understanding the olive microbiome of susceptible …...understanding the olive microbiome of...

Understanding the olive microbiome

of susceptible and resistant cultivars

for sustainable biocontrol

1 2 3 4

Baptista P1, Cameirão C1, Giampetruzzi A3, Morelli M4, Abou Kubaa R4, Altamura

G4, D’Attoma G4, Pereira JA1, Lino Neto T2, Sisto A4, De Bellis P4, Saldarelli P4

Fra

mew

ork

Does the endophytic microbiota play any

role in disease resistance?

Olive Quick Decline Syndrome

(OQDS)

Apulian Region (southern Italy)

Infected olive tree

ResistantSusceptible

FS17Kalamata

Xylella

Endophytes

Aim

s

1) Evaluate the dynamics of endophytes and Xylella

communities in susceptible and resistant olive cultivars

2) Evaluate the role of endophytic communities in the

expression of OQDS symptoms

3) Identify potential endophytes with antagonistic activity

against Xylella

Xylem vessel

Infected olive tree

ResistantSusceptible

FS17Kalamata

Xylella

Endophytes

1

2

3

April 2017 and November 2018

Ap

pro

ac

h

Mic

rob

iom

eX

yle

lla

abundance

DNA extraction from xylem wood shavings

Bacteria Fungi

DNA shotgun sequencing

Oliv

e t

wig

s

colle

ction

qPCR

Collection in Sannicola

(outbreak area in Italy)

FS17 Kalamata

Res Sus

NextSeq 500 with 2x150bp reads

400 M read pairs/ 120 Gb raw data

12 trees FS17(6 High; 6 Low)

12 trees Kalamata(6 High; 6 Low )

Res Sus

V3-V4 region ITS1 region

Bacteria Fungi

Illumina

23%

15%

14%10%

8%

6%

5%

3%

2%2%

2%

2% 2%

WallemiaMitosporidiumOthersLobosporangiumColletotrichumPhycomycesParacoccidioidesAspergillusBlastomycesLodderomycesPucciniaCoccidioidesHistoplasmaTrichophytonNeurosporaThermothelomyces)MarssoninaAscoidea

7 phyla

11 classes

23 orders

29 families

35 genera

Ba

cte

ria

Fu

ng

i

4 phyla

13 classes

21 orders

34 families

42 genera

Proteobacteria (75%)Actinobacteria (13%)

Ascomycota (44%)Basidiomycota (25%)

Overa

ll m

icro

bia

l co

mm

un

ity

43%

11%6%

6%

6%

5%

3%

3%

2%2%

2%

2% 2%

XylellaAsaiaOthersMethylobacteriumFriedmanniellaPseudomonasSphingomonasStreptomycesKlebsiellaMycobacteriumBacillusStaphylococcusMycoplasmaHymenobacterBradyrhizobiumBurkholderiaCorynebacteriumLactobacillusStreptococcus

Co

re b

acte

rial

co

mm

un

ity

Resistant FS17 Susceptible Kalamata

2018

To

tal

Methylobacterium

Friedmanniella

Asaia

Xylella

Sphingomonas

Hymenobacter

Asaia

Xylella

Streptomyces

Pseudomonas

Methylobacterium

Mycobacterium

2017

Xylella

Asaia

Staphylococcus

Mycobacterium

Streptococcus

Streptomyces

Xylella

Xylella

Asaia

Methylobacterium

Sphingomonas

Streptomyces

Mycobacterium

Staphylococcus

Mycoplasma

Pseudomonas

Xylella

Asaia

Streptomyces

Mycobacterium

Genera having a 50% prevalence among samples and 0.01% abundance

Xylella tends to totally

occupy the internal tissues

This was particularly

obvious in the cv Kalamata

Co

re b

acte

rial

co

mm

un

ity

Average of Xylella abundance over the total Bacteria

0

20

40

60

80

100

FS17 Kalamata

Xyle

lla

/ b

ac

teri

a (

%)

2017

2018

p<0.05n.s.

Resistant FS17 Susceptible Kalamata

2018

To

tal

2017

WallemiaMitosporidium

LobosporangiumPhycomyces

Paracoccidioides

WallemiaMitosporidium


Paracoccidioides

WallemiaMitosporidiumColletotrichum


Paracoccidioides

WallemiaMitosporidiumColletotrichum


Paracoccidioides

Co

re f

un

gal co

mm

un

ity

Genera having a 50% prevalence among samples and 0.01% abundance

Co

re f

un

gal co

mm

un

ity

Comparison of Xylella abundance over the total Fungi

0%

20%

40%

60%

80%

100%

2017 2018 2017 2018

FS17 Kalamata

Rela

tive a

bundan

ce

Xylella

Bacteria

Fungi

Xylella/Fungi ratio

15.50.90.1 5.7

The increase in Xylella abundance in the second year

inverts the Xylella/Fungi ratio, especially in Kalamata

Ba

cte

ria

Fu

ng

i

Overa

ll m

icro

bia

l d

ivers

ity

10

20

30

40

HIG

HLO

W

Alp

ha

-div

ers

ity I

nd

ex:

Ch

ao

1

CLASS

HIGH

LOW

2

3

4

5

6

HIG

HLO

W

Alp

ha

-div

ers

ity I

nd

ex:

Fis

he

r

CLASS

HIGH

LOW

p=0.016 p<0.001

15

16

17

18

19

HIG

HLO

W

Alp

ha

-div

ers

ity I

nd

ex:

Fis

he

r

CLASS

HIGH

LOW

p=0.005

130

140

150

160

HIG

HLO

W

Alp

ha

-div

ers

ity I

nd

ex:

Ch

ao

1

CLASS

HIGH

LOW

p=0.384

10

20

30

40

FS17

KAL

Alp

ha

-div

ers

ity I

nd

ex:

Ch

ao

1

CLASS

FS17

KAL

p=0.040

2

3

4

5

6

FS17

KAL

Alp

ha

-div

ers

ity I

nd

ex:

Fis

he

r

CLASS

FS17

KAL

p=0.058

15

16

17

18

19

FS17

KAL

Alp

ha

-div

ers

ity I

nd

ex:

Fis

he

r

CLASS

FS17

KAL

p=0.630

130

140

150

160

FS17

KAL

Alp

ha

-div

ers

ity I

nd

ex:

Ch

ao

1

CLASS

FS17

KAL

p=0.260

Xylella abundance Cultivar

Ba

cte

ria

Fu

ng

i

Low

FS17 Kal FS17 Kal

High

RANOSIM=0.66

p=0.001

High

Low

RANOSIM=0.18

p=0.023High

Low

Low

FS17 Kal FS17 Kal

High

Non-metric multidimensional scale plot

Non-metric multidimensional scale plot

Overa

ll m

icro

bia

l co

mp

osit

ion

En

do

ph

yti

cb

ac

teri

a-X

yle

lla

rela

tio

ns

hip

Low

High

FS17

Kal

Co-inertia factorial map of bacterial communities, presenting positive (■) and

negative (□) relationships with cultivars and Xylella abundance

Serr

atia

Bra

dyrh

izobiu

m

Bra

dyrh

izobia

ceae

Eliz

abeth

kin

gia

Candid

atu

s_P

hyto

pla

sm

a

Mic

rom

onospora

Le

pto

tric

hia

His

top

hil

us

Low

High

FS17

Kal

Co-inertia factorial map of fungal communities, presenting positive (■) and

negative (□) relationships with cultivars and Xylella abundance

En

do

ph

yti

cfu

ng

i-X

yle

lla

rela

tio

ns

hip C

olle

totr

ichum

Debary

om

yces

Altern

aria

Beauveria

Wa

lle

mia

Penic

illio

psis

Ve

rru

co

nis

Na

um

ov

ozy

ma

Methylobacterium pseudosasicola

Curtobacterium ammoniigenes

Curtobacterium citreum

Sphingomonas aerolata

Novosphingobium soli


Sphingomonas aquatilis

Sphingomonas insulae


Sphingomonas panacis



Micrococcus yunnanensis

Sphingomonas panacis


Methylobacterium sp.

Methylobacterium phyllostachyos

Curtobacterium ammoniigenes


Sphingomonas sp.

Agrococcus jenensis


Methylobacterium phyllostachyos


Methylobacterium sp.

Sphingomonas sp.


Res

Resistant

FS17

Kalamata

An

tag

on

isti

c a

cti

vit

y a

ga

ins

t X

yle

lla

Susceptible

None of the isolates tested showed

antagonistic effect against X. fastidiosa

Ta

ke

ho

me

no

tes

Xylella dominates the bacterial endophyte community of both cultivars, and becomes the unique genus of the core bacterial community of the susceptible cv. Kalamata, in the 2nd year

This increase in Xylella abundance changeddrastically the diversity and composition ofbacterial community, particularly in the susceptiblecv. Kalamata

These changes might be due to the presence of Xylella that probably encourage the establishment of other bacterial species

Specific bacterial /fungal genera were associated to the high or low abundance of Xylella in each cultivar, and their ability to trigger disease should be studied in the future

Ac

kn

ow

led

gm

en

ts

Teresa Lino Neto

Annalisa GiampetruzziMaria SaponariPasquale SaldarelliMassimiliano MorelliGiusy D’AttomaAbou KubaaAltamura GAngelo SistoDe Bellis P

Cristina CameirãoJosé Alberto PereiraPaula Baptista

understanding the olive microbiome of susceptible …...understanding the olive microbiome of...

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