Burkholderia mallei and pseudomallei
Author: Mark H. Weir
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Overview: Burkholderia and meliodosis
Melioidosis, which typically infects horses, mules and donkeys but can also present a potentially life threatening disease in humans as well, is caused by the bacterium Bukholderia pseudomallei (B. pseudimallei). The bacterium is present in numerous tropical regions such as Central and South America and Southeast Asia. Burkholderia mallei (B. mallei) is a close relative of B. pseudomallei both of which have been categorized as a B level bioterror agent by the CDC.
Summary Data
Brett, P.J. and Woods, D.E.(2000) Pathogenesis of and Immunity to Melioidosis Acta Tropica 74: 201210
Miller, W.R., Pannel, I., Cravitz, I., Tanner, W.A., Rosebury, T. (1947) Studies on Certain Biological Characteristics of Melleomyces mallei and Malleomyces pseudomallei II. Virulence and Infectivity for Animals Journal of Bacteriology 55: 127135
Experiment serial number 
Reference 
Host type 
Agent strain 
Route 
# of doses 
Dose units 
Response 
Best fit model 
Optimized parameter(s) 
LD_{50}/ID_{50}

18* 
^{[1]} 
mouse 
KHW 
intranasal 
5 
CFU 

exponential 
k = 1.00E04 
6.92E+03

17 
^{[1]} 
mouse 
KHW 
intranasal 
5 
CFU 

exponential 
k = 1.04E02 
6.63E+01

21 
^{[2]} 
guinea pig 
W294 
intraperitoneal 
6 
CFU 
death 
betaPoisson 
α = 2.67E01 , N_{50} = 2.55E+02 
2.55E+02

*This model is preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.


^{*} Recommended Model
Since intranasal exposure is closer to inhalation which is the likeliest exposure route for humans, especially compared to intraperitoneal, the data sets and resulting models from the Brett and Woods (2000) article is preferred. Also given the improved fit between the two data sets experiment 18 is chosen as the recommended model.
a:
Optimization Output for experiment 18
C57BL/6 Mice KHW Strain Data ^{[1]}
Dose 
Infected 
Noninfected 
Total

150 
0 
6 
6

450 
1 
5 
6

1350 
1 
5 
6

4050 
3 
3 
6

12200 
3 
3 
6


Goodness of fit and model selection
Model 
Deviance 
Δ 
Degrees of freedom 
χ^{2}_{0.95,1} pvalue 
χ^{2}_{0.95,mk} pvalue

Exponential

3.36

2.17

4

3.84 0.141

9.49 0.499

Beta Poisson

1.19

3

7.81 0.755

Exponential is preferred to betaPoisson; cannot reject good fit for exponential.


Optimized parameters for the exponential model, from 10000 bootstrap iterations
Parameter

MLE estimate

Percentiles

0.5% 
2.5% 
5% 
95% 
97.5% 
99.5%

k 
1E04 
2.87E05 
4.15E05 
4.99E05 
1.89E04 
2.13E04 
2.70E04

ID50/LD50/ETC* 
6.92E+03 
2.57E+03 
3.26E+03 
3.68E+03 
1.39E+04 
1.67E+04 
2.41E+04

*Not a parameter of the exponential model; however, it facilitates comparison with other models.


Parameter histogram for exponential model (uncertainty of the parameter) Exponential model plot, with confidence bounds around optimized model
Optimization Output for experiment 17
BALB/c Mice KHW Strain Data ^{[1]}
Dose 
Infected 
Noninfected 
Total

5 
0 
6 
6

15 
0 
6 
6

45 
3 
1 
4

135 
4 
2 
6

405 
6 
0 
6


Goodness of fit and model selection
Model 
Deviance 
Δ 
Degrees of freedom 
χ^{2}_{0.95,1} pvalue 
χ^{2}_{0.95,mk} pvalue

Exponential

5.25

0.000362

4

3.84 1

9.49 0.263

Beta Poisson

5.25

3

7.81 0.154

Exponential is preferred to betaPoisson; cannot reject good fit for exponential.


Optimized parameters for the exponential model, from 10000 bootstrap iterations
Parameter

MLE estimate

Percentiles

0.5% 
2.5% 
5% 
95% 
97.5% 
99.5%

k 
1.04E02 
4.94E03 
5.96E03 
6.60E03 
1.92E02 
2.45E02 
2.45E02

ID50/LD50/ETC* 
6.63E+01 
2.82E+01 
2.82E+01 
3.61E+01 
1.05E+02 
1.16E+02 
1.40E+02

*Not a parameter of the exponential model; however, it facilitates comparison with other models.


Parameter histogram for exponential model (uncertainty of the parameter) Exponential model plot, with confidence bounds around optimized model
Optimization Output for experiment 21
Guinea Pigs W294 Strain Data ^{[2]}
Dose 
Dead 
Survived 
Total

44 
1 
4 
5

440 
3 
2 
5

4400 
4 
1 
5

44000 
5 
0 
5

440000 
5 
0 
5

4.4E+06 
4 
1 
5


Goodness of fit and model selection
Model 
Deviance 
Δ 
Degrees of freedom 
χ^{2}_{0.95,1} pvalue 
χ^{2}_{0.95,mk} pvalue

Exponential

70.3

66.1

5

3.84 4.44e16

11.1 8.93e14

Beta Poisson

4.14

4

9.49 0.387

BetaPoisson fits better than exponential; cannot reject good fit for betaPoisson.


Optimized parameters for the betaPoisson model, from 10000 bootstrap iterations
Parameter

MLE estimate

Percentiles

0.5% 
2.5% 
5% 
95% 
97.5% 
99.5%

α

2.67E01

3.36E02 
8.80E02 
1.16E01 
1.05E+01 
3.45E+02 
3.55E+03

N_{50}

2.55E+02

4.80E07 
2.49E+00 
1.48E+01 
1.35E+03 
1.80E+03 
3.22E+03


Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters. beta Poisson model plot, with confidence bounds around optimized model
References
 ↑ ^{1.0} ^{1.1} ^{1.2} ^{1.3} Brett, P.J. and Woods, D.E.(2000) Pathogenesis of and Immunity to Melioidosis Acta Tropica 74: 201210
 ↑ ^{2.0} ^{2.1} Miller, W.R., Pannel, I., Cravitz, I., Tanner, W.A., Rosebury, T. (1947) Studies on Certain Biological Characteristics of Melleomyces mallei and Malleomyces pseudomallei II. Virulence and Infectivity for Animals Journal of Bacteriology 55: 127135