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1 Most probable number (MPN) Total Cell Counts Thoma-chamber Membrane filter Automatic counting Quantitative PCR Most probable number (MPN)

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1

Most probable number (MPN)

Total Cell Counts

Thoma-chamber

Membrane filter

Automatic counting

Quantitative PCR

Most probable number (MPN)

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Most probable number (MPN)

• Serial dilution of an inoculum in a liquid medium until the final tube or tubes

in the series show no growth

• The last tube showing growth should have developed from 10 or fewer cells

• Use of several replicate

tubes at each dilution

improves accuracy of the

final MPN obtained

Slurry(Sedimentaufschlämmung)

18 mL artificial seawater

+ 2 cm3 sediment

(1:10)

Microtiterplate with 96 wells

(0.9 mL medium + 0.1 mL slurry)

���� Variations in samples, medium,

substrates, etc.

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• Calculation of MPN

• Numerical code � last 3 dilution steps showing growth

• Statistical methods � ‘ most probable number ‘ (MPN Tables)

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10-110-610-610-1

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MPN indexcells/ml

Confidence interval (95%)

Borderslower upper100µl 10µl 1µl

MPN Table

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• Last 3 positive steps:

321

• MPN (de Man):

150

� 150 cells in the dilution 10-2 that contains 10 µL slurry

� 1 mL slurry: 15,000 cells

� dilution factor (medium/sediment) = 10

� cells per cm3 sediment: 150,000

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10-110-610-610-1

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A 221 ���� 28 cells in 10 -3 (1µL slurry)���� 28,000 cells/mL slurry���� 280,000 cells/mL sediment

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B 110 ���� 7 cells in 10 -1 (100µL slurry)���� 70 cells/mL slurry���� 700 cells/mL sediment

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Kontrolle

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10-110-610-610-1

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C 331 ���� 460 cells in 10 -1 (100µL slurry)���� 4,600 cells/mL slurry���� 46,000 cells/mL sediment

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D 111 ���� 11 cells in 10 -2 (10µL slurry)���� 11,00 cells/mL slurry���� 11,000 cells/mL sediment

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Total Cell Counts

Thoma-chamber

Membrane filter

Automatic counting

Image acquisition

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Image acquisition

Total Cell Counts

Thoma-chamber

a-Field

b-Fieldc-Field

Known areas, depth of chamber, volumes

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b-Field

Thoma-chamber

Counting

+ on the upper and right-hand border line of a small square

- on the lower and left-hand border line of a small square

b-Field

Thoma-chamber

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Calculation of cell counts

Cell counts/mL = Total number of all counted cells

Number of small squares counted

Volume of a small square in mLx

Volume of a small square in mL = (Length) 2 x Depth of chamber

Thoma-chamber

Membrane filter

effective Filtration-area

Counting square

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Membrane filter

Cell counts/mL =

Total number of counted cells

effective Filtration area in mm2

Number of counted squares

Filtered volumein mL

x

xx Area of one squarein mm 2

Calculation of cell counts

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www.picolay.de

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Deconvolution and stacking

Stacking : Selection of best areas (sharpness or colour)

Deconvolution : reconstructionbased on information of all layers

Tick,40x12/19 images

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1/5 5/5

Stacked

CountThem

The most-boring job...

www.picolay.de

Quantitative PCR

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SybrGreen technique

Amplification

5´ 3´

5´3´

⇒⇒⇒⇒ weak fluorescence

No binding on single stranded DNA

UV (497 nm)

5´ 3´

5´3´

ss DNA

⇒⇒⇒⇒ strongfluorescence

SybrGreen intercalates at double stranded DNA

UV 520 nm

ds DNA

SybrGreen technique

Advantage:• easy to establish

• less expensive than other methods

• especially usefull if different primer sets are applied

Drawback:• unspeciffic binding possible

General:• DNA extraction crucial• specificity of primers

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Other methods

• Taq man probes• Molecular beacons

Advantages:• High specific binding with a second probe

Annealing ofTaq man probes and primers

Amplification

Release of fluorophor

Molecular beacon: Hairpin structure, fluorophor and quencher closely connected

Opening of hairpin duringannealing results in fluorescence

Rotor-Gene 2000/3000 Corbett Research Raw data

Rotor and detection units

The thermocycler

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TheThreshold:• Level with highest rate

of amplification

The Ct-value:• The number of cycles to reach

the treshold is directly correlated to the copy number in the original sample

Standard curve:• Calculation of target concentration• Calculation of organisms per sample

(x 16S rRNA copy number)

3.8 for Bacteria, 2 for Archaea(Fogel et al. 1999)

Data aquisition and analysis