Modern food safety: Western Health Sciences University ...€¦ · Western Health Sciences University College of Veterinary Medicine Pomona, CA ... Why is this important? !!Functional

Modern food safety: Managing the microbiome of food animals for performance and food safety goals

Brian B. Oakley, M.S., Ph.D. Associate Professor Western Health Sciences University College of Veterinary Medicine Pomona, CA

[email protected]

Importance of microbiota

courtesy of Gregory Plotnikoff, M.D.

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GI microbiome helps control energy balance

Importance of microbiota

Turnbaugh et al. 2006 Nature (444)

Bacteria truly inhabit a “Micro” Biome

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Surface Areas:

Mara-Serengeti = 25,000 km2

Human GI tract = 40 m2

All animals are mostly microbial

Animals are: !! 50-90% bacterial by cell

count !! 90-99% bacterial by gene

count

Veterinary & Food Animal Medicine MUST consider what comprises the majority of the organism

by Gaby D'Allesandro / © AMNH

Can modern food safety go back to the future?

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courtesy of Gregory Plotnikoff, M.D.

Q: Can we move from a mentality of ‘killing bad bugs’ to Ecosystem Management? Current state of the art is development of “Microbial Agriculture”

Microbial Ecology – Nascent field

!! Who is there? !! How many of each? !! What are they doing?

Renaissance of Microbial Ecology !! DNA sequencing costs are decreasing faster than

Moore’s law:

Toolkit of molecular microbial ecology

!!Compositional census

!!16S rRNA !! Taxonomic ID

!!Functional census !! Metagenomics

!!Metabolic potential

!! Metatranscriptomics !!Metabolic activity

Revolutionized by high-throughput sequencing


!!Compositional census

!!16S rRNA !! Taxonomic ID


!!Functional census !! Metagenomics

Renaissance of Microbial Ecology High-throughput sequencing

!! Great plate count anomaly - Has largely removed previous limitations !! Only 0.1 – 1% of taxa cultivable !! ‘uncultured majority’ – Only 26/52 phyla in cultivation

!! Comprehensive census once impossible, now routine

!! Bioinformatic and Computational Advances

Staley and Konopka 1985. Ann Rev Micro Rappe and Giovannoni 2003. Ann Rev Micro

Next-gen sequencing

0 2000 6000 10000

05

00

15

00

25

00

Old-school cloning/Sanger sequencing

Number of sequences

Cum

ulat

ive

num

ber

of s

eque

nce

type

s

NGS Output

Pre-processed dataset

Reformat, parse, build data tables,

map OTUs to taxonomy

OTU/Taxonomy

Assignment

Statistical & Graphical summaries

UCLUST, USEARCH SILVA, PERL

R

mothur

seconds - minutes

PERL

PERL, QIIME

Bioinformatics gives the keys to the kingdom

seconds - minutes

Huse et al. 2007 Gen Biol Quince et al. 2009 Nat Met Kunin et al. 2010 EM

Schloss et al. 2009 AEM Oakley et al. 2012 ISMEJ

Pipeline built from generic building blocks

Importance of Microbial Ecology Can now answer: •! Community composition – who’s there •! Community structure – how many of each •! Community function – what are they doing

!! Humans as ‘super-organisms’ !! New tools applied to microbial

ecosystems in and on our bodies !! “Second genome”

!! ~10x more microbial than human cells

!! ~100x more genes

!! Critical roles in nutrition, health,

disease http://www.nature.com/nature/focus/humanmicrobiota/

HMP – Humans as microbial ecosystems

Poultry microbiology and its importance for food safety

!! ~ 9,000,000,000 broilers processed per yr in U.S.

!! ~ 40,000,000 tons of feed per yr

!! Carbon footprint ~450,000,000,000 car miles yr-1

!! Major source of protein & foodborne illness

!! Microbiome of birds and production system as ‘super-organism’

Renaissance of Microbial Ecology

Broiler Production 101

Grow-out

Hatchery Transport

Consumer

Processing

Can we manage the micro biota?

!!What do natural communities look like?

!!New tools & approaches needed

!!Alternative antimicrobials

!!Can we put it all together? “Seed, Feed, & Weed”

Community changes significantly as bird grows

Temporal differences > feed additives

−3 −2 −1 0 1 2 3

−3−2

−1 0

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3

−3

−2

−1

0

1

2

3

CA1

CA2

CA3

CTL

FO

WO

FW

7d 21d 42d

Figure 1.

What do natural communities look like?

Oakley et al. 2015 BMC Vet Res.

0 7 14 21 28 35 42

050

100

150

200

250

Time (day post-hatch)

Ric

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2.0

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ty (S

hann

on In

dex)

RichnessDiversity

Figure 4.

Time

A)

B)

Network nodesNetwork edges

7d

92

165

21d

122

680

42d

147

611

Community changes significantly as bird grows



Community changes significantly through time …and space

Oakley et al. 2016


Cecal

Fecal

S1F1

S1F2

S1F3

S1F4

S1F5

S2F1

S2F2

S2F3

S2F4

S2F5

S3F1

S3F2

S3F3

S3F4

S3F5

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S4F2

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G3F

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G3F

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G4F

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F1F1

F1F2

F1F3

F1F5

F2F1

F2F2

F2F3

F2F4

F2F5

F3F1

F3F2

F3F3

F3F4

F3F5

F4F1

F4F3

F4F4

F4F5

Prop

ortio

n of

seq

uenc

es

0.0

0.2

0.4

0.6

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1.0

0.0

0.2

0.4

0.6

0.8

1.0

ProteobacteriaFirmicutesBacteroidetesActinobacteriaChrysiogenetesCyanobacteriaSynergistetesTenericutesVerrucomicrobia

S1C

1S1

C3

S1C

4S1

C5

S2C

1S2

C2

S2C

3S2

C4

S2C

5S3

C1

S3C

2S3

C3

S3C

4S3

C5

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C2

S4C

3S4

C4

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n of

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es

FirmicutesBacteroidetesProteobacteriaActinobacteriacandidate ZB3ChrysiogenetesFusobacteriaSpirochaetesSynergistetesTenericutesVerrucomicrobia

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Knowledge of community composition can guide management strategies

0.0

0.2

0.4

0.6

0.8

1.0 Clostridium sensu strictoSyntrophococcusLachnospiracea_i-sLactonifactorPseudoflavonifractorOscillibacterButyricicoccusBlautiaClostridium XlVaFlavonifractorDoreaRoseburia

AnaerotruncusRobinsoniellaHowardellaFaecalibacteriumAminiphilusMahellaSubdoligranulumPapillibacterHydrogenoanaerobacteriumClostridium XVIIIClostridium XlVbAlistipesPr

op. o

f seq

uenc

es

7 d0 d 21 d 42 dCT

L

CTL FO WO FW FO WO FW CTL

FO WO FW

Treatment

Figure 2.

ClostridialesSynergistalesThermoanaerobacteralesBacteroides



Birds exposed to wide range of environmental bacteria, but reproducibly colonized by limited subset…..

PJ Turnbaugh et al. Nature 000, 1-5 (2008) doi:10.1038/nature07540

Humans: Taxonomic variability but functional conservation


0.00

0.25

0.50

0.75

1.00

0.00

0.25

0.50

0.75

1.00

D14_C

D14_M

D14_T

D14_V

D35_C

D35_M

D35_T

D35_V

sample

pro

po

rtio

n

Amino acid transport and metabolism

Carbohydrate transport and metabolism

Cell envelope biogenesis, outer membrane

Coenzyme metabolism

DNA replication, recombination, and repair

Energy production and conversion

Inorganic ion transport and metabolism

Intracellular trafficking and secretion

Nucleotide transport and metabolism

Secondary metabolites biosynthesis, transport, and catabolism

Signal transduction mechanisms

Transcription

Anaerostipes

Anaerotruncus

Blautia

Butyricicoccus

Clostridium IV

Clostridium XlVa

Coprococcus

Escherichia/Shigella

Ethanoligenens

Flavonifractor

Hespellia

Lachnospiracea_i_c

Lactobacillus

Moryella

Papillibacter

Parasporobacterium

Pseudoflavonifractor

Reichenbachiella

Roseburia

D14_C

D14_M

D14_T

D14_V

D35_C

D35_M

D35_T

D35_V

sample

Danzeisen et al. PLoS ONE 2011 Oakley et al. FEMS Micro Let 2014

!! Why is this important? !! Functional redundancy

!! Possible to construct minimal community?


Poultry: Taxonomic variability but functional conservation

Can we manage the microbiota?





Fluorescence in-situ hybridization (FISH) !!Sequence-based discrimination of

bacterial cells (and colonies)

Stringent hybridization and washing

SPECIES A

Ribosome (rRNA + proteins)

Thousands per cell

Thousands per cell

TGCAAGAT TGCAAGAT

TGCAAGAT TGCAAGAT

ACGTTCTA ACGTTCTA ACGTTCTA ACGTTCTA


ACGTTCTA ACGTTCTA

ACGTTCTA

ACGTTCTA ACGTTCTA


ACGTTCTA ACGTTCTA

ACGTTCTA ACGTTCTA ACGTTCTA

ACGTTCTA

ACGTTCTA ACGTTCTA

ACGTTCTA ACGTTCTA

ACGTTCTA ACGTTCTA

ACGTTCTA ACGTTCTA


GGCAAGTT GGCAAGTT

GGCAAGTT GGCAAGTT

SPECIES B

ACGTTCTA ACGTTCTA ACGTTCTA TGCAAGAT TGCAAGAT

TGCAAGAT TGCAAGAT

ACGTTCTA ACGTTCTA

ACGTTCTA

TGCAAGAT

ACGTTCTA ACGTTCTA ACGTTCTA

ACGTTCTA TGCAAGAT TGCAAGAT

ACGTTCTA

GGCAAGTT GGCAAGTT

GGCAAGTT GGCAAGTT

Campylobacter hominis

Campylobacter rectusCampylobacter rectus

Campylobacter showaeCampylobacter gracilis

Campylobacter concisusCampylobacter curvus

Campylobacter mucosalisCampylobacter fetus subsp. venCampylobacter fetus subsp. fetCampylobacter hyointestinalis

Campylobacter hyointestinalis Campylobacter lanienae

Campylobacter coliCampylobacter lari RM2100Campylobacter lari subsp. lariCampylobacter peloridis

Campylobacter insulaenigraeCampylobacter jejuni subsp. jejuni 81116Campylobacter jejuni subsp. jejuni 81−176ATCC33250Campylobacter jejuni subsp. jejuni NCTC 11168Campylobacter jejuni subsp. jeCampylobacter jejuni subsp. doCampylobacter lari subsp. conc

Campylobacter coli RM2228Campylobacter jejuni RM1221

Campylobacter upsaliensisCampylobacter upsaliensis RM3195

Campylobacter helveticusCampylobacter cuniculorum

Campylobacter canadensisArcobacter cryaerophilus

Helicobacter canisHelicobacter sp. ABHU4stomsp

Helicobacter bilisHelicobacter sp. GA−3

Helicobacter sp. CLO−3Helicobacter mastomyrinusHelicobacter sp. hokurin−1

Helicobacter sp. WYS−2001Helicobacter fennelliae

Synechococcus sp. HOG0.10

!!Can use massive rRNA sequence repositories to design specific and sensitive probes:

Fluorescence in-situ hybridization (FISH)

Proteobacteria

Bacteria

Hierarchical probe concept

Campylobacter hominis

Campylobacter rectusCampylobacter rectus

Campylobacter showaeCampylobacter gracilis

Campylobacter concisusCampylobacter curvus

Campylobacter mucosalisCampylobacter fetus subsp. venCampylobacter fetus subsp. fetCampylobacter hyointestinalis

Campylobacter hyointestinalis Campylobacter lanienae

Campylobacter coliCampylobacter lari RM2100Campylobacter lari ATCC 43675Campylobacter peloridis

Campylobacter insulaenigraeCampylobacter jejuni subsp. jejuni 81116Campylobacter jejuni subsp. jejuni 81−176Campylobacter jejuni ATCC 33250Campylobacter jejuni subsp. jejuni NCTC 11168Campylobacter jejuni subsp. jejuni ATCC 49943Campylobacter jejuni subsp. doylei LMG8843Campylobacter lari LMG21009T

Campylobacter coli RM2228Campylobacter jejuni RM1221

Campylobacter upsaliensisCampylobacter upsaliensis RM3195

Campylobacter helveticusCampylobacter cuniculorum

Campylobacter canadensisArcobacter cryaerophilus

Helicobacter canisHelicobacter sp. ABHU4stomsp

Helicobacter bilisHelicobacter sp. GA−3

Helicobacter sp. CLO−3Helicobacter mastomyrinusHelicobacter sp. hokurin−1

Helicobacter sp. WYS−2001Helicobacter fennelliae

0.10

- - A - - - - - - - - - - - - - - -- - A - - - - - - - - - - - - - - -- - A - - - - - - - - - - - - - - -- - A - - - - - - - - - - - - - - -- - A G - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - -

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unlabeled1

unlabeled2

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!"#$%&'()''

* * ** ** * ***+ +, , , , ,-Campylobacter jejuni subsp. jejuni NCTC 11168 labeledCampylobacter jejuni subsp. jejuni ATCC 49943Campylobacter jejuni subsp. doylei LMG8843

Campylobacter jejuni subsp. jejuni NCTC 11168Campylobacter jejuni subsp. jejuni ATCC 49943

labeled

Campylobacter jejuni subsp. jejuni 81116Campylobacter jejuni subsp. jejuni 81−176Campylobacter jejuni ATCC 33250Campylobacter jejuni ATCC 33250

Labeled probe (49943)

Competitor probe (81-176)

Competitor probe (81-176)

Labeled probe (11168)

●

●

●

●

●

●

●

●

0 10 20 30 40 50 60 70

050

100

150

200

Formamide (%)

Rel

ativ

e flu

ores

cenc

e in

tens

ity

● Perfect Match (49943/11168)

Single mismatch plus competitor probeSingle mismatch (81-176/33250)

Three probe cocktail: 1. Campy~Cy3 2. Competitor probe 3. EUB~Alx488

!! New tools & approaches Can we manage the microbiota?

!! Now have direct window to follow individual strains in G-I tract

!! Developed high-throughput image analysis tools

C. jejuni 11168 gavage, image cecal sample directly:

!! New tools & approaches Can we manage the microbiota?






!CP26-F

!CP39-O

Can we manage the microbiota? !! Alternative antimicrobials


•! Amidases

•! Muramidases (Lysozyme)

•! Glucosaminidases

•! Endopeptidases

•! Holins form lesions in bacterial membranes

•! Autolysins and prophage enzymes present in bacterial genomes

Structural modeling suggest potential for mix-and-match use of phage lytic enzyme domains to tailor specificity as alternative antimicrobial agents:

•! N-acetylmuramoyl-L-alanine amidase sequence conservation varies by domain

•! Percent protein sequence conservation is shown from highest 100% (red) to lowest 60% (blue).

Oakley et al. BMC Genomics 2011







Importance of early development

De

sire

d

ph

en

oty

pe

May not be possible to return to desired condition from dysbiotic state

Pert

urb

atio

n

Desired phenotype Dys

bio

sis

Proper management

X ?

?

Poor management

Initial State

Dysbiotic state

Knowledge of community composition can guide management strategies

0.0

0.2

0.4

0.6

0.8

1.0 Clostridium sensu strictoSyntrophococcusLachnospiracea_i-sLactonifactorPseudoflavonifractorOscillibacterButyricicoccusBlautiaClostridium XlVaFlavonifractorDoreaRoseburia

AnaerotruncusRobinsoniellaHowardellaFaecalibacteriumAminiphilusMahellaSubdoligranulumPapillibacterHydrogenoanaerobacteriumClostridium XVIIIClostridium XlVbAlistipesPr

op. o

f seq

uenc

es

7 d0 d 21 d 42 d

CTL

CTL FO WO FW FO WO FW CTL

FO WO FW

Treatment

Figure 2.

ClostridialesSynergistalesThermoanaerobacteralesBacteroides


Managing the micro biota…

0 5 10 15 20 25

0.0

0.2

0.4

0.6

0.8

1.0

Mean cytokine

Rel

ativ

e pr

opor

tion

F

Firmicutes: −0.553Proteobacteria: 0.696


IL6

Microbiome datasets are amenable to high-throughput data mining to identify potentially desirable & undesirable taxa. Statistical associations of particular taxa with pro- and anti-inflammatory cytokines…

Ultimate objective is to manipulate taxonomic composition to achieve desired immune responses…

0 5 10 15 20 25

0.0

0.1

0.2

0.3

0.4

0.5

Mean cytokine

Rel

ativ

e pr

opor

tion

S

Faecalibacterium: −0.56

0 5 10 15 20 25

0.0

0.1

0.2

0.3

0.4

0.5

Mean cytokine

Rel

ativ

e pr

opor

tion

F

Clostridium: −0.506Ruminococcus: 0.531

Microbiome datasets can reveal associations… Answer may be different for different age birds:


IL-1B

Can we identify a microbial contribution to FCR?

HRFI LRFI

LRFI HRFI

?

Experiment 1


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C 8

482

Bact

eroi

des

vulg

atus

Bact

eroi

des

nord

iiBa

cter

oide

s eg

gerth

iiAn

aero

filum

agi

leVi

ctiva

llis v

aden

sis

Met

hylo

baci

llus

flage

llatu

sC

ollin

sella

ste

rcor

is D

SM 1

3279

Bact

eroi

des

egge

rthii

DSM

206

97An

aero

trunc

us c

olih

omin

is D

SM 1

7241

Sutte

rella

wad

swor

then

sis

LRFI

Taxa found only in HRFI flock

Taxa found only in LRFI flock


LRFI HRFI

LRFI HRFI

Experiment 2: Genetics vs. microflora

Reciprocal transplant of fecal material from adults to chicks:

Plus uninoculated controls...

Inoculum improves weight gain

050

010

0015

0020

00

week

body

wt (

g)

0 1 2 3 4 5 6

050

010

0015

0020

00

week

body

wt (

g)

0 1 2 3 4 5 6

inoculated Minoculated Funinoculated Muninoculated F

7.7%/135g

6.7%/103g

inoculated uninoculated

0200

400

600

RFI

!3022

Females

Inoculum improves FCR

!! Different cecal communities at 6 weeks


−1.0 −0.5 0.0 0.5 1.0

−3−2

−10

12

CA1

CA2

Low to Low

High to Low

Low to High

Low to High

High to High

High to High

High Male

High Male

High FemaleLow to High

High to High

Low to Low

High to Low

Low to Low

High to Low

High to Low

Low Male

Low Male

Low Female

High to Low

Low Male

Low to Low

High to Low

Low Female

High to Low

Low to Low

Low Female

Low Male

Low Female

Low Female

Low Male

Low Female

Low Female

Low Male

No inoculumDay-of-hatch inoculum

Two groups have significantly different microflora after 6 weeks:

!! Different cecal communities at 6 weeks pr

op o

f seq

s

0.00

0.10

0.20

0.30

inoculated

prop

of s

eqs

0.00

0.10

0.20

0.30 uninoculated

Strain Identification

Can FMT ‘lay the golden egg’?

14 d 1 d

5x

•! Community composition •! Metagenome •! Host Transcriptome •! Immune response (M1 vs. M2) •! AME •! Pathogen load •! Growth

FMT+

FMT-


14 d 1 d

5x

−2 −1 0 1

−10

12

CA1

CA2

1_NA_M34_D10

1_NA_M35_D11

1_NA_M36_D12

1_NA_M37_D1

1_NA_M38_D2

2_NA_M39_D3

2_NA_M41_D52_NA_M42_D6

2_NA_M43_D7

4_NA_M44_D8

4_NA_M45_D9

4_NA_M46_D10

4_NA_M47_D11

4_NA_M48_D12

5_NA_M49_D1

5_NA_M50_D2

5_NA_M51_D3

5_NA_M52_D4

5_NA_M53_D5

5_NA_M54_D65_NA_M55_D7

5_NA_M56_D8

NA_NA_M57_D9

5_NA_M58_D10

5_NA_M59_D11

5_NA_M60_D12

6_NA_M63_D3

6_NA_M64_D4

6_NA_M65_D5

6_NA_M66_D6

6_NA_M67_D7

6_NA_M68_D86_NA_M69_D9

3_NA_M70_D10

3_NA_M71_D11

3_NA_M72_D12

3_NA_M73_D13_NA_M74_D2

3_NA_M75_D3

5_NA_M76_D4

5_NA_M80_D8

1_NA_M34_D10

1_NA_M35_D11

1_NA_M36_D12

1_NA_M37_D1

1_NA_M38_D2

0 1

2_NA_M39_D3

2_NA_M41_D52_NA_M42_D62_NA_M42_D62_NA_M41_D52_NA_M42_D62_NA_M41_D5

2_NA_M43_D7

4_NA_M44_D8

4_NA_M45_D94_NA_M45_D9

4_NA_M46_D102_NA_M41_D5

4_NA_M46_D102_NA_M41_D5

4_NA_M47_D114_NA_M47_D11

4_NA_M48_D124_NA_M44_D8

4_NA_M48_D124_NA_M44_D8

5_NA_M49_D1

5_NA_M50_D22_NA_M43_D75_NA_M50_D22_NA_M43_D7

5_NA_M51_D35_NA_M51_D34_NA_M45_D95_NA_M51_D34_NA_M45_D9

5_NA_M52_D45_NA_M52_D4

5_NA_M53_D5

5_NA_M54_D65_NA_M55_D7

5_NA_M56_D8

NA_NA_M57_D9


5_NA_M59_D115_NA_M59_D11

5_NA_M60_D125_NA_M60_D125_NA_M60_D122_NA_M43_D75_NA_M60_D122_NA_M43_D75_NA_M50_D25_NA_M60_D125_NA_M50_D22_NA_M43_D75_NA_M50_D22_NA_M43_D75_NA_M60_D122_NA_M43_D75_NA_M50_D22_NA_M43_D7

6_NA_M63_D35_NA_M52_D4

6_NA_M63_D35_NA_M52_D4

6_NA_M64_D4

6_NA_M65_D5

6_NA_M66_D6

6_NA_M67_D7

6_NA_M68_D86_NA_M68_D85_NA_M59_D11

6_NA_M68_D85_NA_M59_D115_NA_M59_D11




6_NA_M68_D85_NA_M59_D11

3_NA_M70_D10

3_NA_M71_D113_NA_M71_D113_NA_M71_D115_NA_M55_D73_NA_M71_D115_NA_M55_D76_NA_M63_D33_NA_M71_D116_NA_M63_D3

3_NA_M72_D125_NA_M51_D33_NA_M72_D125_NA_M51_D34_NA_M45_D95_NA_M51_D34_NA_M45_D93_NA_M72_D12

4_NA_M45_D95_NA_M51_D34_NA_M45_D9


3_NA_M75_D3


5_NA_M80_D85_NA_M80_D83_NA_M70_D105_NA_M80_D83_NA_M70_D10

Initial inoculum


14 d 1 d

5x

M34_D

10−1

M35_D

11−1

M36_D

12−1

M37_D

1−1

M38_D

2−1

M39_D

3−2

M41_D

5−2

M42_D

6−2

M43_D

7−2

M70_D

10−3

M71_D

11−3

M72_D

12−3

M73_D

1−3

M74_D

2−3

M75_D

3−3

M44_D

8−4

M45_D

9−4

M46_D

10−4

M47_D

11−4

M48_D

12−4

M49_D

1−5

M50_D

2−5

M51_D

3−5

M52_D

4−5

M53_D

5−5

M54_D

6−5

M55_D

7−5

M56_D

8−5

M58_D

10−5

M59_D

11−5

M60_D

12−5

M76_D

4−5

M80_D

8−5

M63_D

3−6

M64_D

4−6

M65_D

5−6

M66_D

6−6

M67_D

7−6

M68_D

8−6

M69_D

9−6

M57_D

9−NA

Pro

p. of sequences

0.0

0.2

0.4

0.6

0.8

1.0

Lactobacillus

Ruminiclostridium

Blautia

Lachnospiraceae

Eubacterium

Dehalobacter

Bacteroides

Subdoligranulum

Olsenella

Anaerobacterium

Faecalicoccus

Erysipelatoclostridium

Gracilibacter

AcholeplasmaRuminococcus

Spiroplasma

Faecalibacterium

AlistipesPapillibacter

AnaerocolumnaParabacteroides

Intestinimonas

Barnesiella

Acetivibrio

AlkaliphilusPeptococcus

Microbacter

Sporobacter

Clostridium

Anaerostipes


14 d 1 d

5x

1 2 3 4 5 6

0.0

0.1

0.2

0.3

0.4

0.5

Bacteroides

0.000215809557482717


FMT+

FMT-

!!!

!!!

!!! !

!!

0

30

60

90

2 4 6day post challenge day post challenge

body

wei

ght (

g)

body

wei

ght (

g)Treatment!

!

!

Clean

Dirty

PBS

!!!

!!!

!

!! !

!

!

0

30

60

90

2 4 6

Treatment!

!

!

Clean

Dirty

PBS

A) No challenge B) Challenge

!

(15)

m20−4, 96.7

mg20−4, 99.6c2−6−12, 96.9m1−10−15, 97.6

m2−9, 99.2

m20−1, 99.6c20−1, 99.5

m20−5, 99.6

c1−3c, 99.8c10−3, 99.7c1−4a, 100

c10−4, 98.5c20−4, 98.8

c20−3−3, 96.3m20−2, 96.5

mg20−2, 92.9

mg10−1, 99.2

c1−9a, 99.1c20−2, 98.6

c1−8, 95.4m1−9, 95.5

Ab7Poly2, Anaerobacter polyendosporusCloInte3, Clostridium intestinale

CloAlg18, Clostridium algidicarnisCloPutr3, Clostridium putrefaciens

CloMesop, Clostridium mesophilum

CloCaven, Clostridium cavendishiiCloSart2, Clostridium sartagoforme

CloButy9, Clostridium butyricumCloSacc9, Clostridium saccharoperbutylacetonicum N1−4(HMT)CloPunic, Clostridium puniceumCloPerf4, Clostridium perfringens

CloSpo17, Clostridium sporogenes

CloHisto, Clostridium histolyticumCloProte, Clostridium proteolyticum

CloLimos, Clostridium limosum

CloDiff4, [Clostridium] difficileCloDiff3, [Clostridium] difficile

CloGlyc8, [Clostridium] glycolicumCloMayom, Clostridium mayombei

RumFaeci, Ruminococcus faecisRumTorq3, Ruminococcus torques ATCC 27756

BauHydro, Blautia hydrogenotrophica DSM 10507

CloAero2, Clostridium aerotolerans

CloXyla8, Clostridium xylanolyticum

FlfPlau3, Flavonifractor plautiiCisMinut, Christensenella minuta

Bacillus

0.10

CloIrre2, [Clostridium] irregulare

Microbiome datasets can guide targeted cultivation of potentially novel strains from chicken G-I tract:

Novel strains shown in red genome sequenced

Strain Identification

Outer ring = consensus of cut sites Fragment sizes and order reflect true arrangement in genome Provides true barcode of genome Provides template for assembly of genome sequence reads

Characterization of new isolates "! Genome Sequencing "! Optical Mapping

Strain characterization

Characterization of new isolates "! Genome Sequencing "! Optical Mapping

Strain characterization

Identifying Differentially Abundant COGs between Cluster N and Cluster W)

Image adapted from: doi: 10.1128/mBio.00889-14 22 April 2014 mBio vol. 5 no. 2 e00889-14

Butyrate Synthesis Pathways of new strains !"#$%!

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4-Aminobutyrate Pathway

Y9! ZAD! Y9! Y9! Y9! Y9! Y9! ZAD! Y9! Y9! Y9! Y9! Y9! ZAD! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9!

Acetyl-CoA Pathway

ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD!

Glutarate Pathway Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9!

Lysine Pathway Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9! Y9!

Common Ending Pathway

Y9! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! ZAD! Y9! ZAD! ZAD! ZAD! Y9! ZAD!

*Color Represents Presence or Absence of Pathway based on KEGG EC numbers found in Genome (allowing for 1 missing enzyme)

ZAD!!34565785!9:!3;<=>;?!Y9! !'@65785!9:!3;<=>;?!

A Majority of Uploaded Genomes can synthesize Butyrate from Acetyl-CoA according to their functional profile

CONCLUSIONS

#!Managing the microbiota can improve performance and food safety

#!Next-generation sequencing is a transformative tool

#!Proper management starts with understanding natural communities

#! ‘Efficacy-first’ inversion of traditional strain-centric approach may be valuable

Acknowledgements

USDA ARS Athens •! Bruce Seal •! Johnna Garrish •! Mark Berrang •! Nelson Cox •! Eric Line •! Jeff Buhr •! Seung-Chul Yoon •! Rick Meinersmann •! Cesar Morales •! Susan Brooks •! Jessica Johnson •! Raja Chalghoumi (Fulbright fellow)

CDC Atlanta •! Vladimir Loparev •! Rebecca Lindsey

UGA •! Sammy Aggrey •! Steve Collett •! Eldin Talundzic

SEPRL •! Laszlo Zak •! Michael Day

U.S. Poultry & Egg Association USDA 1433 Formula Funds USDA NIFA competitive grants

University of illinois •! Franck Carbonero •! Rex Gaskins

ARS College Station •! Mike Kogut

Western University •! Dr. Dominique Griffon •! Dr. Santiago Aguilar •! Ella Richardson •! Kim Calloway •! Jory Clark

Modern food safety: Western Health Sciences University ...€¦ · Western Health Sciences University College of Veterinary Medicine Pomona, CA ... Why is this important? !!Functional

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