Exploring The Fruit Microbiome

Michael Wisniewski, Samir Droby

USDA-ARS, Kearneysville, WV, ARO, Israel,

2009 – Twenty year Review –New Paradigm

BARD Sponosored WorkshopFormation of ISHS Working Group Which Has Met

Every Two Years – Last Meeting in Belgium

2016 – Special Issue of PB&TComprehensive Review of All Alternative

Approaches to Postharvest Disease Control and the Development and Commercialization of Biocontrol

ProductsJOURNEY FROM SIMPLICITY TO COMPLEXITY

2018 – Emphasized the Relevance of Microbiome-Based Research to

Postharvest BiocontrolPresent BARD-Sponsored Workshop 2019

Networks, MetaOrganism, Holobiont, Synthetic

Biology

How do Concepts Related to the Microbiome Apply to Fruit

Is There a Core Apple Microbiome

Do Genotypes Influence the Composition of the Microbiome and Vice Versa

Can We Develop and Utilize Different Functional Microbiomes

How can we utilize knowledge of the Microbiome to Develop Biological Solutions

to Disease, Quality, and Food Safety Problems

Spatial and Compositional Variation in Organic and

Conventionally Grown Fruit

Abelfattah, A., et al. Horticulture Research 2016. 3:16047

Characterize the Microbiome of Different Portions of the Apple

(Stem End, Calyx End, Peel, and Wounds)

Abdelfattah et al. 2016 nature.com/hortres 5

1) Apple fungal communities

Figure 1 Left) Sunburst chart showing the total relative abundance of fungal phyla (interior circle) and classes (exterior circle) overall detected in investigated samples.Right) Pie chart showing the total relative abundance of fungal genera detected across all samples.

1 2 3 45 6 7 89 10 11 1213 14 15 1617 18 19 2021 22 23 2425 26 27 2829 30 31 3233 34 35 3637 38 39 4041 42 43 4445 46 47 4849 50 51 5253 54 55 5657 58 59 6061 62 63 6465 66 67 6869 70 71 7273 74 75 7677 78 79 8081 82 83 8485 86 87 88

8000 OTUs, 5 phyla, and > 350 genera

Peel

Wound CE

SE

PCoA plot of beta diversity in different portions of the apple based on Bray Curtis dissimilarity metrics.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Peel Wound CE SE

Rel

ativ

eab

un

dan

ce%

Fruit Location

Fungal general ≥ 1% present in the Apple’s 4 locations

othertaxa

Wickerhamomyces 1%

Sporobolomyces 1%

Ustilago1%

Metschnikowia1.1%

Stemphylium 1.2%

Chalastospora1.2%

Aspergillus 1.5%

Piloderma1.5%

Candida1.5%

Unidentified Pleosporales 1.8%

Phaeosphaeria 2%

Ulocladium2%

unidentified2.2%

Trichosporon 2.6%

Acremonium 3.1%

Aureobasidium 3.3%

Unidentified Dothideomycetes 3.3%

Malassezia4.6%

Didymella4.7%

Cladosporium5.1%

Mycosphaerella 6.3%

Alternaria6.6%

Penicillium 8%

Cryptococcus 9.2%

Note species diversity in peel tissuesAbundance of

Penicillium in Wound Tissues

Abundance of Alternaria in Stem and

Calyx Tissue

Cryptococcus

Penicillium

Alternaria

CladosporiumMycosphaerella

Is There a Core Apple Microbiome

USA (WA, NY, WV), Israel, Turkey, Italy, Spain, Switzerland, Uruguay, Canada (Ontario, New

Brunswick)

Two Orchards in Each Country

‘Royal Gala’Harvest Maturity

Three Tissue Types (Calyx, Stem, Peel)

Geographical, Climatic, Management Data

IS, Trk, SP, It, SW, WV, NY, WA

ITS

NY vs. WA

ITS

The Endophytic Microbiome of Apple Trees is Influenced by Genotype

Endophytic Populations – 16S and ITS – Illumina Sequencing

Liu et al. 2018. Microbiome 6:18

Honey Crisp

Golden Delicious

Royal Gala

GD

HC

RG GD

RG

HC

PCoA Clustering of the Fungal Microbiome of Different Apple Scions

Apple Pedigrees

M.9 – Unknown Pedigree

Old French Genotype

Merton 793

Northern SpyMM.111

Volk, G. et al. 2015. Chloroplast heterogeneity and historical admixture within the genus Malus. Amer. J. Bot 102: 1198-

1208

Asian Group

North American Group

M. domestica Admixture

Effect of Management Practices on Apple MicrobiomeWashing, Waxing, Low-Temperature Storage

Unwashed, Washed Only, Washed then Waxed Stored for 6 months at Low Temperature (1-2oC),

Bacteria and Fungi

Shield-Brite® AP-40 commercial Shellac Coating

‘Enterprise’

ResultsBacteria

Time: Alpha Diversity - Significant Difference between T0 and All Months. Beta Diversity –Significant Differences between all months.

Tissue: Alpha Diversity – Significant

Difference Between All Tissue-types. Beta Diversity – Significant Difference Between All Tissue – types

Treatment: Alpha Diversity – Significant Difference Between Unwashed and Other Treatments (Washing and Washing and Waxing). Beta Diversity – Significant Difference Between All Treatments.

Beta Diversity

FDR-p values

ResultsFungi

Time: Alpha Diversity - Significant Difference between T0 and 2 Months. Beta Diversity –Significant Differences between all months.

Tissue: Alpha Diversity – Significant

Difference Between All Tissue-types. Beta Diversity – Significant Difference Between All Tissue – types

Treatment: Alpha Diversity – Significant Difference Between Unwashed and Other Treatments (Washing and Washing and Waxing). Beta Diversity – Significant Difference Between All Treatments.

Beta Diversity

FDR-p values

A

C

E

B

D

F

ITSTissue

Calyx

Peel

Stem

ITSTreatment

UW

W

WW

16sTime

2 M

4 M

6 M

0 M

16sTissue

Calyx

Peel

Stem

16sTreatment

UW

W

WW

ITSTime

2 M

4 M

6 M

0 M

Bacterial Taxa

Tissue-TypePeel vs. CalyxFirmicutes (Baccili)

Planctomycetes

Armitimonadales

Nitrospirales

Sphingobacteria

Flavobacteria

Actinomycetales

Peel vs. StemFirmicutes (Baccili)

Sphingobacteria

Cytophagales

Flavobacteria

Acidomicrobiales

Coriobacteriales

MetaCoder

Treatment

Bacterial Taxa

MetaCoder

Fungal Taxa

Tissue-Type

MetaCoder

Treatment

Fungal Taxa

MetaCoder

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UW W WW

Ab

un

dan

ce

Treatment

Bacterial Composition by Treatment (>1% of Genera)

unclassified_Bacillales

unclassified_Oxalobacteraceae

Aeromicrobium

unclassified_Comamonadaceae

unclassified_Sphingomonadaceae

Janthinobacterium

Agrobacterium

unclassified_Methylocystaceae

Methylobacterium

unclassified_Microbacteriaceae

Sphingomonas

Pseudomonas

unclassified_Enterobacteriaceae

unclassified_Bacteria

Enterobacteriaceae

Pseudomonas

Methylobacterium

Bacteria by Treatment

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Stem Calyx Peel

Ab

un

dan

ce

Tissue

Bacterial Composition by Tissue (>1% of Genera)

unclassified_Bacillales

unclassified_Oxalobacteraceae

Aeromicrobium

unclassified_Comamonadaceae

unclassified_Sphingomonadaceae

Janthinobacterium

Agrobacterium

unclassified_Methylocystaceae

Methylobacterium

unclassified_Microbacteriaceae

Sphingomonas

Pseudomonas

unclassified_Enterobacteriaceae

unclassified_Bacteria

Bacteria by Tissue-Type

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UW W WW

Ab

un

dan

ce

Treatment

Fungal Composition by Treatment (>1% of Genera)

Vishniacozyma

Golubevia

Sarocladium

Paraconiothyrium

Alternaria

Cladosporium

unclassified_Capnodiales

Ramularia

Penicillium

unclassified_Pleosporales

Pseudomicrostroma

unclassified_Ascomycota

Aureobasidium

unclassified_Pleosporaceae

Cladosporium

Unclassified AscomycotaAureobasidium

Penicillium

Pseudomicrostroma(Rhodoturula)

Fungi by Treatment

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Stem Calyx Peel

Ab

un

dan

ce

Tissue

Fungal Composition by Tissue (>1% of Genera)

Vishniacozyma

Golubevia

Sarocladium

Paraconiothyrium

Alternaria

Cladosporium

unclassified_Capnodiales

Ramularia

Penicillium

unclassified_Pleosporales

Pseudomicrostroma

unclassified_Ascomycota

Aureobasidium

unclassified_Pleosporaceae

Penicillium

Fungi by Tissue-Type

AureobasidiumAlternariaPseudomicrostroma

(Rhodoturula)

31

L. monocytogenes survival in Enterprise apples, as affected by washing and application of commercial wax.

Effect of postharvest washing and waxing on applethe persistence of foodborne pathogens

Malus sieversii: Progenitor of Modern Apple

qM-Pe3.1, 28% var

BpMADS4 Female Parent

Introgression qM-Pe3.1

• {[‘Royal Gala’ X PI613981) X ‘Pinova’-BpMADS4] X ‘Enterprise’}

Endophytes

Epiphytes

Microbial Metabolites

Fruit Metabolites

Phyto-hormones

Immune Responses

Pathogens

Moving from simplicity to complexity

How Can Microbiome Studies Be Applied to the Development of Biocontrol Systems ?

Can microbiome studies inform us about postharvest pathology (spatial and genotypic resistance and

susceptibility) ?

Can an understanding of the functional interactions on pre-and post-harvested fruit lead to the development of better

biocontrol systems ?

Can microbiome studies be used to develop functional and spatially informed consortia that support both plant and

human health?

Acknowledgements

Erik BurchardAhmed Abdelfattah

Shiri Freilich

Global Study

Scientists from All the Participating Countries

Adam Rivers – USDA-ARSRavin Poudel – USDA-ARS

Edoardo PiemboDavide SpadoroRosario TorresNeus TeixidoSilvana Vero

Domestication Study

Staff at the USDA-ARS Apple Germplasm Repository

Jia Liu

Waxing Study

Dumitru MacarisinShiri Freilich

Susan Whitehead

General AcknowlegementsGabrielle Berg

Students and Colleagues

Questions