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Journal of Clinical Microbiology, November 2001, p. 4190-4192, Vol. 39, No. 11
0095-1137/01/$04.00+0 DOI: 10.1128/JCM.39.11.4190-4192.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
Determining Confidence Intervals When Measuring Genetic Diversity
and the Discriminatory Abilities of Typing Methods for
Microorganisms
Hajo
Grundmann,1,*
Satoshi
Hori,1 and
Gregor
Tanner2
Division of Microbiology and Infectious
Diseases, University Hospital Nottingham,1 and
School of Mathematical Sciences,2
University of Nottingham, Nottingham NG7 2UH, United Kingdom
Received 21 June 2001/Returned for modification 24 July
2001/Accepted 21 August 2001
 |
ABSTRACT |
We describe here a method for determining confidence intervals for
a commonly used index of diversity. This approach facilitates the
comparison of the genetic population structure of microorganisms isolated from different environments and improves the objective assessment of the discriminatory power of typing techniques.
 |
TEXT |
The discrimination of organisms on
the basis of variable phenotypic or genetic markers is still the
mainstay of quantitative microbial ecology and descriptive
epidemiology. To determine the diversity of microorganisms in defined
environments (ecosystems) or to identify the reproductive success of
disease causing organisms, i.e., the spread of particular strains
between hosts, genetic typing techniques are deployed which have the
ability to distinguish diverse organisms of the same species.
Importantly, when one is comparing the diversity of a single species
between different ecosystems or comparing the various typing methods
used to resolve such differences, a robust statistical approach is
required that allows an objective assessment. To this end, indices of
diversity have been defined mathematically that are based on the
frequency with which organisms of a particular type occur in a
population or can be discriminated by a given typing tool (3, 4,
5). Individuals of a population will belong to one of
Z types and will occur with frequencies of
1 ...
Z such that

= 1. For microorganisms that usually have a very large
population size, the genetic diversity (
) can be described as
= 1 - 
2, which will be the
probability that two individuals chosen at random will be of a
different type.
Inferences on the diversity of the population involve a sampling
process. The index of diversity D, as defined by Simpson (5) and lately utilized for the assessment of the
discriminatory power of typing techniques (2, 6), is an
unbiased estimate of the true diversity
of a population based on a
sample of n individuals. Simply by chance, different samples
will give different results, the difference being due to sample
variation and by drawing repeated samples, the precision of the mean
estimate for D will improve. If repeated samples of a fixed
size n are drawn from the sample population, the values of
D will be distributed about
with the variance
2 (5):
|
(1)
|
where
j is the frequency
nj/n,
nj is the number of strains belonging to
the jth type, and n is the total number of
strains in the sample population. An estimate of the standard deviation
of
is given by the square root of
2, and
we propose the following as approximate 95% confidence interval (CI):
|
(2)
|
We have applied these equations to determine confidence intervals
(i) when assessing the genetic diversity of Staphylococcus aureus isolated from healthy carriers in the community as opposed to hospitalised patients and (ii) when comparing the discriminatory power of macrorestriction analysis by using SmaI restriction
patterns with that of RAPD [random(ly) amplified polymorphic DNA] typing.
By using the same sampling frame, healthy individuals in the community
and inpatients of the same age group who had stayed at the University
Hospital in Nottingham for more than 3 weeks were sampled by use of
swabs taken from the anterior nares. Carriage strains of S. aureus obtained from the community were genotyped by
SmaI macrorestriction analysis, as well as by RAPD typing, by using two different primers. Carriage strains from hospitalized patients were typed by macrorestriction alone. Macrorestriction and
RAPD analyses were performed by standard published protocols (7; Harmony
[http: //www.phls.co.uk/International/Harmony/microtyping.htm]), and
genotypes were classified according to conventional criteria, with more
than two band differences defining separate genotypes or a cutoff value
of 70% for Pearson correlation coefficients discriminating genotypes
in the RAPD approach (1, 8).
Among the 117 carriage strains from the community, 57 types were
distinguished by macrorestriction analysis. Of 117 carriage strains
obtained from the hospital population 55 types were distinguished. The
distribution and type frequencies are presented in Tables 1 and 2.
The genetic diversity (D) of carriage strains in the community was 97.6%, with a CI of 96.8 to 98.5%, and for carriage strains from hospital patients (D) it equalled 89.5%, with
a CI of 84.4 to 94.7% (the CI values did not overlap).
We also compared the discriminatory ability of macrorestriction
analysis with RAPD typing for the sample of community carriage isolates. While macrorestriction analysis identified 57 SmaI
restriction patterns, 26 types could be discriminated when RAPD results
generated by different primers were combined (Table
3). The index of diversity based on the
combined RAPD grouping was 89.9%, and the CI was 86.5 to 93.3%.
For nominal scale data, such as phenotypic or genetic markers, there is
no mean or median that could serve as a reference for a central
tendency or a measure of variability. Instead, we can invoke the
concept of diversity to determine the distribution of observations
among categories. We suggest use of the standard deviation for
Simpson's index of diversity as a measure of dispersion around the
true diversity,
. Two times the standard deviation on either side of
the measured value should roughly include 95% of all of the expected
distribution of the sample mean and is thus an approximate measure for
the confidence with which various diversity indices can be estimated.
For highly diverse populations or typing techniques with extreme
abilities to discriminate genotypes, the number of classes (genotypes)
will increase with increasing sample size. Thus, the chance that two
randomly sampled isolates differ will increase, i.e., the index of
diversity becomes dependent on the sample size. Therefore, it is
important to compare samples of roughly the same size as long as the
number of classes depends on the sample size.
Using this algorithm, we concluded that the observed difference of the
genetic diversity with nonoverlapping CIs among community and hospital
carriage strains of S. aureus reflect two truly distinct population structures shaped by differential ecological constraints. Likewise, we have measured the discriminatory capacity of RAPD and
macrorestriction analysis with sufficient precision and can be
confident that the inability of RAPD typing to achieve the same degree
of discrimination as macrorestriction analysis is an inherent property
of these methods. We believe that an estimation of confidence intervals
when calculating the index of diversity greatly aids the comparison of
genetic diversity in different environments, as well as the ability to
objectively address the discriminatory potential of diverse typing systems.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Division of
Microbiology and Infectious Diseases, University Hospital, Queen's
Medical Centre, Clifton Blvd., Nottingham NG7 2UH, United Kingdom.
Phone: 44-115-970-9162. Fax: 44-115-970-9233. E-mail:
Hajo.Grundmann{at}Nottingham.ac.uk.
 |
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Journal of Clinical Microbiology, November 2001, p. 4190-4192, Vol. 39, No. 11
0095-1137/01/$04.00+0 DOI: 10.1128/JCM.39.11.4190-4192.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
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