Capability of mucoid Pseudomonas aeruginosa to survive in chlorinated water

Grobe, Susanne; Wingender, Jost; Flemming, Hans‐Curt

doi:10.1078/1438-4639-00085

Cited by 60 publications

(36 citation statements)

References 8 publications

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“…An upper limit of free chlorine of 0.8 mg/l and an ozone level of 0.02 mg/l is recommended [16]. However, P. aeruginosa is highly adapted to survive in the environment and mucoid P. aeruginosa has been reported to survive water chlorination with free chlorine below 0.57 mg/l [17]. American researchers have recommended a free chlorine residual level of 0.6 mg/l or higher with a pH between 7.2 -7.8 for preventing P. aeruginosa dermatitis [18].…”

Section: Discussionmentioning

confidence: 99%

Pseudomonas aeruginosa in public swimming pools and bathroom water of patients with cystic fibrosis

Barben

Hafen

Schmid

2005

Journal of Cystic Fibrosis

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Section: Discussionmentioning

confidence: 99%

Pseudomonas aeruginosa in public swimming pools and bathroom water of patients with cystic fibrosis

Barben

Hafen

Schmid

2005

Journal of Cystic Fibrosis

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“…In particular, Pseudomonas spp. are recognized as able to form biofilms (36,(42)(43)(44), adhering to surfaces and improving their resistance to sanitation and cleaning procedures (20,45,46).…”

Section: Discussionmentioning

confidence: 99%

Overlap of Spoilage-Associated Microbiota between Meat and the Meat Processing Environment in Small-Scale and Large-Scale Retail Distributions

Stellato

Storia

Filippis

et al. 2016

Appl Environ Microbiol

154

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Microbial contamination in food processing plants can play a fundamental role in food quality and safety. The aims of this study were to learn more about the possible influence of the meat processing environment on initial fresh meat contamination and to investigate the differences between small-scale retail distribution (SD) and large-scale retail distribution (LD) facilities. Samples were collected from butcheries (n ‫؍‬ 20), including LD (n ‫؍‬ 10) and SD (n ‫؍‬ 10) facilities, over two sampling campaigns. Samples included fresh beef and pork cuts and swab samples from the knife, the chopping board, and the butcher's hand. The microbiota of both meat samples and environmental swabs were very complex, including more than 800 operational taxonomic units (OTUs) collapsed at the species level. The 16S rRNA sequencing analysis showed that core microbiota were shared by 80% of the samples and included Pseudomonas spp., Streptococcus spp., Brochothrix spp., Psychrobacter spp., and Acinetobacter spp. Hierarchical clustering of the samples based on the microbiota showed a certain separation between meat and environmental samples, with higher levels of Proteobacteria in meat. In particular, levels of Pseudomonas and several Enterobacteriaceae members were significantly higher in meat samples, while Brochothrix, Staphylococcus, lactic acid bacteria, and Psychrobacter prevailed in environmental swab samples. Consistent clustering was also observed when metabolic activities were considered by predictive metagenomic analysis of the samples. An increase in carbohydrate metabolism was predicted for the environmental swabs and was consistently linked to Firmicutes, while increases in pathways related to amino acid and lipid metabolism were predicted for the meat samples and were positively correlated with Proteobacteria. Our results highlighted the importance of the processing environment in contributing to the initial microbial levels of meat and clearly showed that the type of retail facility (LD or SD) did not apparently affect the contamination. IMPORTANCEThe study provides an in-depth description of the microbiota of meat and meat processing environments. It highlights the importance of the environment as a contamination source of spoilage bacteria, and it shows that the size of the retail facility does not affect the level and type of contamination. Meat is a complex niche with chemical and physical properties that allow the colonization and development of a variety of microorganisms, especially bacteria (1, 2). Several factors can influence the occurrence of microbes in meat. After slaughtering, meat can be contaminated by microorganisms from water, air, and soil, as well as from the workers and equipment involved in the processing. In the later processing steps of the fresh meat chain (i.e., handling, cutting, and storage), abiotic factors such as temperature, gaseous atmosphere, pH, and NaCl levels select for certain bacteria, allowing colonization of the meat surface by different spoilage-related species and...

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“…Activities of microbial growth and the presence of potential opportunistic pathogens have been detected in tap water, faucets, and showerheads, etc., all end points of the DWDS (8,14). Many studies attribute the survival of opportunistic pathogens in DWDS to resistance mechanisms such as cell wall permeability and biofilm formation (9,10). The type of bacterial communities present in a DWDS and the disinfection regime applied may also be factors influencing pathogen retention in the DWDS.…”

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confidence: 99%

Pyrosequencing Analysis of Bacterial Biofilm Communities in Water Meters of a Drinking Water Distribution System

Hong

Hwang

Ling

et al. 2010

Appl Environ Microbiol

173

130

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The applicability of 454 pyrosequencing to characterize bacterial biofilm communities from two water meters of a drinking water distribution system was assessed. Differences in bacterial diversity and composition were observed. A better understanding of the bacterial ecology of drinking water biofilms will allow for effective management of water quality in distribution systems.Drinking water distribution systems (DWDS) are interesting model systems for studies of microbial diversity and ecosystem functions in engineered environments. DWDS biofilms in particular have received much focus due to the importance of potable water delivery to end-point consumers (8). Both cultivation-based and molecular approaches have been used to reveal bacterial communities from different locations or pipe materials within a DWDS and from DWDS that differ in source water and nutrients. Studies of bacterial communities throughout DWDS have indicated that populations can differ drastically from source water to tap water (7). Activities of microbial growth and the presence of potential opportunistic pathogens have been detected in tap water, faucets, and showerheads, etc., all end points of the DWDS (8,14). Many studies attribute the survival of opportunistic pathogens in DWDS to resistance mechanisms such as cell wall permeability and biofilm formation (9, 10). The type of bacterial communities present in a DWDS and the disinfection regime applied may also be factors influencing pathogen retention in the DWDS. Nitrifying microorganisms, for example, can contribute to the depletion of monochloramine and subsequently lead to increased overall microbial growth (7).Compared to the analysis of microbial communities in source water and end-point drinking water, investigations related to the delivery process are difficult due to limited access and the high cost involved in sampling within the DWDS. To overcome these challenges, several studies have used model DWDS to mimic full-scale DWDS so as to address treatment effects on water quality. The researchers in these studies reported that episodic chlorination may accelerate the development of microbial communities with increased resistance to disinfectants (4) and that bacterial diversity can also affect disinfection efficacy and pathogen survival (1). In addition, the occurrence of bacterial community succession was observed in a model DWDS (17), which indicated the importance of longterm monitoring of bacterial biofilm development in the DWDS. These findings also demonstrated the need for the direct study of microbial communities within the DWDS, which would complement studies of the source water and end points, give a more complete view of the microbial ecology of the DWDS, and lend insights for subsequent monitoring of the DWDS.Biofilms obtained from water meters can be a good alternative to those obtained from distribution water pipes to study biofilms in DWDS because the water meters can be obtained relatively easily from private households. Moreover, the biofilms in the water meters no...

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Capability of mucoid Pseudomonas aeruginosa to survive in chlorinated water

Cited by 60 publications

References 8 publications

Pseudomonas aeruginosa in public swimming pools and bathroom water of patients with cystic fibrosis

Pseudomonas aeruginosa in public swimming pools and bathroom water of patients with cystic fibrosis

Overlap of Spoilage-Associated Microbiota between Meat and the Meat Processing Environment in Small-Scale and Large-Scale Retail Distributions

Pyrosequencing Analysis of Bacterial Biofilm Communities in Water Meters of a Drinking Water Distribution System

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