Lab 4:

Most Probable Number Method (MPN)

Most Probable Number Method (MPN)

• What is the MPN method?• How to determine the amount

of bacteria from the MPN method?

Objective

Most Probable Number Method (MPN)

The most probable number (MPN) method is familiar to quality control (QC) microbiologists as part of the microbial limits tests.

• Its usefulness goes far beyond this one test, however. • The theory behind the MPN method is central to the commonly

used D-value determination by fraction-negative method, and a variant of this method has been suggested for trending of environmental monitoring data from the aseptic core.

• MPN can be adjusted to provide a sensitive method to determine differences between two qualitative microbiological methods. As such, it can be used as a tool in validation of rapid microbiological methods and for growth promotion testing of broth media.

Most Probable Number Method (MPN)

The most probable number (MPN) is particularly useful for low concentrations of organisms (<100/g), especially in milk and water, and for those foods whose particulate matter may interfere with accurate colony counts.

Only viable organisms are enumerated by the MPN determination.

If, in the microbiologist's experience, the bacteria in the prepared sample in question can be found attached in chains that are not separated by the preparation and dilution, the MPN should be judged as an estimate of growth units (GUs) or colony-forming units (CFUs) instead of individual bacteria.

Most Probable Number Method (MPN)

For simplicity, however, here we will speak of these GUs or CFUs as individual bacteria.

The following assumptions are necessary to support the MPN method.

The sample is prepared in such a way that the bacteria are distributed randomly within it.

The bacteria are separate, not clustered together, and they do not repel each other.

The growth medium and conditions of incubation have been chosen so that every inoculum that contains even one viable

organism will produce detectable growth. The essence of the MPN method is the dilution of a sample to

such a degree that inoculate will sometimes but not always contain viable organisms.

The "outcome", i.e., the numbers of inoculate producing growth at each dilution, will imply an estimate of the

original, undiluted concentration of bacteria in the sample.

In order to obtain estimates over a broad range of possible concentrations, microbiologists use serial dilutions, incubating several tubes (or plates, etc.) at each dilution.

Confidence Intervals

The 95 percent confidence intervals in the tables have the following meaning.

Before the tubes are inoculated, the chance is at least 95 percent that the confidence interval associated with the eventual result will enclose the actual concentration.

Selecting Three Dilutions for Table Reference

An MPN can be computed for any numbers of tubes at any numbers of dilutions.

MPN values based on 3 decimal dilutions, however, are very close approximations to those based on 4 or more dilutions.

When more than three dilutions are used in a decimal series of dilutions, refer to the 3 dilution table according to the following two cases, illustrated by the table of examples below (with 5 tubes at each dilution).

Inconclusive Tubes

In special cases where tubes or plates cannot be judged either positive or negative (e.g., plates overgrown by competing microflora at low dilutions), these tubes or plates should be excluded from the results.

The entire dilutions at or below those in which exclusion occurs may be excluded.

If it is not desired to exclude the remaining tubes at or below the dilution of the excluded tubes, the results will now have an unequal number of tubes at several dilutions.

Table 1MPN/g Combination

of Positives0.0001 g 0.001 g 0.01 g 0.1 g 1.0 g Example

33 5-1-0 0 0 1 5 5 a

33 5-1-0 0 0 1 5 4 b

40 4-4-1 0 1 4 4 5 c

40 4-4-1 1 0 4 4 5 d

5400 5-5-2 2 5 5 5 5 e

0.20 0-0-1 0 0 1 0 0 f

4.7 4-2-2 0 1 1 4 4 g

Example: The following inoculated tubes give a positive reading:1. 5 tubes with 10 ml of 1:10 dilution of test material - all 5 are positive2. 5 tubes with 1 ml of 1:10 dilution of test material - 1 is positive3. 5 tubes with 1 ml of 1:100 dilution of test material – none are positive

The quantities in each of the five tubes of the three dilution series represent 1, 0.1 and 0.01 g (ml), respectively of the test material.

According to Table I, a reading of 5-1-0 gives a value of 33 when10, 1 and 0.1 g (ml) respectively are used. However, since only 1/10 of these amounts were actually used in the analysis, the value of 33 obtained from Table II must be multiplied by 10 giving 33 x 10 = 330 organisms per 100 g (ml) of test material

If the results need to be expressed per g (ml), the MPN value is 330 ÷ 100 = 3.3. When higher dilutions are used, the same procedure is followed, but the multiplier (dilution factor) is enlarged to relate the amount of test material actually present to the values given for 10, 1.0 and 0.1 g (ml) in Table I.

MPN/100 ml=No .microorganisms x dilution factor of middle set of tubes (Table I)

Most Probable Number

Advantages Disadvantages Relatively simple and sensitive Can count a specific type in the presence of others Can use large sample volumes

Time consuming and labor intensive Requires large volumes of glassware Doesn’t give the “real” value Doesn’t give isolated colonies

The basic concept for the MPN method is to dilute the sample to such a degree that inocula in the tubes will sometimes (but not always) contain viable organisms.

By replicates, and dilution series, this will result in a fairly accurate estimate of the most probable number of cells in the sample.

While this method is most commonly used in the personal products, medical device, and pharmaceutical QC microbiology labs for water testing or the compendial bioburden test, it has significant potential for other applications.

These possible applications of MPN include D-value determination, environmental monitoring, media growth promotion studies, and aspects of the validation of rapid microbiological methods.

SUMMARY

END OF LECTURE