r apid profiling of b eer spoilage m icro-organism s and...

Rapid Profiling of Beer Spoilage

Micro-organisms and Yeast Health

Dr Jon Meneses

Brewing & Supply Chain Manager

Coopers Brewery Limited

Asia Pacific Convention 2018 | Wellington, New Zealand

Non-Saccharomyces Brettanomyces spp.

Pichia spp.

Candida spp.

Rhodotorula spp.

Saccharomyces S. cerevisiae

S. diastaticus

S. bayanus

S. pastorianus

Gram Positive Lactobacillus spp.

Pediococcus spp.

Bacillus spp.

Micrococcus spp.

Gram Negative Acetobacter spp.

Zymomonas spp.

Pectinatus spp.

Megasphaera spp.

IMPACTS • Off Flavours

• Haziness

• Stuck Fermentation

• Over attenuation

• Damaged reputation

• Financial loss

Beer Spoilage Micro-organisms

0 500 1000 1500 2000 2500 3000

0

2000

4000

6000 Inte

ns.

[a.u

.]

320 330 340 350 360 370 380 390 400 410 420 m/z

Identification Of Micro-organisms

Selective Agar Plates

Real Time PCR MALDI-TOF MS

Light Microscope

0 500 1000 1500 2000 2500 3000

0

2000

4000

6000 Inte

ns.

[a.u

.]

320 330 340 350 360 370 380 390 400 410 420 m/z

ADVANTAGES • Characterise proteins,

lipids and other

organic macro

molecules.

• High throughput

• Cost effective Vs PCR

• Accurate and rapid ID

DIS-ADVANTAGES • Cost of instrument

• Requires pre-

enrichment

• Suited to pure

cultures

MALDI-TOF Mass Spectroscopy (Matrix Assisted Laser Desorption Ionisation Time Of Flight)

How MALDI-TOF Analysis Work (Video Show)


Prepare cell

culture

1

2x water wash

1x ethanol wash

3

Dried-droplet onto

MALDI target

5

Biotyper acquisition 1 biological replicate,

8 technical replicates

Acquire 3X (24 Spectra)

6

Extract with 70%

formic acid

4

Harvest 150,000

cells

2

7

Automated identification Review and Validation

(5,643 MSP in library)

Agar plate

Protein Extraction and MALDI-TOF Analysis


Mass Spectra Profile (MSP) Creation For Database

STRAIN

Dekkera/Brettanomyces bruxellensis


Weihenstephan Weizen

Kölsch

Munich Lager

Czech Pils

Lactobacillus brevis

Lactobacillus lindneri

Pediococcus damnosus

Megasphaera cerevisiae

Pectinatus frisingensis

Wild yeast isolate from Coopers Brewery Ltd.

Top-fermenting brewing yeasts,

commercially sourced

Bottom-fermenting brewing yeasts,


Wild yeast isolate, commercially sourced

Facultative anaerobic bacteria,


Obligate anaerobic bacteria,


(20 biological replicates of each strain to generate reference spectrum)

MALDI-TOF Mass Spectra Profile Of Samples

Identification From Spiked Beer Samples

Prepare cell

culture

1

2x water wash

1x ethanol wash

3

Dried-droplet onto

MALDI target

5




6

Extract with 70%

formic acid

4

Harvest 150,000

cells

2

7

Automated identification (5,643 MSP + 16 Generated MSP)

Agar plate

Bacteria or Yeast


Strain MSP Score Against Database (5,643) & Internal Database (16)

Range Interpretation Colour

2.00 - 3.00 High Confidence Identification

Genus and species Green

1.70 - 1.99 Low Confidence Identification

Species Yellow

< 1.70 No Organism Identification Possible Red

STRAIN


Weihenstephan Weizen

Kölsch

Munich Lager

Czech Pils


Lactobacillus lindneri

Pediococcus damnosus

Megasphaera cerevisiae

Pectinatus frisingensis

SCORE

2.195 / 2.179 / 2.190 / 2.120

2.080 / 2.243 / 2.132 / 2.120

2.463 / 2.386 / 2.492 / 2.471

2.369 / 2.422 / 2.377 / Czech Pils (N = 1)

detected as Munich Lager (N = 4)

2.318 / 2.096 / 2.359 / 2.044

2.400 / 2.252 / 2.209 / 2.298

2.248 / 2.309 / 2.332 / 2.273

2.377 / 2.439 / 2.484 / 2.512

2.573 / 2.589 / 2.525 / 2.450

Accuracy

4/4

4/4

4/4

3/4

0/4

4/4

4/4

4/4

4/4

4/4

Brewery Vs Commercial Dekkera/Brettanomyces Wild Yeast MSP


Identification of Brewery Isolates

Analysed 29 agar-plates from routine

microbiological plating of samples from

brewery and malt extract plant.

50 distinctive colonies were selected and

analysed by MS profiling.

Five colonies produced distinctive spectra, but

could not be identified (score below threshold)

Analysis was rapid taking only 1/2 day to

complete.

90% (45 colonies) could be identified using

Biotyper of which 25 microorganisms were

unique.


Identification Of Unknown Contaminants By LC-MS/MS Sample

Plate 4

Plate 5

Plate 11

Plate 12

Plate 13

Colony Morphology

Small green colonies

Green viscous growth




Microorganism

Identified as Acidomonas methanolica

Several microorganisms identified




Plate 5 – green viscous growth Plate 11 – green viscous growth

Plate 12 – green viscous growth Plate 13 – green viscous growth

Isolates

Lager brewing yeast

Brettanomyces bruxellensis

Burkholderia cepacia

Burkholderia vietnamiensis

Candida guilliermondii

Candida inconspicua

Candida krusei

Candida pelliculosa

Enterococcus gilvus

Exophiala dermatitidus


Lactobacillus paracasei

Lactococcus lactis

Pandoraea apista

Pichia manshurica

Staphylococcus capitis

Staphylococcus hominis

Isolate Impact

Bottom-fermenting brewing yeast Lager yeast

Burkholderia cepacia BCC organisms are typically found in water and soil, human pathogen, affects lungs

Burkholderia vietnamiensis BCC organisms are typically found in water and soil, human pathogen, affects lungs

Candida guilliermondii Oppotunistic fungal pathogen

Candida inconspicua Oppotunistic fungal pathogen

Candida krusei Oppotunistic fungal pathogen

Candida pelliculosa Oppotunistic fungal pathogen

Dekkera/Brettanomyces bruxellensis Wild yeast

Enterococcus gilvus Large genus of Lactic acid bacteria

Exophiala dermatitidus Respiratory pathogen

Lactobacillus brevis Lactic acid producers

Lactobacillus paracasei Lactic acid producers

Lactococcus lactis Lactic acid producers

Pandoraea apista Respiratory pathogen

Pichia manshurica Produce volatile phenols

Rhodotorula mucilaginosa Oppotunistic fungal pathogen

Staphylococcus capitis Associated with endocarditis

Staphylococcus hominis Produce thioalcohol (rotten eggs)


Part II Profiling of Yeast Health


Monitoring Yeast Health (Project Aims)

To determine if the yeast proteome during

fermentation and re-pitching produces

different mass spectrum profiles (MSP).

To identify the proteins that change and how

they relate to off-flavours.

To assess how these changes affect the

overall flavour profile of the product, in

conjunction with metabolite profiling.

To establish a database that allows monitoring

of these changes.

To determine the applicability of the database

by analysing samples from the brewery


Prepare cell

culture

1

2x water wash

1x ethanol wash

3

Dried-droplet onto

MALDI target

5




6

Extract with 70%

formic acid

4

Harvest 150,000

cells

2

7


Agar plate

Protein Extraction and MALDI-TOF Analysis

Issues for High-Throughput sampling and obtaining

consistent profiles:

Extraction

Not enough protein Too few cells

Formic acid extraction not consistent

good for bacterial cells but poor for yeast cells


Protein Extraction Optimisation

Coomassie stain (µg) Silver stain (ng)

FA: Formic Acid

TCA: Trichloro Acetic Acid

SDS: Sodium Dodecyl Sulfate

Biorupter®: Sonicator of cells


TCA/Biorupter®

&

Acetone precipitation

Prepare cell

culture

1

Dried-droplet onto

MALDI target

5




6

Harvest 150,000

cells

2

7


Agar plate

Alternative Extraction Protocols (Trichloroacetic acid (TCA)/ acetone precipitation)

20% TCA

Biorupter

3

Acetone

precipitation

4

?


Optimisation Of Cell Number For Database MSP Generation

Pair-wise correlations

Spotted 8 technical replicates for each yeast cell concentration

Acquired 3 x spectra per replicate ( 24 spectrum)

This was repeated 5X

3,000,000 cells

88% spectral resolution

1,000,000 cells


Correlation above 0.90 Correlation above 0.95

2,000,000 cells



(Value of 1 means complete agreement, Value of -1 means complete dis-agreement)

Prepare cell

culture

1

Dried-droplet onto

MALDI target

5




6

Harvest 2,000,000

cells

2

7


Agar plate

Optimised Extraction Protocol (Trichloroacetic acid (TCA)/ acetone precipitation) & 2,000,000 yeast cells

20% TCA

Biorupter

3

Acetone

precipitation

4


Validation Of Changes To Yeast Proteins Exposed To Stress

Normal (Yeast-peptone D-

glucose media)

Nutrient deprivation (Yeast-

peptone media)

Oxidative stress (1% (v/v) and

2mM hydrogen peroxide)

Osmotic stress (15% (w/v)

mannitol)

Ethanol stress (10% (v/v)

ethanol)

Cold (4C)


Profile Changes After Cold and Ethanol Stress

Cold

(4C)

Ethanol

(10%)


Profile Changes After Oxidative Stress

1% H202

2mM

H202


Profile Changes After Osmotic and Nutrient Deprivation

Osmotic

(15% Mannitol)

Nutrient

deprivation


Preliminary Data of Lager Fermentation & Yeast Storage MSP Profile

Day 1:

Fermentation

Day 2:

Fermentation

Day 8:

Fermentation

Day 5:

Yeast Storage

Day 1:

Yeast Storage

0 500 1000 1500 2000 2500 3000

0

2000

4000

6000 Inte

ns.

[a.u

.]

320 330 340 350 360 370 380 390 400 410 420 m/z

Conclusions

Eliminate pre-enrichment by

direct testing of beer

Optimised accuracy of detection

in mixed cultures utilising

Microfluidics

Identifying the proteins that

change when exposed to

different stresses

Suitable for the identification of

beer spoilage microorganisms

Accurate and rapid

Can detect protein changes

in yeast under stress

Future Research


Acknowledgements

Professor Peter Hoffmann Dr Florian Weiland Dr Mark Condina Dr Michelle Turvey

Brooke Dilmetz Erica Keller


r apid profiling of b eer spoilage m icro-organism s and...

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