Favere, J., Buysschaert, B., Boon, N. & De Gusseme, B. Online microbial fingerprinting for quality management of drinking water: full-scale event detection. Water Res. 170, 115353 (2020).
Potgieter, S. C., Pinto, A. J., Havenga, M., Sigudu, M. & Venter, S. N. Reproducible microbial community dynamics of two drinking water systems treating similar source waters. Preprint at https://www.biorxiv.org/content/10.1101/678920v1 (2019).
van Der Kooij, D. Biological stability: a multidimensional quality aspect of treated water. Water Air Soil Poll. 123, 25–34 (2000).
Prest, E. I. et al. Biological stability of drinking water: controlling factors, methods, and challenges. Front. Microbiol. 7, 45–45 (2016).
van der Kooij, D., Vrouwenvelder, H. S. & Veenendaal, H. R. Kinetic aspects of biofilm formation on surfaces exposed to drinking water. Water Sci. Technol. 32, 61–65 (1995).
van Lieverloo, J. H. M., Hoogenboezem, W., Veenendaal, G. & van der Kooij, D. Variability of invertebrate abundance in drinking water distribution systems in the Netherlands in relation to biostability and sediment volumes. Water Res. 46, 4918–4932 (2012).
LeChevallier, M. W., Welch, N. J. & Smith, D. B. Full-scale studies of factors related to coliform regrowth in drinking water. Appl. Environ. Microb. 62, 2201–2211 (1996).
Vital, M., Hammes, F. & Egli, T. Escherichia coli O157 can grow in natural freshwater at low carbon concentrations. Environ. Microbiol. 10, 2387–2396 (2008).
Pavlov, D., de Wet, C. M. E., Grabow, W. O. K. & Ehlers, M. M. Potentially pathogenic features of heterotrophic plate count bacteria isolated from treated and untreated drinking water. Int. J. Food Microbiol. 92, 275–287 (2004).
Kotlarz, N. et al. Retrospective analysis of nontuberculous mycobacterial infection and monochloramine disinfection of municipal drinking water in Michigan. mSphere 4, e00160–19 (2019).
van der Kooij, D., Bakker, G. L., Italiaander, R., Veenendaal, H. R. & Wullings, B. A. Biofilm composition and threshold concentration for growth of Legionella pneumophila on surfaces exposed to flowing warm tap water without disinfectant. Appl. Environ. Microb. 83, e02737–16 (2017).
Liu, S. et al. Understanding, monitoring, and controlling biofilm growth in drinking water distribution systems. Environ. Sci. Technol. 50, 8954–8976 (2016).
van der Wielen, P. W. J. J. & van der Kooij, D. Effect of water composition, distance and season on the adenosine triphosphate concentration in unchlorinated drinking water in the Netherlands. Water Res. 44, 4860–4867 (2010).
Potgieter, S. et al. Long-term spatial and temporal microbial community dynamics in a large-scale drinking water distribution system with multiple disinfectant regimes. Water Res. 139, 406–419 (2018).
Zhang, Y. & Liu, W.-T. The application of molecular tools to study the drinking water microbiome–Current understanding and future needs. Crit. Rev. Env. Sci. Tec. 49, 1188–1235 (2019).
Chowdhury, S. Heterotrophic bacteria in drinking water distribution system: a review. Environ. Monit. Assess. 184, 6087–6137 (2012).
van der Kooij, D., Visser, A. & Hijnen, W. A. M. Determining the concentration of easily assimilable organic-carbon in drinking-water. J. Am. Water Works Ass. 74, 540–545 (1982).
Escobar, I. C. & Randall, A. A. Sample storage impact on the assimilable organic carbon (AOC) bioassay. Water Res. 34, 1680–1686 (2000).
Cheswick, R. et al. Comparing flow cytometry with culture-based methods for microbial monitoring and as a diagnostic tool for assessing drinking water treatment processes. Environ. Int. 130, 104893 (2019).
Bartram, J., Cotruvo, J., Exner, M., Fricker, C. & Glasmacher, A. Heterotrophic plate count measurement in drinking water safety management – Report of an Expert Meeting Geneva, 24–25 April 2002. Int. J. Food Microbiol. 92, 241–247 (2004).
Horn, S., Pieters, R. & Bezuidenhout, C. Pathogenic features of heterotrophic plate count bacteria from drinking-water boreholes. J. Water Health 14, 890–900 (2016).
van Nevel, S. et al. Flow cytometric bacterial cell counts challenge conventional heterotrophic plate counts for routine microbiological drinking water monitoring. Water Res. 113, 191–206 (2017).
Højris, B., Christensen, S. C. B., Albrechtsen, H.-J., Smith, C. & Dahlqvist, M. A novel, optical, on-line bacteria sensor for monitoring drinking water quality. Sci. Rep. 6, 23935 (2016).
Banna, M. H. et al. Online drinking water quality monitoring: review on available and emerging technologies. Crit. Rev. Environ. Sci. Technol. 44, 1370–1421 (2014).
Ivnitski, D., Abdel-Hamid, I., Atanasov, P. & Wilkins, E. Biosensors for detection of pathogenic bacteria. Biosens. Bioelectron. 14, 599–624 (1999).
Gruden, C., Skerlos, S. & Adriaens, P. Flow cytometry for microbial sensing in environmental sustainability applications: current status and future prospects. FEMS Microbiol. Ecol. 49, 37–49 (2004).
Rajapaksha, P. et al. A review of methods for the detection of pathogenic microorganisms. Analyst 144, 396–411 (2019).
LeChevallier, M. W. et al. Development of a rapid assimilable organic-carbon method for water. Appl. Environ. Microbiol. 59, 1526–1531 (1993).
van der Kooij, D. et al. Assessment of the microbial growth potential of slow sand filtrate with the biomass production potential test in comparison with the assimilable organic carbon method. Water Res. 125, 270–279 (2017).
de Vera, G. A. & Wert, E. C. Using discrete and online ATP measurements to evaluate regrowth potential following ozonation and (non)biological drinking water treatment. Water Res. 154, 377–386 (2019).
Hammes, F. A. & Egli, T. New method for assimilable organic carbon determination using flow-cytometric enumeration and a natural microbial consortium as inoculum. Environ. Sci. Technol. 39, 3289–3294 (2005).
Gillespie, S. et al. Assessing microbiological water quality in drinking water distribution systems with disinfectant residual using flow cytometry. Water Res. 65, 224–234 (2014).
Farhat, N. et al. A uniform bacterial growth potential assay for different water types. Water Res. 142, 227–235 (2018).
Hammes, F. et al. Development and laboratory-scale testing of a fully automated online flow cytometer for drinking water analysis. Cytom. A. 81A, 508–516 (2012).
Buysschaert, B., Vermijs, L., Naka, A., Boon, N. & De Gusseme, B. Online flow cytometric monitoring of microbial water quality in a full-scale water treatment plant. npj Clean. Water 1, 16 (2018).
Besmer, M. D. et al. The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems. Front. Microbiol 5, 265 (2014).
Vives-Rego, J., Lebaron, P. & Nebe-von Caron, G. Current and future applications of flow cytometry in aquatic microbiology. FEMS Microbiol. Rev. 24, 429–448 (2000).
Besmer, M. D. et al. Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment. Sci. Rep. 6, 38462 (2016).
Besmer, M. D. & Hammes, F. Short-term microbial dynamics in a drinking water plant treating groundwater with occasional high microbial loads. Water Res. 107, 11–18 (2016).
Page, R. M. et al. Online analysis: deeper insights into water quality dynamics in spring water. Sci. Total Environ. 599–600, 227–236 (2017).
Buysschaert, B., Kerckhof, F. M., Vandamme, P., Baets, B. D. & Boon, N. Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization. Cytom. A 93, 201–212 (2018).
Koch, C., Harnisch, F., Schröder, U. & Müller, S. Cytometric fingerprints: evaluation of new tools for analyzing microbial community dynamics. Front. Microbiol. 5, 273 (2014).
Koch, C., Harms, H. & Müller, S. Dynamics in the microbial cytome—single cell analytics in natural systems. Curr. Opin. Biotechnol. 27, 134–141 (2014).
Props, R., Monsieurs, P., Mysara, M., Clement, L. & Boon, N. Measuring the biodiversity of microbial communities by flow cytometry. Methods Ecol. Evol. 7, 1376–1385 (2016).
Wang, Y., Hammes, F., Boon, N., Chami, M. & Egli, T. Isolation and characterization of low nucleic acid (LNA)-content bacteria. ISME J. 3, 889–902 (2009).
van Nevel, S. et al. Routine bacterial analysis with automated flow cytometry. J. Microbiol. Meth. 94, 73–76 (2013).
Schleich, C. et al. Mapping dynamics of bacterial communities in a full-scale drinking water distribution system using flow cytometry. Water 11, 2137 (2019).
Zhang, Z. et al. Effect of pipe corrosion scales on chlorine dioxide consumption in drinking water distribution systems. Water Res. 42, 129–136 (2008).
Al-Jasser, A. O. Chlorine decay in drinking-water transmission and distribution systems: pipe service age effect. Water Res. 41, 387–396 (2007).
Hallam, N. B. et al. The decay of chlorine associated with the pipe wall in water distribution systems. Water Res. 36, 3479–3488 (2002).
Fish, K. E. & Boxall, J. B. Biofilm microbiome (re)growth dynamics in drinking water distribution systems are impacted by chlorine concentration. Front. Microbiol. 9, 2519 (2018).
Proctor, C. R. et al. Phylogenetic clustering of small low nucleic acid-content bacteria across diverse freshwater ecosystems. ISME J. 12, 1344–1359 (2018).
Ramseier, M. K., von Gunten, U., Freihofer, P. & Hammes, F. Kinetics of membrane damage to high (HNA) and low (LNA) nucleic acid bacterial clusters in drinking water by ozone, chlorine, chlorine dioxide, monochloramine, ferrate (VI), and permanganate. Water Res. 45, 1490–1500 (2011).
Koch, C. et al. CHIC—an automated approach for the detection of dynamic variations in complex microbial communities. Cytom. A. 83A, 561–567 (2013).
Schumann, J. et al. flowCHIC: analyze flow cytometric data using histogram information. R package version 1.18.0 (2019).
Bertelli, C. et al. Reduced chlorine in drinking water distribution systems impacts bacterial biodiversity in biofilms. Front. Microbiol. 9, 2520–2520 (2018).
Keserue, H.-A., Füchslin, H. P. & Egli, T. Rapid detection and enumeration of Giardia lamblia cysts in water samples by immunomagnetic separation and flow cytometric analysis. Appl. Environ. Microbiol. 77, 5420–5427 (2011).
Wolf-Baca, M. & Siedlecka, A. Detection of pathogenic bacteria in hot tap water using the qPCR method: preliminary research. SN Appl. Sci. 1, 840 (2019).
Kim, L. H., Yu, H.-W., Kim, Y.-H., Kim, I. S. & Jang, A. Potential of fluorophore labeled aptamers for Pseudomonas aeruginosa detection in drinking water. J. Korean Soc. Appl. Biol. Chem. 56, 165–171 (2013).
Shin, H.-S., Gedi, V., Kim, J.-K. & Lee, D.-K. Detection of Gram-negative bacterial outer membrane vesicles using DNA aptamers. Sci. Rep. 9, 13167 (2019).
World Health Organization, Guidelines for Drinking-water Quality: Fourth Edition Incorporating the First Addendum (2017).
Rice, E. W., Baird, R. B. & Eaton, A. D. In Standard Methods for the Examination of Water and Wastewater (eds Rice, E. W., Baird, R. W. & Eaton, A. D.) (American Water Works Association/American Public Works Association/Water Environment Federation, 2017).
Noble, R. T., Leecaster, M. K., McGee, C. D., Weisberg, S. B. & Ritter, K. Comparison of bacterial indicator analysis methods in stormwater-affected coastal waters. Water Res. 38, 1183–1188 (2004).
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