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      Near real-time enumeration of live and dead bacteria using a fibre-based spectroscopic device

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          Abstract

          A rapid, cost-effective and easy method that allows on-site determination of the concentration of live and dead bacterial cells using a fibre-based spectroscopic device (the optrode system) is proposed and demonstrated. Identification of live and dead bacteria was achieved by using the commercially available dyes SYTO 9 and propidium iodide, and fluorescence spectra were measured by the optrode. Three spectral processing methods were evaluated for their effectiveness in predicting the original bacterial concentration in the samples: principal components regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR). Without any sample pre-concentration, PCR achieved the most reliable results. It was able to quantify live bacteria from 10 8 down to 10 6.2 bacteria/mL and showed the potential to detect as low as 10 5.7 bacteria/mL. Meanwhile, enumeration of dead bacteria using PCR was achieved between 10 8 and 10 7 bacteria/mL. The general procedures described in this article can be applied or modified for the enumeration of bacteria within populations stained with fluorescent dyes. The optrode is a promising device for the enumeration of live and dead bacterial populations particularly where rapid, on-site measurement and analysis is required.

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            Standard deviations and standard errors.

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              Flow-cytometric total bacterial cell counts as a descriptive microbiological parameter for drinking water treatment processes.

              There are significantly more microbial cells in drinking water than what can be cultured on synthetic growth media. Nonetheless, cultivation-based heterotrophic plate counts (HPCs) are used worldwide as a general microbial quality parameter in drinking water treatment and distribution. Total bacterial cell concentrations are normally not considered during drinking water treatment as a design, operative or legislative parameters. This is mainly because easy and rapid methods for quantification of total bacterial cell concentrations have, up to now, not been available. As a consequence, the existing lack of data does not allow demonstrating the practical value of this parameter. In this study, we have used fluorescence staining of microbial cells with the nucleic acid stain SYBR((R)) Green I together with quantitative flow cytometry (FCM) to analyse total cell concentrations in water samples from a drinking water pilot plant. The plant treats surface water (Lake Zürich) through sequential ozonation, granular active carbon (GAC) filtration and membrane ultrafiltration (UF). The data were compared with adenosine tri-phosphate (ATP) measurements and conventional HPCs performed on the same water samples. We demonstrated that the impact of all three major treatment steps on the microbiology in the system could accurately be described with total cell counting: (1) ozonation caused chemical destruction of the bacterial cells; (2) GAC filtration facilitated significant regrowth of the microbial community; and (3) membrane UF physically removed the bacterial cells from the water. FCM typically detected 1-2 log units more than HPC, while ATP measurements were prone to interference from extracellular ATP released during the ozonation step in the treatment train. We have shown that total cell concentration measured with FCM is a rapid, easy, sensitive and importantly, a descriptive parameter of several widely applied drinking water treatment processes.
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                Author and article information

                Contributors
                fou521@aucklanduni.ac.nz
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 March 2019
                18 March 2019
                2019
                : 9
                : 4807
                Affiliations
                [1 ]ISNI 0000 0004 0372 3343, GRID grid.9654.e, Department of Physics, , The University of Auckland, ; Auckland, New Zealand
                [2 ]The Dodd-Walls Centre for Photonic and Quantum Technologies, Auckland, New Zealand
                [3 ]ISNI 0000 0004 0372 3343, GRID grid.9654.e, School of Medical Sciences, , The University of Auckland, ; Auckland, New Zealand
                Author information
                http://orcid.org/0000-0002-5037-0857
                http://orcid.org/0000-0003-3187-9743
                http://orcid.org/0000-0001-9653-6907
                Article
                41221
                10.1038/s41598-019-41221-1
                6423134
                30886183
                c0fdbac7-80e5-4267-99c9-dffb202940c7
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 September 2018
                : 28 February 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003524, Ministry of Business, Innovation and Employment (MBIE);
                Award ID: UOAX1411
                Award ID: UOAX1411
                Award ID: UOAX1411
                Award ID: UOAX1411
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