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Journal of Clinical Microbiology, November 2008, p. 3822-3825, Vol. 46, No. 11
0095-1137/08/$08.00+0 doi:10.1128/JCM.00451-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.
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Universidade Federal do Rio de Janeiro, Centro de Ciências da Saúde, Instituto de Microbiologia Professor Paulo de Góes, Rio de Janeiro, Brazil,1 Pontifícia Universidade Católica do Rio Grande do Sul, Faculdade de Biociências, Laboratório de Biologia Genômica e Molecular Porto Alegre, Brazil,2 Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de Biologia Molecular Aplicada a Micobactérias, Rio de Janeiro, Brazil3
Received 6 March 2008/ Returned for modification 21 March 2008/ Accepted 19 August 2008
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The clinical isolates used in this study were provided by the Laboratory of Mycobacteria, Federal University of Rio de Janeiro, and were isolated from different places. Fifty-two isolates were investigated to determine the species (28 clinical isolates and 24 environmental isolates) (Table 1). Isolates were cultured in solid Lowenstein-Jensen medium, and conventional identification procedures were carried out according to the methods of Kent and Kubicae (4). DNA samples were extracted according to the cetyltrimethylammonium bromide protocol of Van Embden and colleagues (17), and PCR assays were performed according to the method of Telenti et al. (15). Samples were purified with MicroSpin S-400 columns (Amersham Biosciences) and a QIAquick PCR purification kit (Qiagen). Sequencing was performed with a DYEnamic ET dye terminator kit (MegaBace; Amersham Biosciences) and read with a MegaBace1000 (Amersham Biosciences) automated system. All chromatograms were checked using the CHROMAS 1.45 program, and the sequences were aligned using Clustal_X 1.83 (16), with manual adjustments using the BioEdit 7.0.9 program. The substitution model used for phylogenetic reconstructions was estimated with Modeltest 3.7 (11), using the minimum theoretical information criterion and the Bayesian information criterion, as suggested by Posada and Buckley (10). Isolates were identified by comparing unknown sequences to reference databases by a FASTA BLAST search (see the supplemental material). Genetic diversity parameters, such as haplotype and nucleotide diversity (6), were estimated employing DnaSP 4.0 software (Table 2). Phylogenetic trees were reconstructed by the maximum likelihood (ML) and neighbor-joining methods, using the program PAUP* 4.0b10 (D. Swofford, Sunderland, MA). The branch confidence values were estimated using 1,000 bootstrap replicates. We inferred ML trees with a heuristic nearest-neighbor interchange search option. The neighbor-joining analysis used the ML distance in the evolutionary model selected by the model test. Nocardia sp. and Corynebacterium sp. were used as outgroup species, and Mycobacterium tuberculosis was used as a more closely related species (Fig. 1).
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TABLE 1. Environmental and clinical strains
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TABLE 2. Genetic diversity parameters
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FIG. 1. Consensus tree for 200 bootstraps showing the phylogenetic relationships among environmental and clinical isolates from several places in the region surrounding Rio de Janeiro, Brazil, and sequences of known mycobacterial species. The tree is based on a comparison of a 368-bp sequence from the mycobacterial hsp65 gene, using the neighbor-joining method. Bootstrap values of >70% are indicated. The distance between two strains is the sum of the branch lengths between them.
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Although water does not represent the only source of M. avium complex in humans, it is possible that it might be the primary source (3). Human activities probably have a great influence on the distribution and prevalence of mycobacteria. The treatment of drinking water supplies with chlorine or other disinfectants (e.g., ozone) leads to selection for environmental mycobacteria (7). This fact could explain why many clinical and environmental species in the present study grouped with M. avium. In this investigation, two clinical isolates grouped with M. scrofulaceum, maybe because of implementation of a clean water method, similar to the one that occurred in the United States in 1975, when increased chlorination rates may have led to a strong reduction of M. scrofulaceum in the water. Additionally, the epidemiology of infection by environmental mycobacteria is poorly understood due to a lack of data regarding the primary reservoirs of different mycobacterial species (5, 12).
A great number of the environmental isolates collected were identified by slow growth and were grouped with clinical isolates. This result could be related to the previously discussed question of adaptive value. There are many situations in which human and mycobacterial distributions can overlap geographically and environmentally, resulting in human exposure and in an impact on mycobacterial ecology. Humans are exposed to mycobacteria in water through drinking, swimming, and bathing. Contamination has been facilitated mainly in hospitals, where patients with reduced immunity are more exposed. Previous studies which correlate environmental parameters with the isolation of environmental mycobacteria were performed with acidic, organic, rich material and stagnant water reservoirs (1). However, we could see that infection by NTM can almost exclusively be associated with environmental mycobacteria that have adapted to humans. Our investigation provides evidence that hsp65 sequencing has the potential of being an accurate, reliable, and effective means for identifying clinical and environmental Mycobacterium isolates. It has the advantages over biochemical test profiles of being rapid and trustworthy. Moreover, the results of sequencing can be used to correlate the specimens between themselves and to give support in their identification.
Our results show that the hsp65 sequences from reference strains of mycobacteria provide a basis for determining systematic phylogenetic relationships. The phylogenetic analysis suggests that slow growth evolved recently in mycobacteria and, as discussed above, possibly has a great adaptive value (9). This study also shows the possibility that species correlate with each other and, moreover, the possible entry ports of mycobacteria in the artificial human environment. With regard to the information about DNA polymorphism obtained with the clinical and environmental isolates individually, we observed that it was greater in clinical than in environmental samples. This could be explained by an adaptation of the environmental species to the artificial human environment, probably through biofilms. It could also help us to understand why so many infections caused by mycobacteria have been reported recently. Currently, it is very important to understand associations between species of mycobacteria in Brazil because infections by these microorganisms have been increasing and causing outbreaks in hospitals, where the port of entry for infection is mainly surgery patients, and are becoming a serious and delicate problem for public health.
We are grateful to Denis Broock Rosemberg and Laura Utz for critical reviews of the manuscript.
Published ahead of print on 3 September 2008. ![]()
Supplemental material for this article may be found at http://jcm.asm.org/. ![]()
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