Molecular identification of potential pathogens in water and air of a hospital therapy pool

Abstract

Indoor warm-water therapy pool workers in a Midwestern regional hospital were diagnosed with non-tuberculosis pulmonary hypersensitive pneumonitis and Mycobacterium avium infections. In response, we conducted a multiseason survey of microorganisms present in this therapy pool water, in biofilms associated with the pool containment walls, and in air immediately above the pool. The survey used culture, microscopy, and culture-independent molecular phylogenetic analyses. Although outfitted with a state-of-the-art UV-peroxide disinfection system, the numbers of bacteria in the therapy pool water were relatively high compared with the potable water used to fill the pool. Regardless of the source, direct microscopic counts of microbes were routinely approximately 1,000 times greater than conventional plate counts. Analysis of clone libraries of small subunit rRNA genes from environmental DNA provided phylogenetic diversity estimates of the microorganisms collected in and above the pool. A survey of >1,300 rRNA genes yielded a total of 628 unique sequences, the most common of which was nearly identical to that of M. avium strains. The high proportion of clones with different Mycobacterium spp. rRNA genes suggested that such organisms comprised a significant fraction of microbes in the pool water (to >30%) and preferentially partition into aerosols (to >80%) relative to other waterborne bacteria present. The results of the study strongly validate aerosol partitioning as a mechanism for disease transfer in these environments. The results also show that culture protocols currently used by public health facilities and agencies are seriously inadequate for the detection and enumeration of potential pathogens.

Fig. 1.

Phylogenetic distribution of pool environment bacterial rRNA genes. Clone sequences were grouped phylogenetically to accompany the text discussion, and percentages of sequences associated with the indicated groups are shown as pie charts. (A) Pool air, February. (B) Pool water, February. (C) Sand filter, December. (D) Pool air, August. (E) Outside air, August. (F) Pool water and side biofilm, August. Mycobacteria, Mycobacterium spp.; Actinob, Actinobacteria; other Actinob, Actinobacteria excluding mycobacteria; Sphingom, Sphingomonadaceae; α-Proteobact, α-proteobacteria; other α-Proteobact, α-proteobacteria excluding Sphingomonadaceae; β-Proteobact, β-proteobacteria; γ-Proteobact, γ-proteobacteria; δ-Proteobact, δ-proteobacteria; Cyanobact, Cyanobacteria; Bcl/Cls-grp, Bacillus/Clostridium group; Bct/Chl-grp, Bacteroidetes/Chlorobi group; other bacteria, bacteria not included in other groups.

Fig. 2.

Phylogenetic relationships of pool environment Mycobacterium spp. Shown are 16S rRNA gene sequences relative to cultured “slow-growing” (A) and “fast-growing” (B) mycobacteria. The analyses were based on an alignment of 890 nucleotide positions. Maximum likelihood, MP, and NJ algorithms resulted in identical results for the relationships supported by bootstrap analyses. NJ phylograms are shown to illustrate the phylogenetic results. Circles signify bootstrap support for nodes, with filled circles indicating MP and NJ boostrap support >70% and open circles indicating support >50%. Clones with prefixes MB and MC were obtained from the February 2001 and August 2001 sampling events, respectively. All mycobacterial clones were processed from pool air except for six clones that were processed from the pool water and sides sample (MC042310; MC0424c5; MC0424c7; MC0424c9; MC042411; and MC0508c9).