AirborneAirborne bacteriabacteria::

namesnames and and numbersnumbers,,

pleaseplease……Runar Runar ThyrhaugThyrhaugDep. Dep. ofof BiologyBiologyUniversityUniversity ofof Bergen BergenNorwayNorway

runar.thyrhaug@bio.uib.norunar.thyrhaug@bio.uib.no

My My backgroundbackground

MicrobialMicrobial ecologyecology Marine Marine microbiologymicrobiology group-group- Bergen, Bergen, NorwayNorway FocusFocus: : algaealgae, , bacteriabacteria, , protozooaprotozooa, virus, virus

My My backgroundbackground

MicrobialMicrobial ecologyecology Marine Marine microbiologymicrobiology group-group- Bergen, Bergen, NorwayNorway FocusFocus: : algaealgae, , bacteriabacteria, , protozooaprotozooa, virus, virus MethodsMethods

NutrientNutrient uptakeuptake/turnover/turnover ProductionProduction rates rates GeneticGenetic diversitydiversity//biodiversitybiodiversity ViralViral activityactivity ModellingModelling ( (vsvs experimentsexperiments))

WhyWhy airborneairborne bacteriabacteria??

CuriosityCuriosity……newnew fieldfield BiodiversityBiodiversity and transport rates and transport rates MicrobialMicrobial productionproduction ImprovedImproved//newnew methodsmethods……possibilitiespossibilities??

BacteriaBacteria in in thethe air air

……from from wherewhere??BacteriaBacteria VirusVirus

SoilSoil ( (terrestrialterrestrial)) ~10~1099 g g-1-1 ????

SeaSea / /freshfresh water water ~10~1066 mL mL-1-1 ~10~1077 mL mL-1-1

BacteriaBacteria in in thethe air air

……from from wherewhere??BacteriaBacteria VirusVirus

SoilSoil ( (terrestrialterrestrial)) ~10~1099 g g-1-1 ????

SeaSea / /freshfresh water water ~10~1066 mL mL-1-1 ~10~1077 mL mL-1-1

WeWe know: know: Most marine Most marine bacteriabacteria areare assumedassumed to be to be alivealive NutrientNutrient limited N , P or C limited N , P or C <1% <1% growinggrowing onon agar plates ( agar plates (seasea water and water and soilsoil samples!) samples!)

CountingCounting airborneairborne

bacteriabacteria LiquidLiquid samples! samples!

RainRain or air or air sampledsampled in in liquidsliquids MethodsMethods::

FlowFlow cytometrycytometry (FCM) (FCM) DNA/RNA DNA/RNA stainingstaining - fluor / - fluor /scatterscatter signals from single signals from single particlesparticles

QuantitativeQuantitative PCR (Q-PCR) PCR (Q-PCR) DNA DNA stainingstaining –– amountamount ofof bacterialbacterial DNA in a bulk sample DNA in a bulk sample

ColonyColony forming forming unitsunits (CFU) (CFU) BacteriaBacteria willingwilling to to growgrow onon agar plates agar plates

EpifluorescenseEpifluorescense microscopymicroscopy (EFM) (EFM) DNA/RNA DNA/RNA stainingstaining - fluor signals from single - fluor signals from single particlesparticles

FCM plot / EFM FCM plot / EFM picturepicture

seasea water water examplesexamples::

FCM plot / EFM FCM plot / EFM picturepicture

seasea water water examplesexamples::

Marine bacteria

FCM plot / EFM FCM plot / EFM picturepicture

seasea water water examplesexamples::

Marine viruses

Marine bacteria

FCM plot / EFM FCM plot / EFM picturepicture

seasea water water examplesexamples::

Marine viruses

Marine bacteria

Emiliania huxleyi virusisolate (EhV)

EhV

Sampling Sampling airborneairborne

bacteriabacteria

Xmx-cvXmx-cv ( (DycorDycor)) 0,7 m0,7 m33 min min-1-1

5 5 mLmL PBS PBS Suggested Suggested maxmaxsampling time: 5 minsampling time: 5 min OurOur maxmax: 10 min: 10 min

FlowFlow cytometrycytometry o fo f air air

samplessamplesT0=BlankT0=Blank

Fluo

res c

e nce

Scatter signal

FlowFlow cytometrycytometry o fo f air air

samplessamplesT0=BlankT0=Blank

T5~3,5m3 in 5 T5~3,5m3 in 5 mLmL

Fluo

res c

e nce

Scatter signal

Fluo

resc

ence

Scatter signal

FlowFlow cytometrycytometry o fo f air air

samplessamplesT0=BlankT0=Blank

T5~3,5m3 in 5 T5~3,5m3 in 5 mLmL

~103 pr m3

Fluo

res c

e nce

Scatter signal

Fluo

resc

ence

Scatter signal

FlowFlow cytometrycytometry vsvs Q- Q-

PCRPCR Q-PCR:FCM ~10Q-PCR:FCM ~10 CalibrationCalibration goinggoing onon!!

Q-PCR (Log bact pr m3)

0 2 4 6 8

FCM

(Log bact pr m3 )

0

2

4

6

8 Air: Air: yellowyellow RainRain: red: red SeaSea water:bluewater:blue

FlowFlow cytometrycytometry vsvs Q- Q-

PCRPCR Q-PCR:FCM ~10Q-PCR:FCM ~10 CalibrationCalibration goinggoing onon!!

Q-PCR (Log bact pr m3)

0 2 4 6 8

FCM

(Log bact pr m3 )

0

2

4

6

8

CFU: CFU: aroundaround 1-2% 1-2%comparedcompared to FCM to FCM

EpifluorescenceEpifluorescence microscopymicroscopy::difficultdifficult to to discriminatediscriminatesignal/signal/noisenoise

Air: Air: yellowyellow RainRain: red: red SeaSea water:bluewater:blue

SnowSnow and and rainrain samples samples

snowsnow ~500-10 ~500-1044 pr pr mLmL RainRain ~10 ~1044 pr pr mLmL

SnowSnow and and rainrain samples samples

snowsnow ~500-10 ~500-1044 pr pr mLmL RainRain ~10 ~1044 pr pr mLmL

Bacterial production:

Addition of H3 leucine, 24 h incubation

SnowSnow and and rainrain samples samples

snowsnow ~500-10 ~500-1044 pr pr mLmL RainRain ~10 ~1044 pr pr mLmL

Bacterial production:

Addition of H3 leucine, 24 h incubation

Result: activity pr bacteria ~ as in sea water

Estimated generation time~ 1day

ComparisonComparison o fo f 3 3

bioaerosolbioaerosol samplers samplers Time seriesTime series FCM and CFU FCM and CFU countscounts LiquidLiquid loss rates loss rates

Sampler 1Sampler 1

Xmx-cvXmx-cv ( (DycorDycor)) 0,7 m0,7 m33 min min-1-1

5 5 mLmL Suggested Suggested maxmaxsampling time: 5 minsampling time: 5 min OurOur sampling time 0-10 min sampling time 0-10 min LiquidLiquid: PBS: PBS ~10% PBS loss ~10% PBS loss afterafter 10 min 10 min

Sampler 2Sampler 2

SKC 225-9595 (SKC)SKC 225-9595 (SKC) 0,0125 m0,0125 m33 min min-1-1

Sampling time 0-60 minSampling time 0-60 min LiquidLiquid: : MilliQMilliQ Refill~25% Refill~25% milliQmilliQ at 10 min at 10 min

Sampler 3Sampler 3

KKäärcherrcher DS 5550 DS 5550

Sampler 3Sampler 3

KKäärcherrcher DS 5550 DS 5550 3,3 m3,3 m33 min min-1-1

1500 1500 mLmL Max sampling time: 120 minMax sampling time: 120 min LiquidLiquid: PBS: PBS ~10% ~10% pbspbs loss loss afterafter 120 min 120 min

Black: direct counts FCM ”bacteria pr mL”

Grey: estimated bacterial concentration pr m3 air

White: estimated bacterial conc pr m3 air after substracting blank (T0 sample)

FCM FCM countscounts - time series - time series

Bacterial concentration (m

L-1)

0

200

400

600

800

1000

Sampling time (min)0 20 40 60 80 100 120 140

Estimated bact conc (m

-3)

0

1000

2000

3000

4000

200004000060000

no correctionT0 substracted

Karcher - FCM

Bacterial concentration (m

L-1)

0

500

1000

1500

2000

2500

3000

Sampling time (min)0 2 4 6 8 10

Estimated bact conc (m

-3)

0

1000

2000

400060008000

no correctionT0 substracted

XMX - FCM

Bacterial concentration (m

L-1

)

0

100

200

300

400

500

600

Sampling time (min)0 20 40 60 80

Estimated bact conc (m

-3)

0

2000

4000

6000

8000

10000

1200020000

40000no correctionT0 substracted

SKC - FCM

CFU CFU countscounts - time - time

seriesseries

Bacterial concentration (m

L-1

)

0

10

20

30

40

50

Sampling time (min)0 20 40 60 80

Bact concentration (m

-3)

020406080

100120140160180200

1000

2000

3000no correctionT0 substracted

SKC - CFU

Bacterial concentration (m

L-1

)

0

10

20

30

40

50

Sampling time (min)0 2 4 6 8 10

Bact concentration (m

-3)

0

20

40

60

80

no correctionT0 substracted

XMX - CFU

Bacterial concentration (m

L-1

)

0

5

10

15

20

25

30

35

Sampling time (min)0 20 40 60 80 100 120 140

Bact concentration (m

-3)

020406080

100120140160180200

no correctionT0 substracted

Karcher - CFU

Black: direct counts CFM ”bacteria pr mL”

Grey: estimated bacterial concentration pr m3 air

White: estimated bacterial conc pr m3 air after substracting blank (T0 sample)

CFU as % o f FCM

240±142.0220Mas-100

1371.8260slit sampler

1.60.84200±22008800±2200467±770.038160SKC

2.41.31400±6902500±690433±350.261120Karcher

1.11.01600±3301800±330418±131.4110XMX-CV

FCMdata T0subst.

FCM raw dataFCM±std.dev4

T0 substr

FCM±std.dev4

raw datanCFU±err3volume

(m3)time(min)

CFU as % of FCMFCM m3CFU pr m3sampling data

Sampler

Table xx. cfu and fcm bacterial counts in samples with the highest theoretical concentration factor in this experiment.1. estimated air volume sampled pr ml sampling liquid.2. Air volume sampled.3. std dev except slitsamplers, 4. std dev of 3 dilutions

CFU as % o f FCM

240±142.0220Mas-100

1371.8260slit sampler

1.60.84200±22008800±2200467±770.038160SKC

2.41.31400±6902500±690433±350.261120Karcher

1.11.01600±3301800±330418±131.4110XMX-CV

FCMdata T0subst.

FCM raw dataFCM±std.dev4

T0 substr

FCM±std.dev4

raw datanCFU±err3volume

(m3)time(min)

CFU as % of FCMFCM m3CFU pr m3sampling data

Sampler

Table xx. cfu and fcm bacterial counts in samples with the highest theoretical concentration factor in this experiment.1. estimated air volume sampled pr ml sampling liquid.2. Air volume sampled.3. std dev except slitsamplers, 4. std dev of 3 dilutions

CFU as % o f FCM

240±142.0220Mas-100

1371.8260slit sampler

1.60.84200±22008800±2200467±770.038160SKC

2.41.31400±6902500±690433±350.261120Karcher

1.11.01600±3301800±330418±131.4110XMX-CV

FCMdata T0subst.

FCM raw dataFCM±std.dev4

T0 substr

FCM±std.dev4

raw datanCFU±err3volume

(m3)time(min)

CFU as % of FCMFCM m3CFU pr m3sampling data

Sampler

Table xx. cfu and fcm bacterial counts in samples with the highest theoretical concentration factor in this experiment.1. estimated air volume sampled pr ml sampling liquid.2. Air volume sampled.3. std dev except slitsamplers, 4. std dev of 3 dilutions

TheThe dicedice is is thrownthrown……

Evaluation

Background noise

Liquid volume

Sampling volume

Sampling time

Sampling efficience – concentration factors

Reliability

TheThe dicedice is is thrownthrown……

XMX-CV

+ Robust

+ Low backgroud

+ Fast sampling

- Low liquid volume

TheThe dicedice is is thrownthrown……

XMX-CV

+ Robust

+ Low backgroud

+ Fast sampling

- Low liquid volume

+ ok background

-Very low efficiency

-Highest liquid lossrate

SKC

TheThe dicedice is is thrownthrown……

XMX-CV

+ Robust

+ Low backgroud

+ Fast sampling

- Low liquid volume

+ ok background

-Very low efficiency

-Highest liquid lossrate

SKC KKäärcherrcher

+ High volume rates

+ High volumes

- High volumes

- Highest backgroud

In In thethe end end

BacteriaBacteria in air pr m in air pr m33:: CFUCFU 10-5010-50 FCMFCM ~10~1033

In In thethe end end

BacteriaBacteria in air pr m in air pr m33:: CFUCFU 10-5010-50 FCMFCM ~10~1033

BacteriaBacteria in in snowsnow//rainrain pr pr mLmL:: CFUCFU 10-20010-200 FCMFCM ~10~1044

BacterialBacterial activityactivity in in snowsnow//rainrain ~ SW ~ SW bacteriabacteria

In In thethe end end

BacteriaBacteria in air pr m in air pr m33:: CFUCFU 10-5010-50 FCMFCM ~10~1033

BacteriaBacteria in in snowsnow//rainrain pr pr mLmL:: CFUCFU 10-20010-200 FCMFCM ~10~1044

BacterialBacterial activityactivity in in snowsnow//rainrain ~ SW ~ SW bacteriabacteria

Sampler test:Sampler test:1.1. XMX-CVXMX-CV2.2. KKäärcherrcher3.3. SKCSKC

In In thethe end end

BacteriaBacteria in air pr m in air pr m33:: CFUCFU 10-5010-50 FCMFCM ~10~1033

BacteriaBacteria in in snowsnow//rainrain pr pr mLmL:: CFUCFU 10-20010-200 FCMFCM ~10~1044

BacterialBacterial activityactivity in in snowsnow//rainrain ~ SW ~ SW bacteriabacteria

Sampler test:Sampler test:1.1. XMX-CVXMX-CV2.2. KKäärcherrcher3.3. SKCSKC

UniversityUniversity ofof Bergen, Dep Bergen, Dep BiologyBiology JJøørn rn EinenEinen Ruth-Anne Ruth-Anne SandaaSandaa Gunnar Gunnar BratbakBratbak Mikal HeldalMikal Heldal

NorwegianNorwegian DefenceDefence ResearchResearch Establishment Establishment JanetJanet Martha Martha BlatnyBlatny Gunnar SkoganGunnar Skogan Else-Marie Else-Marie FykseFykse Tone Tone AarskaugAarskaug

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