Vol. 56, No. 7
APPLIED AND ENVIRONMENTAL MICROBIOLOGY, JUlY 1990, p. 2219-2222
0099-2240/90/072219-04$02.00/0
Application of the Theory of Adaptive Polymorphism to the Ecology and Epidemiology of Pathogenic Yeasts PAUL R. HUNTERt* AND CHERRY A. M. FRASER
Division of Hospital Infection, Central Public Health Laboratory, 61 Colindale Avenue, London NW9 5HT, England Received 26 February 1990/Accepted 23 April 1990
The theory of adaptive polymorphism predicts that species occupying broad ecological niches will be phenotypically and genotypically more varied than those occupying narrow niches. It is suggested that this theory has direct relevance to the epidemiology of microbial pathogens in that environmental pathogens inhabit a broader niche and should be expected to exhibit greater variation than pathogens that are obligate commensals. This proved to be the case when one obligate commensal, the pathogenic yeast Candida albicans, was compared with other Candida spp. and an environmental pathogen, Cryptococcus neoformans. Further evidence of this relationship is derived from the literature. This observation adds further support to the theory of adaptive polymorphism, although the mechanisms of maintenance of polymorphism in asexualHy reproducing populations must be different from those in sexually reproducing populations. This observation may give important clues to the epidemiology of those infections for which it is not already known.
Population variance, dispersion, or diversity is a powerful concept in both ecological and evolutionary theory. One theory in particular seeks to relate population variance to the ecological concept of niche width. This theory, the theory of adaptive polymorphism, states that if of two inversions coexisting in a population, one or the other is selected for at various times, then populations with both inversions will be at an advantage over populations with only one (3). This theory predicts that populations occupying wide ecological niches show greater variation than do populations occupying narrow niches (15, 18, 21). For example, taking related populations of insular birds, a population inhabiting an island with a single soil type shows less variation in bill width than a related species occupying an island with several soil types (21). It is suggested that this theory has direct relevance to microbial ecology and hence epidemiology. The reservoir of infection of microbial pathogens can be humans, as for venereal diseases; animals, as for the zoonoses; or the environment, as for legionellosis. The theory of adaptive polymorphism predicts that environmental organisms show greater variation than do obligate human pathogens. To test this prediction, the population variances of an obligate commensal pathogen, Candida albicans, and a selection of other Candida species were compared with that of an environmentally derived pathogen, Cryptococcus neofor-
from the National Collection of Pathogenic Fungi, Central Public Health Laboratory, London; their numbers were NCPF 3153, NCPF 3118, NCPF 3179, and NCPF 3108. The remaining strains and their sources and NCPF numbers (if given) are listed in Table 1. Strain characterization was by carbon source assimilation reactions and extracellular enzyme production. The carbon source assimilation reactions of the 100 strains were tested with the API 50CH kit [API-Bio Merieux (UK) Ltd., Basingstoke, England]. Additional carbon sources were from the ATB 32GN kit (API-Bio Merieux). The test procedure used was as previously described (7). Extracellular enzyme production was detected by means of the API ZYM system, by the method originally described for C. albicans (4). For numerical analysis, a positive response was given the value 1 and a negative response was given the value 0. Population variability (mean population variance) was calculated by the Van Valen modification of Levene's test (22), which is given by the mean Euclidean distance of all members of a population from the population centroid: N
p
V ±= [E (x,jx1)2
I1/2
IN
i=l J=1
where N is the total number of strains in the population, P is the number of tests used to characterize the strains, xi is the value of the jth character of the ith strain, and xj is the centroid value for the jth character. The centroid values were then taken as the median value for each character (16). In the original description of the method, the significance of differences in variation between populations was calculated by Student's t test between the set of distances for each population. In this study, because more than one species group was investigated, the significance was tested by the one-way analysis of variance (1). The derivation of the median centroid and the mean population variance can be illustrated by considering the following hypothetical example. Consider a population of three strains characterized by five tests as follows: 1 0 0 0 0 Strain Strain 2 1 1 1 0 1
mans.
MATERIALS AND METHODS A total of 100 strains of C. albicans isolated from a variety of clinical samples were compared with 20 strains of Cryptococcus neoformans, 9 strains of Candida tropicalis, 10 strains of Candida parapsilosis, and 7 strains of Candida glabrata. The origins of the 100 strains of C. albicans have already been described; isolated were 19 strains from feces, 29 strains from vaginal swabs, 9 strains from urine, 10 strains from skin lesions, and 19 strains from blood cultures or deep sites (7). Included within these 100 strains were 4 strains * Corresponding author. t Present address: Public Health Laboratory, City Hospital, Hoole Lane, Chester CH2 3EG, England.
2219
2220
APPL. ENVIRON. MICROBIOL.
HUNTER AND FRASER
TABLE 1. Sources and National Collection of Pathogenic Fungi (NCPF) numbers of strains other than C. albicans Strain and NCPF no.
Year
Geographical origin
3347 3355 3360 3361 3364 3379 3386 3389 3391
1974 1985 1985 1985 1985 1985 1986 1987 1987 1987
Kenya London London England Newcastle London London London London London
3392 3395 3398 3401 3404 3409 3410 3412 3413 3414
1987 1986 1987 1987 1987 1987 1987 1987 1987 1987
London Taunton London Edinburgh London London London Manchester London London
CSF Pus from hip CSF from AIDS patient CSF from AIDS patient CSF from lymphoma patient CSF from AIDS patient CSF from AIDS patient Vertebral bone biopsy CSF from AIDS patient Blood from patient with systemic lupus erythematosus CSF from lymphoma patient CSF (no predisposing cause) CSF from AIDS patient CSF from AIDS patient CSF from AIDS patient CSF from AIDS patient Unknown Blood from AIDS patient CSF from AIDS patient CSF from AIDS patient
C. tropicalis
1986 1987 1986 1986 1986 1986 1987 1986 1986
Luton Cardiff London London London London Hull Glasgow Glasgow
Vaginal swab Urine Central venous line tip Cavitating lung lesion Vaginal swab Feces Blood culture Sputum Axillary skin swab
C. parapsilosis
1987 1987 1987 1987 1987 1987 1987 1987 1987 1956
Cardiff London East Surrey Jersey London Zoo London London London London London
Feces Blood culture Toe swab Peritoneal fluid Swab from elephant Unknown Unknown Ear Urine Toenail
3104
ear
C. glabrata
3264 3309 3203
Species
Mean variance
95% confidence limits
C. glabrata C. albicans C. parapsilosis C. tropicalis Cryptococcus neoformans
0.735 1.034 1.381 1.714 2.449
0.044-1.426 0.901-1.168 1.130-1.632 1.425-2.003 2.163-2.734
Source'
Cryptococcus neoformans 3224b
TABLE 2. Mean population variances and 95% confidence limits for some single species populations of pathogenic yeasts
Di
=
+/11)2
+
(o
1)2 + (o
0)2 + (o 0)2 + (o 0)2 =
D2
=
1(1-1)2
+
(1
1)2 + (1
0)2 + (o
Nasal swab Unknown Human feces Sputum Dolphin kidney
Sputum Heart valve
a
CSF, Cerebrospinal fluid; AIDS, acquired immune deficiency syndrome.
b
Cryptococcus neoformans var. gattii.
Strain 3 0 1 0 1 0 The population median centroid is then calculated by taking the median result for each characteristic as follows: Centroid 1 1 0 0 0 The Euclidean distance (D) of each strain from the centroid is then calculated:
0)2
=
%/'2
V
D3 = (0-1)2 + (1 1)2 + (0 0)2 + (1 0)2 + (0 0)2 = Finally, the population variance is taken to be the mean distance of the strains from the centroid: population variance = (Vi + V2 + V2)13 = 1.276. RESULTS The mean population variances and the 95% confidence limits for the different species groups are shown in Table 2. It can be seen that there was an increase in variance from C. glabrata to Cryptococcus neoformans and through C. albicans, C. parapsilosis, and C. tropicalis. The differences in population variance between the different species were highly significant (F = 16.73, f1 = 5, f2 = 140, P < 0.001). Table 3 shows the mean value for each test that was variable for one or more of the test populations. Those characteristics that gave a mean value of 0.5 were the most variable within a species. There were 8 variable characteristics for C. glabrata, 36 for C. albicans, 15 for C. parapsilosis, 18 for C tropicalis, and 30 for Cryptococcus neoformans. However, the data presented in Table 2 are complicated by the different numbers of strains in the species populations. There are more variable tests recorded for C. albicans than for the other species, but with 100 strains in the group, this is not surprising. Most of the C. albicans characteristics showed low variance. If we consider only those characters with higher variance (say a mean value of greater than 0.2 and less than 0.8), then there are no highly variable characteristics for C. albicans, 3 for C. glabrata, 5 for C. parapsilosis, 8 for C. tropicalis, and 11 for Cryptococcus
Southampton Guildford Holland London Federal Republic of Germany 1987 London 1987 London
1987 1980 1983 1986 1975
0)2 + (1
neoformans.
DISCUSSION Regarding the ecology of the Candida spp. included in this study, it has been suggested that C. albicans and C. glabrata are obligatory animal commensals, while C. tropicalis and C. parapsilosis appear to be facultative commensals (5, 12). On the other hand, Cryptococcus neoformans appears to be an environmental organism which has a predilection for decaying bird feces (9). The results presented here confirm an increasing population variance from the obligate commensals to the facultative commensals and then to the environmental organism, as had been predicted by the theory of adaptive polymorphism. Other examples of microbial population variability correlated with population ecology and hence with epidemiology are present in the literature. One area in which this can be demonstrated is in population analysis by isoenzyme isomerism. For example, Legionella pneumophila exhibits about
2221
ADAPTIVE POLYMORPHISM AND MICROBIAL ECOLOGY
VOL. 56, 1990
TABLE 3. Mean values for characteristics showing intraspecific variation Mean valuea for: Test
API 50CH Glycerol
D-Arabinose L-Arabinose Ribose D-Xylose Adonitol Galactose L-Sorbose Rhamnose Dulcitol Inositol Sorbitol a-Methyl-D-mannoside a-Methyl-D-glucoside N-Acetylglucosamine Amygdalin Arbutin Salicin Cellobiose Maltose Lactose Melibiose Trehalose Inulin Melezitose Raffinose Starch Glycogen Xylitol Gentibiose D-Turanose D-Lyxose D-Tagatose D-Arabitol Gluconate 2-Ketogluconate 5-Ketogluconate ATB 32GN Acetate DL-Lactate L-Alanine
3-Hydroxybenzoate L-Serine Propionate Valerate Citrate 4-Hydroxybenzoate L-Proline
Cytccu C. albicans
C.
tropicalis
,-Glucosidase
N-Acetyl-p-glucosaminidase
neoformans
C. glabrata
parapsilosis
0.14
0.7
0.01 0.01 0.01
0.50
0.25 0.8 0.15 0.75
-
0.97 0.87
0.9
0.11 0.01
0.11
0.9 0.6 -
0.99 0.03 0.97 0.99
-
0.04 0.01
0.33
-
0.90 0.95 0.95 0.85
-
0.55 0.95 0.05 0.25 0.2 0.15 0.9
0.8 0.14 0.22
-
0.98 0.11 0.22
0.01 0.94
0.4
0.86
0.6 0.11 0.11
0.03 0.01 0.97
0.55 0.5
0.8 -
0.05 0.9
-
-
0.97 0.11 0.01 0.96 0.01 0.99 0.04 0.97 0.93 0.98 0.85
0.81 0.13 0.99
-
0.78
0.78 0.22 0.11 0.67 0.89
API ZYM Alkaline phosphatase
Lipase Valine arylamidase Naphthol-AS-BI-phosphohydrolase P-Glucuronidase a-Glucosidase
C.
0.97 0.97
0.05
0.14
0.1 -
0.29
0.4 0.9 0.3
0.3
0.9 0.6 0.3 -
0.05 0.7
-
0.71
0.9
0.86
0.85 0.3
0.89
0.45 0.95 0.85 0.55
0.11
0.06 0.92
0.89 0.22
-
a Variance of characteristic increases as the mean value moves away from 0.0 or 1.0 (i.e., the most variable characteristic would have -, Characteristic shows no variation within species.
a mean
value of 0.5).
2222
HUNTER AND FRASER
50 patterns (17), compared with only 1 for Bordetella pertussis (10). Escherichia coli, an organism colonizing and infecting a wide range of hosts, is rather more variable than Shigella sonnei, an organism infecting only humans (11). Aeromonas hydrophila, an environmental organism, exhibits greater genomic variation (8) than does Neisseria gonorrhoeae, an obligate human parasite (6). Similarly, Chlamydia psittaci, an organism with a wide host range, has a greater degree of DNA polymorphism than does Chlamydia trachomatis, whose host range is rather more limited (2). Phenotypic variability of environmental species of mycobacteria is greater than that of Mycobacterium tuberculosis, an obligate parasite (20). The theory of adaptive polymorphism was developed to explain polymorphism in sexually reproducing populations; thus, a broad niche width would maintain polymorphism in the genetic pool available to future generations by selection of different inversions at different times (14). In asexually reproducing populations, such as microbial pathogens, new generations are clonally derived from their parent organisms. Thus, elimination of polymorphism in microbial pathogens with a narrow niche width may be explained by the selection of the most adapted phenotypes as the less-welladapted phenotype becomes extinct (19). In environmental pathogens, the varying selective pressures mitigate against the selection of a limited number of phenotypes. Although the results obtained in this study have fulfilled the predictions of the theory of adaptive polymorphism, this could have been due to factors other than niche width. Cryptococcus neoformans is a haploid organism, and one might expect it to exhibit greater polymorphism, due to mutation, than C. albicans, a diploid organism. However, selective pressure has an effect on population polymorphism very much stronger than does mutation (14, 19). Furthermore, C. glabrata, another haploid organism, has an even lower population variance than C. albicans. Similarly, if the species definition of Cryptococcus neoformans were drawn more widely than that of C. albicans, then one would again expect a greater degree of polymorphism. This may be further complicated for Cryptococcus neoformans by the inclusion of a strain of Cryptococcus neoformans var. gattii. However, both species can be defined by cluster analysis at the 85% similarity level (P. R. Hunter, M.D. thesis, University of Manchester, Manchester, England, 1989). Furthermore, the single strain of Cryptococcus neoformans var. gattii differed from the population centroid by less than the population mean variance (i.e., dropping Cryptococcus neoformans var. gattii from the analysis would have increased the population variance of Cryptococcus neoformans even more). There does seem to be a general trend towards greater polymorphism in environmental pathogens compared with obligate commensals. The understanding of microbial epidemiology is still incomplete, as in the case of Helicobacter pylori (13). Studies of the population variability may well provide an important clue to the epidemiology of organisms for which it is not known. Furthermore, studies of population variance in microorganisms add further support to the theory of adaptive polymorphism itself.
APPL. ENVIRON. MICROBIOL.
ACKNOWLEDGMENT We thank Colin Campbell of the Mycological Reference Laboratory, Central Public Health Laboratory, London, England, for many of the strains included in this study and for help in the identification of several of the yeasts. LITERATURE CITED 1. Armitage, P., and G. Berry. 1987. Statistical methods in medical research, 2nd ed., p. 186-213. Blackwell Scientific Publications, Ltd., Oxford. 2. Barnes, R. C. 1989. Laboratory diagnosis of human chlamydial infections. Clin. Microbiol. Rev. 2:119-136. 3. Cain, A. J., and P. M. Sheppard. 1954. The theory of adaptive polymorphism. Am. Nat. 88:321-326. 4. Casal, M., and M. J. Linares. 1983. Preliminary investigation of Candida albicans biovars. J. Clin. Microbiol. 18:430-431. 5. Do Carmo-Sousa, L. 1969. Distribution of yeasts in nature, p. 79-105. In A. H. Rose and J. S. Harrison (ed.), The yeasts, vol. 1. Academic Press, Inc. (London), Ltd., London. 6. Guibourdenche, M., M. Y. Popoff, and J. Y. Riou. 1986. Deoxyribonucleic acid relatedness among Neisseria gonorrhoeae, N. meningitidis, N. lactamica, N. cinerea and N. polysaccharea. Ann. Inst. Pasteur Microbiol. 137B:177-185. 7. Hunter, P. R., and C. A. M. Fraser. 1989. Application of a numerical index of discriminatory power to a comparison of four physiochemical typing methods for Candida albicans. J. Clin. Microbiol. 27:2156-2160. 8. Kuijper, E. J., A. G. Steigerwalt, B. S. C. I. M. Schoenmakers, M. F. Peeters, H. C. Zanen, and D. J. Brenner. 1989. Phenotypic characterization and DNA relatedness in human fecal isolates of Aeromonas spp. J. Clin. Microbiol. 27:132-138. 9. Kwon-Chung, K. J., A. K. Varma, and D. H. Howard. 1988. Ecology and epidemiology of Cryptococcus neoformans: a study of recent isolates in the United States, p. 107-112. In J. M. Torres-Rodriguez (ed.), Proceedings of the X Congress of the International Society of Human and Animal Mycology-ISHAM. J. R. Prous S.A., Barcelona, Spain. 10. Musser, J. M., E. L. Hewlett, M. S. Peppler, and R. K. Selander. 1986. Genetic diversity and relationships in populations of Bordetella spp. J. Bacteriol. 166:230-237. 11. Ochman, H., T. S. Whittam, D. A. Caugant, and R. K. Selander. 1983. Enzyme polymorphism and genetic population structure in Escherichia coli and Shigella. J. Gen. Microbiol. 129:27152726. 12. Odds, F. C. 1988. Candida and candidosis. Bailliere Tindall, London. 13. Penner, J. L. 1988. The genus Campylobacter: a decade of progress. Clin. Microbiol. Rev. 1:157-172. 14. Roughgarden, J. 1979. Theory of population genetics and evolutionary ecology: an introduction. Macmillan Publishing Co., Inc., New York. 15. Schoener, T. W. 1974. Resource partitioning in ecological communities. Science 185:27-39. 16. Schultz, B. 1983. On Levene's test and other statistics of variation. Evol. Theory 6:197-203. 17. Selander, R. K., R. M. McKinney, T. S. Whittam, W. F. Bibb, D. J. Brenner, F. S. Nolte, and P. E. Pattison. 1985. Genetic structure of populations of Legionella pneumophila. J. Bacteriol. 163:1021-1037. 18. Selander, R. K., M. H. Smith, S. Y. Yang, W. E. Johnson, and J. B. Gentry. 1971. Biochemical polymorphism and systematics in the genus Peromyscus. I. Variation in the old-field mouse. Univ. Tex. Publ. Stud. Genet. 6:49-90. 19. Smith, J. M. 1989. Evolutionary genetics, p. 14-28. Oxford University Press, Oxford. 20. Tsukamura, M. 1966. Adansonian classification of mycobacteria. J. Gen. Microbiol. 45:253-257. 21. Van Valen, L. 1965. Morphological variation and width of ecological niche. Am. Nat. 99:377-390. 22. Van Valen, L. 1978. The statistics of variation. Evol. Theory 4:33-43.
APPLIED AND ENVIRONMENTAL MICROBIOLOGY, JUlY 1990, p. 2219-2222
0099-2240/90/072219-04$02.00/0
Application of the Theory of Adaptive Polymorphism to the Ecology and Epidemiology of Pathogenic Yeasts PAUL R. HUNTERt* AND CHERRY A. M. FRASER
Division of Hospital Infection, Central Public Health Laboratory, 61 Colindale Avenue, London NW9 5HT, England Received 26 February 1990/Accepted 23 April 1990
The theory of adaptive polymorphism predicts that species occupying broad ecological niches will be phenotypically and genotypically more varied than those occupying narrow niches. It is suggested that this theory has direct relevance to the epidemiology of microbial pathogens in that environmental pathogens inhabit a broader niche and should be expected to exhibit greater variation than pathogens that are obligate commensals. This proved to be the case when one obligate commensal, the pathogenic yeast Candida albicans, was compared with other Candida spp. and an environmental pathogen, Cryptococcus neoformans. Further evidence of this relationship is derived from the literature. This observation adds further support to the theory of adaptive polymorphism, although the mechanisms of maintenance of polymorphism in asexualHy reproducing populations must be different from those in sexually reproducing populations. This observation may give important clues to the epidemiology of those infections for which it is not already known.
Population variance, dispersion, or diversity is a powerful concept in both ecological and evolutionary theory. One theory in particular seeks to relate population variance to the ecological concept of niche width. This theory, the theory of adaptive polymorphism, states that if of two inversions coexisting in a population, one or the other is selected for at various times, then populations with both inversions will be at an advantage over populations with only one (3). This theory predicts that populations occupying wide ecological niches show greater variation than do populations occupying narrow niches (15, 18, 21). For example, taking related populations of insular birds, a population inhabiting an island with a single soil type shows less variation in bill width than a related species occupying an island with several soil types (21). It is suggested that this theory has direct relevance to microbial ecology and hence epidemiology. The reservoir of infection of microbial pathogens can be humans, as for venereal diseases; animals, as for the zoonoses; or the environment, as for legionellosis. The theory of adaptive polymorphism predicts that environmental organisms show greater variation than do obligate human pathogens. To test this prediction, the population variances of an obligate commensal pathogen, Candida albicans, and a selection of other Candida species were compared with that of an environmentally derived pathogen, Cryptococcus neofor-
from the National Collection of Pathogenic Fungi, Central Public Health Laboratory, London; their numbers were NCPF 3153, NCPF 3118, NCPF 3179, and NCPF 3108. The remaining strains and their sources and NCPF numbers (if given) are listed in Table 1. Strain characterization was by carbon source assimilation reactions and extracellular enzyme production. The carbon source assimilation reactions of the 100 strains were tested with the API 50CH kit [API-Bio Merieux (UK) Ltd., Basingstoke, England]. Additional carbon sources were from the ATB 32GN kit (API-Bio Merieux). The test procedure used was as previously described (7). Extracellular enzyme production was detected by means of the API ZYM system, by the method originally described for C. albicans (4). For numerical analysis, a positive response was given the value 1 and a negative response was given the value 0. Population variability (mean population variance) was calculated by the Van Valen modification of Levene's test (22), which is given by the mean Euclidean distance of all members of a population from the population centroid: N
p
V ±= [E (x,jx1)2
I1/2
IN
i=l J=1
where N is the total number of strains in the population, P is the number of tests used to characterize the strains, xi is the value of the jth character of the ith strain, and xj is the centroid value for the jth character. The centroid values were then taken as the median value for each character (16). In the original description of the method, the significance of differences in variation between populations was calculated by Student's t test between the set of distances for each population. In this study, because more than one species group was investigated, the significance was tested by the one-way analysis of variance (1). The derivation of the median centroid and the mean population variance can be illustrated by considering the following hypothetical example. Consider a population of three strains characterized by five tests as follows: 1 0 0 0 0 Strain Strain 2 1 1 1 0 1
mans.
MATERIALS AND METHODS A total of 100 strains of C. albicans isolated from a variety of clinical samples were compared with 20 strains of Cryptococcus neoformans, 9 strains of Candida tropicalis, 10 strains of Candida parapsilosis, and 7 strains of Candida glabrata. The origins of the 100 strains of C. albicans have already been described; isolated were 19 strains from feces, 29 strains from vaginal swabs, 9 strains from urine, 10 strains from skin lesions, and 19 strains from blood cultures or deep sites (7). Included within these 100 strains were 4 strains * Corresponding author. t Present address: Public Health Laboratory, City Hospital, Hoole Lane, Chester CH2 3EG, England.
2219
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APPL. ENVIRON. MICROBIOL.
HUNTER AND FRASER
TABLE 1. Sources and National Collection of Pathogenic Fungi (NCPF) numbers of strains other than C. albicans Strain and NCPF no.
Year
Geographical origin
3347 3355 3360 3361 3364 3379 3386 3389 3391
1974 1985 1985 1985 1985 1985 1986 1987 1987 1987
Kenya London London England Newcastle London London London London London
3392 3395 3398 3401 3404 3409 3410 3412 3413 3414
1987 1986 1987 1987 1987 1987 1987 1987 1987 1987
London Taunton London Edinburgh London London London Manchester London London
CSF Pus from hip CSF from AIDS patient CSF from AIDS patient CSF from lymphoma patient CSF from AIDS patient CSF from AIDS patient Vertebral bone biopsy CSF from AIDS patient Blood from patient with systemic lupus erythematosus CSF from lymphoma patient CSF (no predisposing cause) CSF from AIDS patient CSF from AIDS patient CSF from AIDS patient CSF from AIDS patient Unknown Blood from AIDS patient CSF from AIDS patient CSF from AIDS patient
C. tropicalis
1986 1987 1986 1986 1986 1986 1987 1986 1986
Luton Cardiff London London London London Hull Glasgow Glasgow
Vaginal swab Urine Central venous line tip Cavitating lung lesion Vaginal swab Feces Blood culture Sputum Axillary skin swab
C. parapsilosis
1987 1987 1987 1987 1987 1987 1987 1987 1987 1956
Cardiff London East Surrey Jersey London Zoo London London London London London
Feces Blood culture Toe swab Peritoneal fluid Swab from elephant Unknown Unknown Ear Urine Toenail
3104
ear
C. glabrata
3264 3309 3203
Species
Mean variance
95% confidence limits
C. glabrata C. albicans C. parapsilosis C. tropicalis Cryptococcus neoformans
0.735 1.034 1.381 1.714 2.449
0.044-1.426 0.901-1.168 1.130-1.632 1.425-2.003 2.163-2.734
Source'
Cryptococcus neoformans 3224b
TABLE 2. Mean population variances and 95% confidence limits for some single species populations of pathogenic yeasts
Di
=
+/11)2
+
(o
1)2 + (o
0)2 + (o 0)2 + (o 0)2 =
D2
=
1(1-1)2
+
(1
1)2 + (1
0)2 + (o
Nasal swab Unknown Human feces Sputum Dolphin kidney
Sputum Heart valve
a
CSF, Cerebrospinal fluid; AIDS, acquired immune deficiency syndrome.
b
Cryptococcus neoformans var. gattii.
Strain 3 0 1 0 1 0 The population median centroid is then calculated by taking the median result for each characteristic as follows: Centroid 1 1 0 0 0 The Euclidean distance (D) of each strain from the centroid is then calculated:
0)2
=
%/'2
V
D3 = (0-1)2 + (1 1)2 + (0 0)2 + (1 0)2 + (0 0)2 = Finally, the population variance is taken to be the mean distance of the strains from the centroid: population variance = (Vi + V2 + V2)13 = 1.276. RESULTS The mean population variances and the 95% confidence limits for the different species groups are shown in Table 2. It can be seen that there was an increase in variance from C. glabrata to Cryptococcus neoformans and through C. albicans, C. parapsilosis, and C. tropicalis. The differences in population variance between the different species were highly significant (F = 16.73, f1 = 5, f2 = 140, P < 0.001). Table 3 shows the mean value for each test that was variable for one or more of the test populations. Those characteristics that gave a mean value of 0.5 were the most variable within a species. There were 8 variable characteristics for C. glabrata, 36 for C. albicans, 15 for C. parapsilosis, 18 for C tropicalis, and 30 for Cryptococcus neoformans. However, the data presented in Table 2 are complicated by the different numbers of strains in the species populations. There are more variable tests recorded for C. albicans than for the other species, but with 100 strains in the group, this is not surprising. Most of the C. albicans characteristics showed low variance. If we consider only those characters with higher variance (say a mean value of greater than 0.2 and less than 0.8), then there are no highly variable characteristics for C. albicans, 3 for C. glabrata, 5 for C. parapsilosis, 8 for C. tropicalis, and 11 for Cryptococcus
Southampton Guildford Holland London Federal Republic of Germany 1987 London 1987 London
1987 1980 1983 1986 1975
0)2 + (1
neoformans.
DISCUSSION Regarding the ecology of the Candida spp. included in this study, it has been suggested that C. albicans and C. glabrata are obligatory animal commensals, while C. tropicalis and C. parapsilosis appear to be facultative commensals (5, 12). On the other hand, Cryptococcus neoformans appears to be an environmental organism which has a predilection for decaying bird feces (9). The results presented here confirm an increasing population variance from the obligate commensals to the facultative commensals and then to the environmental organism, as had been predicted by the theory of adaptive polymorphism. Other examples of microbial population variability correlated with population ecology and hence with epidemiology are present in the literature. One area in which this can be demonstrated is in population analysis by isoenzyme isomerism. For example, Legionella pneumophila exhibits about
2221
ADAPTIVE POLYMORPHISM AND MICROBIAL ECOLOGY
VOL. 56, 1990
TABLE 3. Mean values for characteristics showing intraspecific variation Mean valuea for: Test
API 50CH Glycerol
D-Arabinose L-Arabinose Ribose D-Xylose Adonitol Galactose L-Sorbose Rhamnose Dulcitol Inositol Sorbitol a-Methyl-D-mannoside a-Methyl-D-glucoside N-Acetylglucosamine Amygdalin Arbutin Salicin Cellobiose Maltose Lactose Melibiose Trehalose Inulin Melezitose Raffinose Starch Glycogen Xylitol Gentibiose D-Turanose D-Lyxose D-Tagatose D-Arabitol Gluconate 2-Ketogluconate 5-Ketogluconate ATB 32GN Acetate DL-Lactate L-Alanine
3-Hydroxybenzoate L-Serine Propionate Valerate Citrate 4-Hydroxybenzoate L-Proline
Cytccu C. albicans
C.
tropicalis
,-Glucosidase
N-Acetyl-p-glucosaminidase
neoformans
C. glabrata
parapsilosis
0.14
0.7
0.01 0.01 0.01
0.50
0.25 0.8 0.15 0.75
-
0.97 0.87
0.9
0.11 0.01
0.11
0.9 0.6 -
0.99 0.03 0.97 0.99
-
0.04 0.01
0.33
-
0.90 0.95 0.95 0.85
-
0.55 0.95 0.05 0.25 0.2 0.15 0.9
0.8 0.14 0.22
-
0.98 0.11 0.22
0.01 0.94
0.4
0.86
0.6 0.11 0.11
0.03 0.01 0.97
0.55 0.5
0.8 -
0.05 0.9
-
-
0.97 0.11 0.01 0.96 0.01 0.99 0.04 0.97 0.93 0.98 0.85
0.81 0.13 0.99
-
0.78
0.78 0.22 0.11 0.67 0.89
API ZYM Alkaline phosphatase
Lipase Valine arylamidase Naphthol-AS-BI-phosphohydrolase P-Glucuronidase a-Glucosidase
C.
0.97 0.97
0.05
0.14
0.1 -
0.29
0.4 0.9 0.3
0.3
0.9 0.6 0.3 -
0.05 0.7
-
0.71
0.9
0.86
0.85 0.3
0.89
0.45 0.95 0.85 0.55
0.11
0.06 0.92
0.89 0.22
-
a Variance of characteristic increases as the mean value moves away from 0.0 or 1.0 (i.e., the most variable characteristic would have -, Characteristic shows no variation within species.
a mean
value of 0.5).
2222
HUNTER AND FRASER
50 patterns (17), compared with only 1 for Bordetella pertussis (10). Escherichia coli, an organism colonizing and infecting a wide range of hosts, is rather more variable than Shigella sonnei, an organism infecting only humans (11). Aeromonas hydrophila, an environmental organism, exhibits greater genomic variation (8) than does Neisseria gonorrhoeae, an obligate human parasite (6). Similarly, Chlamydia psittaci, an organism with a wide host range, has a greater degree of DNA polymorphism than does Chlamydia trachomatis, whose host range is rather more limited (2). Phenotypic variability of environmental species of mycobacteria is greater than that of Mycobacterium tuberculosis, an obligate parasite (20). The theory of adaptive polymorphism was developed to explain polymorphism in sexually reproducing populations; thus, a broad niche width would maintain polymorphism in the genetic pool available to future generations by selection of different inversions at different times (14). In asexually reproducing populations, such as microbial pathogens, new generations are clonally derived from their parent organisms. Thus, elimination of polymorphism in microbial pathogens with a narrow niche width may be explained by the selection of the most adapted phenotypes as the less-welladapted phenotype becomes extinct (19). In environmental pathogens, the varying selective pressures mitigate against the selection of a limited number of phenotypes. Although the results obtained in this study have fulfilled the predictions of the theory of adaptive polymorphism, this could have been due to factors other than niche width. Cryptococcus neoformans is a haploid organism, and one might expect it to exhibit greater polymorphism, due to mutation, than C. albicans, a diploid organism. However, selective pressure has an effect on population polymorphism very much stronger than does mutation (14, 19). Furthermore, C. glabrata, another haploid organism, has an even lower population variance than C. albicans. Similarly, if the species definition of Cryptococcus neoformans were drawn more widely than that of C. albicans, then one would again expect a greater degree of polymorphism. This may be further complicated for Cryptococcus neoformans by the inclusion of a strain of Cryptococcus neoformans var. gattii. However, both species can be defined by cluster analysis at the 85% similarity level (P. R. Hunter, M.D. thesis, University of Manchester, Manchester, England, 1989). Furthermore, the single strain of Cryptococcus neoformans var. gattii differed from the population centroid by less than the population mean variance (i.e., dropping Cryptococcus neoformans var. gattii from the analysis would have increased the population variance of Cryptococcus neoformans even more). There does seem to be a general trend towards greater polymorphism in environmental pathogens compared with obligate commensals. The understanding of microbial epidemiology is still incomplete, as in the case of Helicobacter pylori (13). Studies of the population variability may well provide an important clue to the epidemiology of organisms for which it is not known. Furthermore, studies of population variance in microorganisms add further support to the theory of adaptive polymorphism itself.
APPL. ENVIRON. MICROBIOL.
ACKNOWLEDGMENT We thank Colin Campbell of the Mycological Reference Laboratory, Central Public Health Laboratory, London, England, for many of the strains included in this study and for help in the identification of several of the yeasts. LITERATURE CITED 1. Armitage, P., and G. Berry. 1987. Statistical methods in medical research, 2nd ed., p. 186-213. Blackwell Scientific Publications, Ltd., Oxford. 2. Barnes, R. C. 1989. Laboratory diagnosis of human chlamydial infections. Clin. Microbiol. Rev. 2:119-136. 3. Cain, A. J., and P. M. Sheppard. 1954. The theory of adaptive polymorphism. Am. Nat. 88:321-326. 4. Casal, M., and M. J. Linares. 1983. Preliminary investigation of Candida albicans biovars. J. Clin. Microbiol. 18:430-431. 5. Do Carmo-Sousa, L. 1969. Distribution of yeasts in nature, p. 79-105. In A. H. Rose and J. S. Harrison (ed.), The yeasts, vol. 1. Academic Press, Inc. (London), Ltd., London. 6. Guibourdenche, M., M. Y. Popoff, and J. Y. Riou. 1986. Deoxyribonucleic acid relatedness among Neisseria gonorrhoeae, N. meningitidis, N. lactamica, N. cinerea and N. polysaccharea. Ann. Inst. Pasteur Microbiol. 137B:177-185. 7. Hunter, P. R., and C. A. M. Fraser. 1989. Application of a numerical index of discriminatory power to a comparison of four physiochemical typing methods for Candida albicans. J. Clin. Microbiol. 27:2156-2160. 8. Kuijper, E. J., A. G. Steigerwalt, B. S. C. I. M. Schoenmakers, M. F. Peeters, H. C. Zanen, and D. J. Brenner. 1989. Phenotypic characterization and DNA relatedness in human fecal isolates of Aeromonas spp. J. Clin. Microbiol. 27:132-138. 9. Kwon-Chung, K. J., A. K. Varma, and D. H. Howard. 1988. Ecology and epidemiology of Cryptococcus neoformans: a study of recent isolates in the United States, p. 107-112. In J. M. Torres-Rodriguez (ed.), Proceedings of the X Congress of the International Society of Human and Animal Mycology-ISHAM. J. R. Prous S.A., Barcelona, Spain. 10. Musser, J. M., E. L. Hewlett, M. S. Peppler, and R. K. Selander. 1986. Genetic diversity and relationships in populations of Bordetella spp. J. Bacteriol. 166:230-237. 11. Ochman, H., T. S. Whittam, D. A. Caugant, and R. K. Selander. 1983. Enzyme polymorphism and genetic population structure in Escherichia coli and Shigella. J. Gen. Microbiol. 129:27152726. 12. Odds, F. C. 1988. Candida and candidosis. Bailliere Tindall, London. 13. Penner, J. L. 1988. The genus Campylobacter: a decade of progress. Clin. Microbiol. Rev. 1:157-172. 14. Roughgarden, J. 1979. Theory of population genetics and evolutionary ecology: an introduction. Macmillan Publishing Co., Inc., New York. 15. Schoener, T. W. 1974. Resource partitioning in ecological communities. Science 185:27-39. 16. Schultz, B. 1983. On Levene's test and other statistics of variation. Evol. Theory 6:197-203. 17. Selander, R. K., R. M. McKinney, T. S. Whittam, W. F. Bibb, D. J. Brenner, F. S. Nolte, and P. E. Pattison. 1985. Genetic structure of populations of Legionella pneumophila. J. Bacteriol. 163:1021-1037. 18. Selander, R. K., M. H. Smith, S. Y. Yang, W. E. Johnson, and J. B. Gentry. 1971. Biochemical polymorphism and systematics in the genus Peromyscus. I. Variation in the old-field mouse. Univ. Tex. Publ. Stud. Genet. 6:49-90. 19. Smith, J. M. 1989. Evolutionary genetics, p. 14-28. Oxford University Press, Oxford. 20. Tsukamura, M. 1966. Adansonian classification of mycobacteria. J. Gen. Microbiol. 45:253-257. 21. Van Valen, L. 1965. Morphological variation and width of ecological niche. Am. Nat. 99:377-390. 22. Van Valen, L. 1978. The statistics of variation. Evol. Theory 4:33-43.
