were 53% identical. Bacterial cultures from five independent colonies were spotted on an LB plate. Gene expression of the cloned genes was induced with 0.5 mM IPTG. P values are shown for significant results (two-sided t-test). b, Quantification of recovered prey cells after coincubation with Acidovorax aggressor strains. Antibiotic-resistant prey strains E. coli BW25113 and nine different Arabidopsis leaf isolates were mixed at equal ratios with different aggressor strains or with NB medium (negative control). Five Hyde1 loci (including 9 out of 11 Hyde1 genes) are deleted in ∆ 5-Hyde1. ∆ T6SS contains a vasD (Aave_1470) deletion. After coincubation for 19 h on NB agar plates, mixed populations were resuspended in NB medium and spotted on selective antibiotic-containing NB agar. The box plots represent results from at least three independent experiments, with individual values superimposed as dots. The center line represents the median, the box limits represent the 25th and 75th percentiles, and the edges represent the minimal and maximal values. P values are shown at the top; double asterisks denote a significant difference (one-way ANOVA followed by Tukey’s honest significant difference test) between results for wild type versus ∆ T6SS and for wild type versus ∆ 5-Hyde1. Full strain names and statistical information are presented in Supplementary Table 25. For a time course experiment with exemplary strains, see Supplementary Fig. 29.
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genes could be involved in molecular arms races with other organ-isms in the plant environment. As many type VI effectors are used in interbacterial warfare, we tested Acidovorax Hyde1 proteins for antibacterial properties. Expression of two variants of the gene in Escherichia coli led to a 105–106-fold reduction in cell numbers (Fig. 7a, Supplementary Table 25). We constructed a mutant strain of the phytopathogen Acidovorax citrulli AAC00-1with deletion of five Hyde1 loci (∆ 5-Hyde1), encompassing 9 of 11 Hyde1 genes (Supplementary Fig. 28, Supplementary Table 25). Wild-type, ∆ 5-Hyde1, and T6SS-mutant (∆ T6SS) Acidovorax strains were coincubated with an E. coli strain that is susceptible to T6SS kill-ing66 and nine phylogenetically diverse Arabidopsis leaf bacterial isolates16. Survival of wild-type E. coli and six of the leaf isolates after coincubation with wild-type Acidovorax was reduced 102–106-fold compared with that after coincubation with ∆ 5-Hyde1 or ∆ T6SS Acidovorax (Fig. 7b, Supplementary Fig. 29, Supplementary Table 25). Combined with the genomic association of Hyde loci with T6SS, these results suggest that the T6SS antibacterial phe-notype of Acidovorax is mediated by Hyde proteins and that these toxins could be used in competition against other plant-associated organisms. Consistent with a function in microbe–microbe inter-actions, we did not detect compromised virulence of the ∆ 5-Hyde1 strain on host plants (watermelon; data not shown). However, clearance of competitors via T6SS can promote the persistence of Acidovorax citrulli on its host67.
DiscussionThere is increasing awareness that plant-associated microbial communities have important roles in host growth and health. An understanding of plant–microbe relationships at the genomic level could enable scientists to use microbes to enhance agricultural productivity. Most studies have focused on specific plant micro-biomes, with more emphasis on microbial diversity than on gene function12,14,16,18,68–74. Here we sequenced nearly 500 root-associated bacterial genomes isolated from different plant hosts. These new genomes were combined in a collection of 3,837 high-quality bacte-rial genomes for comparative analysis. We developed a systematic approach to identify plant-associated and root-associated genes and putative operons. Our method is accurate as reflected by its abil-ity to capture numerous operons previously shown to have a plant-associated function, the enrichment of plant-associated genes in plant-associated metagenomes, the validation of Hyde1 proteins as likely type VI effectors in Acidovorax directed against other plant-associated bacteria, and the validation of two new genes in P. kuru-riensis that affect rice root colonization. We note that bacterial genes that are enriched in genomes from the plant environment are also likely to be involved in adaptation to the many other organisms that share the same niche, as we demonstrated for Hyde1.
We used five different statistical approaches to identify genes that were significantly associated with the plant/root environment, each with its advantages and disadvantages. The phylogeny-correcting approaches (phyloglmbin, phyloglmcn, and Scoary) allow accurate identification of genes that are polyphyletic and correlate with an environment independently of ancestral state. On the basis of our metagenome validation, the hypergeometric test predicts more genes that are abundant in plant-associated communities than PhyloGLM does. It also identifies monophyletic plant-associated genes, but it yields more false positives than the phylogenetic tests, because in every plant-associated lineage many lineage-specific genes will be considered plant-associated. Scoary is the most stringent method of all and yielded the fewest predictions (Supplementary Table 18). Future experimental validation should prioritize genes predicted in multiple taxa and/or by multiple approaches (Supplementary Figs. 5 and 6, Supplementary Tables 20 and 26).
We discovered 64 PREPARADOs. Proteins containing 19 of these domains are predicted to be secreted by the Sec or T3SS protein
secretion systems (Supplementary Table 21). Notably, plant proteins carrying 35 of these domains belonged to the NLR class of intracellu-lar innate immune receptors (Supplementary Fig. 23, Supplementary Table 21). Thus, these PREPARADO protein domains may serve as molecular mimics. Some may interfere with plant immune functions through disruption of key plant protein interactions75,76. Likewise, the Jacalin-containing proteins we detected in plant-associated bacteria, fungi, and oomycetes may represent a strategy of avoiding immunity triggered by microbial-associated molecular patterns, by binding to extracellular microbial mannose molecules and thereby serving as a molecular invisibility cloak77,78.
Finally, we demonstrated that numerous plant-associated func-tions are consistent across phylogenetically diverse bacterial taxa, and that some functions are even shared with plant-associated eukaryotes. Some of these traits may facilitate plant colonization by microbes and therefore might prove useful in genome engineering of agricultural inoculants to eventually yield a more efficient and sustainable agriculture.
URLs. iTOL Interactive tree (Fig. 1a), https://itol.embl.de/tree/15223230182273621508772620; datasets at the Dangl lab’s dedicated website, http://labs.bio.unc.edu/Dangl/Resources/gfobap_website/index.html (Dataset 1, FNA—nucleotide FASTA files of the 3,837 genomes; Dataset 2, FAA—FASTA files of all proteins used in the analysis; Dataset 3, COG/KEGG Orthology/Pfam/TIGRFAM IMG annotations of all genes used in analysis; Dataset 4, metadata of all genomes; Dataset 5, phylogenetic trees of each of the nine taxa; Dataset 6, pangenome matrices; Dataset 7, pangeneome data frames; Dataset 8, OrthoFinder orthogroup FASTA files; Dataset 9, Mafft MSA of all orthogroups; Dataset 10, hidden Markov models of all orthogroups; Dataset 11, plant-associated/NPA and root-asso-ciated/soil-associated enrichment tables; Dataset 12, correlation matrices; Dataset 13, predicted operons); DSMZ, https://www.dsmz.de/; ATCC, https://www.atcc.org/; NCBI Biosample, https://www.ncbi.nlm.nih.gov/biosample/; IMG, https://img.jgi.doe.gov/cgi-bin/mer/main.cgi; GOLD, https://gold.jgi.doe.gov/; Phytozome, https://phytozome.jgi.doe.gov/pz/portal.html; BrassicaDB, http://brassicadb.org/brad/; sm R package, http://www.stats.gla.ac.uk/~adrian/sm; vegan R package, https://cran.r-project.org/web/packages/vegan/index.html; ape R package, https://cran.r-project.org/web/packages/ape/ape.pdf; fpc R package, https://cran.r-proj-ect.org/web/packages/fpc/index.html; phylolmR package, https://cran.r-project.org/web/packages/phylolm/index.html; scripts used to compute the orthogroups, https://github.com/isaisg/gfobap/tree/master/orthofinder_diamond; scripts used to run the gene enrich-ment tests, https://github.com/isaisg/gfobap/tree/master/enrich-ment_tests; scripts used to perform the PCoA, https://github.com/isaisg/gfobap/tree/master/pcoa_visualization_ogs_enriched.
MethodsMethods, including statements of data availability and any asso-ciated accession codes and references, are available at https://doi.org/10.1038/s41588-017-0012-9.
Received: 20 January 2017; Accepted: 10 November 2017; Published: xx xx xxxx
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AcknowledgementsThe work conducted by the US Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported by the Office of Science of the US Department of Energy under contract no. DE-AC02-05CH11231. J.L.D. and S.G.T. were supported by NSF INSPIRE grant IOS-1343020, and J.L.D. was also supported by DOE–USDA Feedstock Award DE-SC001043 and by the Office of Science (BER), US Department of Energy, grant no. DE-SC0014395. S.H.P. was supported by NIH Training Grant T32 GM067553-06 and was a Howard Hughes Medical Institute (HHMI) International Student Research Fellow. D.S.L. was supported by NIH Training Grant T32 GM07092-34. J.L.D. is an Investigator of the HHMI, supported by the HHMI and the
Gordon and Betty Moore Foundation (GBMF3030). M.E.F. was supported by NIH Dr. Ruth L. Kirschstein NRSA Fellowship F32-GM112345. D.A.P. and T.-Y.L. were supported by the Genomic Science Program, US Department of Energy, Office of Science, Biological and Environmental Research as part of the Oak Ridge National Laboratory Plant Microbe Interfaces Scientific Focus Area (http://pmi.ornl.gov) and Plant Feedstock Genomics Award DE-SC001043. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. J.A.V. was supported by a SystemsX.ch grant (Micro2X) and a European Research Council (ERC) advanced grant (PhyMo). We thank I. Bertani, C. Bez, R. Bowers, D. Burstein, A. Chun Chen, D. Chiniquy, B. Cole, O. Cohen, A. Copeland, J. Eisen, E. Eloe-Fadrosh, M. Hadjithomas, O. Finkel, H. Schnitzel Meule Fux, N. Ivanova, J. Knelman, R. Malmstrom, R. Perez-Torres, D. Salomon, R. Sorek, T. Mucyn, R. Seshadri, T.K. Reddy, L. Ryan, and H. Sberro Livnat for general help, text editing, and ideas for this work. We thank R. Walcott (University of Georgia, Athens, GA, USA) for providing the Acidovorax citrulli VasD mutant strain.
Author contributionsA.L. performed most data analysis and wrote the paper. I.S.G. performed phylogenetic inference, performed phylogenetically aware analyses, analyzed the data, provided the supporting website, and contributed to manuscript writing. M. Mittelviefhaus and J.A.V. designed and performed experiments related to Hyde1 gene function and contributed to manuscript writing. S.C. isolated single bacterial cells and prepared metadata for data analysis. F.M. analyzed data. S.H.P. analyzed data and contributed to manuscript writing. J.M. produced a mutant strain for Hyde1. K.W. tested Hyde1 toxicity in E. coli. G.D. and V.V. produced deletion mutants and designed and performed rice root colonization experiments. K.S. helped in data analysis. B.R.A. prepared metadata for data analysis. D.S.L., T.-Y.L., S.L., Z.J., M. McDonald, A.P.K., M.E.F., and S.L.D. isolated bacteria from different plants or managed this process. T.G.d.R. managed the sequencing project. S.R.G., D.A.P., and R.E.L. managed bacterial isolation efforts and contributed to manuscript writing. B.Z. managed Hyde1 deletion and toxicity testing. S.G.T. contributed to manuscript writing. T.W. managed single-cell isolation efforts and contributed to manuscript writing. J.L.D. directed the overall project and contributed to manuscript writing.
Competing interestsJ.L.D. is a cofounder of and shareholder in, and S.H.P. collaborates with, AgBiome LLC, a corporation that aims to use plant-associated microbes to improve plant productivity.
Additional informationSupplementary information is available for this paper at https://doi.org/10.1038/s41588-017-0012-9.
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MethodsAdditional method descriptions appear in Supplementary Note 1.
Bacterial isolation and genome sequencing. The detailed isolation procedure is described in Supplementary Note 1. Bacterial strains from Brassicaceae and poplar were isolated via previously described protocols79,80. Poplar strains were cultured from root tissues collected from Populus deltoides and Populus trichocarpa trees in Tennessee, North Carolina, and Oregon. Root samples were processed as described previously15,80. Briefly, we isolated rhizosphere strains by plating serial dilutions of root wash, whereas for endosphere strains, we pulverized surface-sterilized roots with a sterile mortar and pestle in 10 mL of MgSO4 (10 mM) solution before plating serial dilutions. Strains were isolated on R2A agar media, and the resulting colonies were picked and re-streaked a minimum of three times to ensure isolation. Isolated strains were identified by 16S rDNA PCR followed by Sanger sequencing.
For maize isolates, we selected soils associated with Il14h and Mo17 maize genotypes grown in Lansing, NY, and Urbana, IL. The rhizosphere soil samples of each maize genotype were grown at each location and were collected at week 12 as previously described68. From each rhizosphere soil sample, soil was washed and samples were plated onto Pseudomonas isolation agar (BD Diagnostic Systems). The plates were incubated at 30 °C until colonies formed, and DNA was extracted from cells.
For isolation of single cells, A. thaliana accessions Col-0 and Cvi-0 were grown to maturity. Roots were washed in distilled water multiple times. Root surfaces were sterilized with bleach. Surface-sterilized roots were then ground with a sterile mortar and pestle. Individual cells were isolated by flow cytometry followed by DNA amplification with MDA, and 16S rDNA screening as described previously81.
DNA from isolates and single cells was sequenced on next-generation sequencing platforms, mostly using Illumina HiSeq technology (Supplementary Table 3). Sequenced genomic DNA was assembled via different assembly methods (Supplementary Table 3). Genomes were annotated using the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4)23 and deposited at the IMG database (“URLs”), ENA, or Genbank for public use.
Data compilation of 3,837 isolate genomes and their isolation-site metadata. We retrieved 5,586 bacterial genomes from the IMG system (“URLs,” Supplementary Table 1). Isolation sites were identified through a manual curation process that included scanning of IMG metadata, DSMZ, ATCC, NCBI Biosample (“URLs”), and the scientific literature. On the basis of its isolation site, each genome was labeled as plant-associated, NPA, or soil-associated. Plant-associated organisms were also labeled as root-associated when isolated from the endophytic compartments or from the rhizoplane. We applied stringent quality control measures to ensure a high-quality and minimally biased set of genomes:
a. Known isolation site: genomes with missing isolation-site information were filtered out.
b. High genome quality and completeness: all isolate genomes passed this filter if N50 (the shortest sequence length at 50% of the genome) was more than 50,000 bp. Single amplified genomes passed the quality filter if they had at least 90% of 35 universal single-copy clusters of orthologous groups (COGs)82. In addition, we used CheckM83 to assess isolate genome completeness and contamination. Only genomes that were at least 95% complete and no more than 5% contaminated were used.
c. High-quality gene annotation: genomes that passed this filter had at least 90% genome sequence coding for genes, with an exception—in the Bartonella genus most genomes have coding base percentages below 90%.
d. Nonredundancy: we computed whole-genome average nucleotide identity and alignment fraction values for each pair of genomes84. When the alignment fraction exceeded 90% and the whole-genome average nucleotide identity was greater than 99.995% we considered the genome pair redundant. In such cases one genome was randomly selected, and the other genome was marked as redundant and was filtered out.
e. Consistency in the phylogenetic tree: we filtered out 14 bacterial genomes that showed discrepancy between their given taxonomy and their actual phylogenetic placement in the bacterial tree.
Construction of the bacterial genome tree. To generate a phylogenetic tree of the 3,837 high-quality and nonredundant bacterial genomes, we retrieved 31 universal single-copy genes from each genome with AMPHORA285. For each individual marker gene, we used Muscle with default parameters to construct an alignment. We masked the 31 alignments by using Zorro86 and filtered the low-quality columns of the alignment. Finally, we concatenated the 31 alignments into an overall merged alignment, from which we built an approximately maximum-likelihood phylogenetic tree with the WAG model implemented in FastTree 2.187. Trees of each taxon are provided in Dataset S5 at http://labs.bio.unc.edu/Dangl/Resources/gfobap_website/faa_trees_metadata.html.
Clustering of 3,837 genomes into nine taxa. We divided the dataset into different taxa (taxonomic groups) to allow downstream identification of genes enriched in the plant-associated or root-associated genomes of each taxon compared with the NPA or soil-associated genomes from the same taxon, respectively. To determine
the number of taxonomic groups to analyze, we converted the phylogenetic tree into a distance matrix, using the cophenetic function implemented in the R package ape (“URLs”). We then clustered the 3,837 genomes into nine groups using k-medoids clustering as implemented in the PAM (partitioning around medoids) algorithm from the R package fpc (“URLs”). The k-medoids algorithm clusters a dataset of n objects into k a priori–defined clusters. To identify the optimal k value for the dataset, we compared the silhouette coefficients for values of k ranging from 1 to 30. We selected a value of k = 9 because it yielded the maximal average silhouette coefficient (0.66). In addition, at k = 9 the taxa were monophyletic, contained hundreds of genomes, and were relatively balanced between plant-associated and NPA genomes in most taxa (Table 1). The resulting genome clusters generally overlapped with annotated taxonomic units. One exception was in the Actinobacteria phylum. Here our clustering divided the genomes into two taxa that we named, for simplicity, Actinobacteria 1 and Actinobacteria 2. However, our rigorous phylogenetic analysis supports previous suggestions for revisions in the taxonomy of phylum Actinobacteria88.
In addition, the tree showed very divergent bacterial taxa in the Bacteroidetes phylum that could not be separated into monophyletic groups. Specifically, the Sphingobacteriales order (from class Sphingobacteria) and the Cytophagaceae (from class Cytophagia) are paraphyletic. Therefore, we decided to unify all Bacteroidetes into one phylum-level taxon. Analysis of the prevalence of the nine taxa in 16S rDNA and metagenome appears in the Supplementary Information.
Pangenome analysis. For each comparison in Supplementary Fig. 2, a random set of ten genomes from each environment (plant-associated and NPA from specific environments) was selected, and the mean and s.d. of the phylogenetic distance in the set were calculated. This step was repeated 50 times to produce two random sets of genomes (plant-associated and NPA) that were comparable and had minimum differences between their mean and s.d. of phylogenetic distances. Genes for pangenome analysis were taken from the orthogroups (see below). Core genome, accessory genome, and unique genes were defined as genes that appeared in all ten genomes, in two to nine genomes, and in only one genome, respectively. For core and accessory genomes, the median copy number in each relevant orthogroup was used.
Genome size comparison and gene category enrichment analysis. Genome sizes were retrieved from the IMG database (“URLs”) and compared by t-test and PhyloGLM26. Kernel density plots from the R sm package (“URLs”) were used to prepare Supplementary Fig. 1. Protein-coding genes were retrieved and mapped to COG IDs with the program RPS-BLAST at an e-value cutoff of 1e–2 and an alignment length of at least 70% of the consensus sequence length. Each COG ID was mapped to at least one COG category (Supplementary Table 6). For each genome, we counted the number of genes from a given category. A t-test and PhyloGLM test were used to compare the number of genes in the genomes that shared the same taxon and category but different labels (e.g., plant-associated versus NPA).
Benchmarking gene clustering with UCLUST and OrthoFinder. We computed clusters of coding sequences across each of the nine taxa defined above with two algorithms: UCLUST89 (v 7.0) and OrthoFinder24 (v 1.1.4). UCLUST was run with 50% identity and 50% coverage in the target to call the clusters. Command used: usearch7.0.1090_i86linux64 -cluster_fast < input_file > -id 0.5 -maxaccepts 0 -maxrejects 0 -target_cov 0.5 –uc < output_file > . To improve pairwise alignment performance, we used the accelerated protein alignment algorithm implemented in DIAMOND90 (v 0.8.36.98) with the --very-sensitive option in the DIAMOND BLASTP algorithm. After computing the alignments, we ran OrthoFinder with default parameters. See “URLs” for the scripts used to compute the orthogroups.
Supplementary Fig. 5 shows benchmarking of OrthoFinder against UCLUST. To estimate the quality of the clusters output by UCLUST and OrthoFinder, we mapped the proteins from our datasets to the curated set of taxon markers from Phyla-AMPHORA91. Next, we compared the distribution of each of the taxon-specific markers identified by Phyla-AMPHORA across the clusters output by UCLUST and OrthoFinder. To compare the two approaches, we estimated two metrics: the purity and the fragmentation index, explained in Supplementary Fig. 5 and in the Supplementary Information.
Identification of plant-associated, NPA, root-associated, and soil genes/domains. The following description applies to plant-associated, NPA, root-associated, and soil genes. For conciseness, only plant-associated genes are described here. Plant-associated genes were identified via a two-step process that included protein/domain clustering on the basis of amino acid sequence similarity and subsequent identification of the protein/domain clusters significantly enriched in proteins/domains from plant-associated bacteria (Supplementary Fig. 4). Clustering of genes and protein domains involved five independent methods: OrthoFinder24, COG20, KEGG Orthology (KO)21, TIGRFAM22, and Pfam25. OrthoFinder was selected (after the aforementioned benchmarking) as a clustering approach that included all proteins, including those that lack any functional annotation. We first compiled, for each taxon separately, a list of all proteins in the genomes. For COG, KO, TIGRFAM, and Pfam, we used the existing annotations
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of IMG genes that are based on BLAST alignments to the different protein/domain models23. This process yielded gene/domain clusters. Next, we determined which clusters were significantly enriched with genes derived from plant-associated genomes. These clusters were termed plant-associated clusters. In the statistical analysis, we used only clusters of more than five members. We corrected P values with Benjamini–Hochberg FDR and used q < 0.05 as the significance threshold, unless stated otherwise. The proteins in each cluster were categorized as either plant-associated or NPA, on the basis of the label of the encoding genome. Namely, a plant-associated gene is a gene derived from a plant-associated gene cluster and a plant-associated genome.
The three main approaches were the hypergeometric test (Hyperg), PhyloGLM, and Scoary. Hyperg looks for overall enrichment of gene copies across a group of genomes but ignores the phylogenetic structure of the dataset. PhyloGLM26 takes into account phylogenetic information to eliminate apparent enrichments that can be explained by shared ancestry. The Hyperg and PhyloGLM tests were used in two versions, based on either gene presence/absence data (hypergbin, phyloglmbin) or gene copy-number data (hypergcn, phyloglmcn). We also used a stringent version of Scoary27, a gene presence/absence approach that combines Fisher’s exact test, a phylogenetic test, and a label-permutation test. The first hypergeometric test, hypergcn, used the gene copy-number data, with the cluster being the sample, the total number of plant-associated and NPA genes being the population, and the number of plant-associated genes within the cluster being considered as ‘successes’. The second version, hybergbin, used gene presence/absence data. P values were corrected by Benjamini–Hochberg FDR92 for clusters of COG/KO/TIGRFAM/Pfam. For the abundant OrthoFinder clusters, we used Bonferroni correction with a threshold of P < 0.1, as downstream validation with metagenomes showed fewer false positives with the more significant clusters. The third and fourth statistical approaches used PhyloGLM26, implemented in the phylolm (v 2.5) R package (“URLs”). PhyloGLM combines a Markov process of lifestyle (e.g., plant-associated versus NPA) evolution with a regularized logistic regression. This approach takes advantage of the known phylogeny to specify the residual correlation structure between genomes that share common ancestry, and so it does not need to make the incorrect assumption that observations are independent. Intuitively PhyloGLM favors genes found in multiple lineages of the same taxon. For each taxon we used the subtree from Fig. 1a to estimate the correlation matrix between observations and used the copy number (in phyloglmcn) or presence/absence pattern (in phyloglmbin) of each gene as the only independent variable. Positive and negative estimates in phyloglmbin/phyloglmcn indicated plant-associated/root-associated and NPA/soil-associated proteins/domains, respectively.
Finally, the fifth statistical approach was Scoary27, which uses a gene presence/absence dataset. Scoary combines Fisher’s exact test, a phylogeny-aware test, and an empirical label-switching permutation analysis. A gene cluster was considered significant by Scoary only if (1) it had a q-value less than 0.05 for Fisher’s exact test, (2) the ‘worst’ P value from the pairwise comparison algorithm was < 0.05, and (3) the empirical (permutation-based) P value was < 0.05. These are very stringent criteria that yielded relatively few significant predictions. Odds ratios greater than or less than 1 in Scoary indicated plant-associated/root-associated and NPA/soil-associated proteins/domains, respectively.
See “URLs” for links to the code used for the gene enrichment tests. A description of additional assessment of plant-associated/NPA prediction robustness using validation genome datasets is presented in Supplementary Note 1.
Validation of predicted plant-associated, NPA, root-associated, and soil-associated genes using metagenomes. Metagenome samples (n = 38; Supplementary Table 16) were downloaded from NCBI and GOLD (“URLs”). The reads were translated into proteins, and proteins at least 40 amino acids long were aligned using HMMsearch93 against the different protein references. The protein references included the predicted plant-associated, root-associated, soil-associated, and NPA proteins from OrthoFinder that were found to be significant by the different approaches. The normalization process is explained in Supplementary Figs. 12–16.
Principal coordinates analysis. To visualize the overall contribution of statistically significant enriched/depleted orthogroups to the differentiation of plant-associated and NPA genomes, we used principal coordinates analysis (PCoA) and logistic regression. For each of the nine taxa analyzed, we ran this analysis over a collection of matrices. The first matrix was the full pan-genome matrix, which depicted the distribution of all the orthogroups contained across all the genomes in a given taxon. The subsequent matrices represented subsets of the full pan-genome matrix; each of these matrices depicted the distribution of only the statistically significant orthogroups as called by one of the five different algorithms used to test for the genotype–phenotype association. A full description of this process is presented in Supplementary Note 1.
We used the function cmdscale from the R (v 3.3.1) stats package to run PCoA over all the matrices described above, using the Canberra distance as implemented in the vegdist function from the vegan (v 2.4-2) R package (“URLs”). Then, we took the first two axes output from the PCoA and used them as independent variables to fit a logistic regression over the labels of each genome (plant-associated, NPA). Finally, we computed the Akaike information criterion for each of the different
models fitted. Briefly, the Akaike information criterion estimates how much information is lost when a model is applied to represent the true model of a particular dataset. See “URLs” for a link to the scripts used to perform the PCoA.
Validation of plant-associated genes in Paraburkholderia kururiensis M130 affecting rice root colonization. Growth and transformation details of P. kururiensis M130 are described in Supplementary Note 1.
Mutant construction. Internal fragments of 200–900 bp from each gene of interest were PCR-amplified with the primers listed in Supplementary Table 17c. Fragments were cloned in the pGem2T easy vector (Promega) and sequenced (GATC Biotech; Germany), then excised with EcoRI restriction enzyme and cloned in the corresponding site in pKNOCK-Km R94. These plasmids were then used as a suicide delivery system to create the knockout mutants and transferred to P. kururiensis M130 by triparental mating. All the mutants were verified by PCR with primers specific to the pKNOCK-Km vector and to the genomic DNA sequences upstream and downstream from the targeted genes.
Rhizosphere colonization experiments with P. kururiensis and mutant derivatives. Seeds of Oryza sativa (BALDO variety) were surface-sterilized and then left to germinate in sterile conditions at 30 °C in the dark for 7 d. Each seedling was then aseptically transferred into a 50-mL Falcon tube containing 35 mL of half-strength Hoagland solution semisolid substrate (0.4% agar). The tubes were then inoculated with 107 colony-forming units (cfu) of a P. kururiensis suspension. Plants were grown for 11 d at 30 °C (16/8-h light/dark cycles). For the determination of the bacterial counts, plants were washed under tap water for 1 min and then cut below the cotyledon to excise the roots. Roots were air-dried for 15 min, weighed, and then transferred to a sterile tube containing 5 mL of PBS. After vortexing, the suspension was serially diluted to 10−1 and 10−2 in PBS, and aliquots were plated on KB plates containing the appropriate antibiotic (rifampicin 50 µ g/mL for the wild type, rifampicin 50 µ g/mL and kanamycin 50 µ g/mL for the mutants). After 3 d of incubation at 30 °C, we counted colony-forming units (CFU). Three replicates for each dilution from ten independent plantlets were used to determine the average CFU values.
Plant-mimicking plant-associated and root-associated proteins. Supplementary Fig. 21 summarizes the algorithm used to find plant-mimicking plant-associated and root-associated proteins. Pfam25 version 30.0 metadata were downloaded. Protein domains that appeared in both Viridiplantae and bacteria and occurred at least two times more frequently in Viridiplantae than in bacteria were considered as plant-like domains (n = 708). In parallel, we scanned the set of significant plant-associated, root-associated, NPA, and soil-associated Pfam protein domains predicted by the five algorithms in the nine taxa. We compiled a list of domains that were significantly plant-associated/root-associated in at least four tests, and significantly NPA/soil-associated in up to two tests (n = 1,779). The overlapping domains between the first two sets were defined as PREPARADOs (n = 64). In parallel, we created two control sets of 500 random plant-like Pfam domains and 500 random plant-associated/root-associated Pfam domains. Enrichment of PREPARADOs integrated into plant NLR proteins in comparison to the domains in the control groups was tested by Fisher’s exact test. To identify domains found in plant disease-resistance proteins, we retrieved all proteins from Phytozome and BrassicaDB (“URLs”). To identify domains in plant disease-resistance proteins, we used hmmscan to search protein sequences for the presence of NB-ARC (PF00931.20), TIR (PF01582.18), TIR_2 (PF13676.4), or RPW8 (PF05659.9) domains. Bacterial proteins carrying the PREPARADO domains were considered as having full-length identity to fungal, oomycete, or plant proteins on the basis of LAST alignments to all Refseq proteins of plants, fungi, and protozoa. “Full-length” is defined here as an alignment length of at least 90% of the length of both query and reference proteins. The threshold used for considering a high amino acid identity was 40%. An explanation of the prediction of secretion of proteins with PREPARADOs is presented in the Supplementary Information.
Prediction of plant-associated, NPA, root-associated, and soil-associated operons and their annotation as biosynthetic gene clusters. Significant plant-associated, NPA, root-associated, and soil-associated genes of each genome were clustered on the basis of genomic distance: genes sharing the same scaffold and strand that were up to 200 bp apart were clustered into the same predicted operon. We allowed up to one spacer gene, which is a non-significant gene, between each pair of significant genes within an operon. Operons were predicted for the genes in COG and OrthoFinder clusters using all five approaches. Operons were annotated as biosynthetic gene clusters if at least one of the constituent genes was part of a biosynthetic gene cluster from the IMG-ABC database95.
Jekyll and Hyde analyses. To find all homologs and paralogs of Jekyll and Hyde genes, we used IMG BLAST search with an e-value threshold of 1e–5 against all IMG isolates. We searched Hyde1 homologs of Acidovorax, Hyde1 homologs of Pseudomonas, Hyde2, and Jekyll genes using proteins of genes Aave_1071, A243_06583, Ga0078621_123530, and Ga0102403_10160 as the query sequence, respectively. Multiple sequence alignments were done with Mafft96. A phylogenetic
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tree of Acidovorax species was produced with RaxML97, based on concatenation of 35 single-copy genes98.
Hyde1 toxicity assay. To verify the toxicity of Hyde1 and Hyde2 proteins to E. coli, we cloned genes encoding proteins Aave_0990 (Hyde2), Aave_0989 (Hyde1), and Aave_3191 (Hyde1), or GFP as a control, to the inducible pET28b expression vector via the LR reaction. The recombinant vectors were transformed into E. coli C41 competent cells by electroporation after sequencing validation. Five colonies were selected and cultured in LB liquid media supplemented with kanamycin with shaking overnight. The OD600 of the bacterial culture was adjusted to 1.0, and then the culture was diluted by 102, 104, 106, and 108 times successively. Bacteria culture gradients were spotted (5 μ L) on LB plates with or without 0.5 mM IPTG to induce gene expression.
Construction of ∆5-Hyde1 strain. Details of the construction of the ∆ 5-Hyde1 strain are presented in Supplementary Note 1. A. citrulli strain AAC00-1 and its derived mutants were grown on nutrient agar medium supplemented with rifampicin (100 µ g/ml). To delete a cluster of five Hyde1 genes (Aave_3191–3195), we carried out a marker-exchange mutagenesis as previously described99. The marker-free mutant was designated as ∆ 1-Hyde1, and its genotype was confirmed by PCR amplification and sequencing. The marker-exchange mutagenesis procedure was repeated to delete four other Hyde1 loci (Supplementary Fig. 28). The primers used are listed in Supplementary Table 25. The final mutant, with deletion of 9 out of 11 Hyde1 genes (in five loci), was designated as ∆ 5-Hyde1 and was used for competition assay. The ∆ T6SS mutant was provided by Ron Walcott’s lab.
Competition assay of Acidovorax citrulli AAC00-1 against different strains. Bacterial strains. E. coli BW25113 pSEVA381 was grown aerobically in LB broth (5 g/L NaCl) at 37 °C in the presence of chloramphenicol. Naturally antibiotic-resistant bacterial leaf isolates16 and Acidovorax strains were grown aerobically in NB medium (5 g/L NaCl) at 28 °C in the presence of the appropriate antibiotic. Antibiotic resistance and concentrations used in the competition assay are mentioned in Supplementary Table 25.
Competition assay. Competition assays were conducted similarly as described elsewhere66,100. Briefly, bacterial overnight cultures were harvested and washed in PBS (pH 7.4) to remove excess antibiotics, and resuspended in fresh NB medium to an optical density of 10. Predator and prey strains were mixed at a 1:1 ratio, and 5 µ L of the mixture was spotted onto dry NB agar plates and incubated at 28 °C. As a negative control, the same volume of NB medium was mixed with prey cells instead of the predator strain. After 19 h of coincubation, bacterial spots were excised from the agar and resuspended in 500 µ L of NB medium and then spotted on NB agar containing antibiotic selective for the prey strains. CFUs of recovered prey cells were determined after incubation at 28 °C. All assays were performed in at least three biological replicates.
Life sciences reporting summary. Further information on experimental design is available in the Life Sciences Reporting Summary.
Data availability. All new genomes (Supplementary Table 3) were submitted and are publicly available in at least one of the following databanks (see accessions in Supplementary Table 3):
1. IMG/M, https://img.jgi.doe.gov/cgi-bin/m/main.cgi2. Genbank, https://www.ncbi.nlm.nih.gov/genbank/3. ENA, http://www.ebi.ac.uk/ena4. A dedicated website for the Dangl lab: http://labs.bio.unc.edu/Dangl/
Resources/gfobap_website/index.htmlThe dedicated website contains nucleotide and amino acid FASTA files of all
datasets used, protein/domain annotations (COG, KO, TiGRfam, Pfam), metadata, phylogenetic trees, OrthoFinder orthogroups, orthogroup hidden Markov models, full enrichment datasets, correlation between orthogroups, and predicted operons (“URLs”).
Links to different scripts that were used in analysis are included in the “URLs” section. The full genome sequence, gene annotation, and metadata of each genome
used can be found at the IMG website (https://img.jgi.doe.gov/). For example, the metadata of taxon ID 2558860101 can be found at https://img.jgi.doe.gov/cgi-bin/mer/main.cgi?section= TaxonDetail&page= taxonDetail&taxon_oid= 2558860101.
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Describe how sample size was determined. Computational analysis is done based on sample size in the order of hunderds. Experiments were done with sample size of 3-30 biological replicates.
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Mostly irrelevant to the study. In the few cases where we used randomizations we made sure the randomized control group has similar features to the tested group. For example in the randomization done for PREPARADOs enrichment in planr NLR immune proteins we randomly sampled 500 PA/RA domains and 500 plant protein domains.
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