Online microbial monitoring of drinking water: How do different techniques respond to contaminations in practice?

Safeguarding the microbial water quality remains a challenge for drinking water utilities, and because of population growth and climate change, new issues arise regularly. To overcome these problems, biostable drinking water production and water reuse will become increasingly important. In this respect, high-resolution online microbial monitoring during treatment and distribution could prove essential. Here, we present the first scientific and practical comparison of multiple online microbial monitoring techniques in which six commercially available devices were set up in a full-scale drinking water production plant. Both the devices' response towards operational changes and contaminations, as well as their detection limit for different contaminations were evaluated and compared. During normal operation, all devices were able to detect abrupt operational changes such as backwashing of activated carbon filters and interruption of the production process in a fast and sensitive way. To benchmark their response to contaminations, the calculation of a dynamic baseline for sensitive separation between noise and events is proposed. In order of sensitivity, enzymatic analysis, ATP measurement, and flow cytometric fingerprinting were the most performant for detection of rain- and groundwater contaminations (0.01 - 0.1 v%). On the other hand, optical classification and flow cytometric cell counts showed to be more robust techniques, requiring less maintenance and providing direct information about the cell concentration, even though they were still more sensitive than plate counting. The choice for a certain technology will thus depend on the type of application and is a balance between sensitivity, price and maintenance. All things considered, a combination of several devices and use of advanced data analysis such as fingerprinting may be of added value. In general, the strategic implementation of online microbial monitoring as early-warning system will allow for intensive quality control by high-frequency sampling as well as a short event response timeframe.

Mildly acidic pH selects for chain elongation to caproic acid over alternative pathways during lactic acid fermentation.

Carbohydrate-rich waste streams can be used for bioproduction of medium-chain carboxylic acids (MCCA) such as caproic acid. The carbohydrates in these streams can be converted to lactic acid as the initial fermentation product, which can then be fermented to MCCA by chain elongation. In this process, chain elongators compete for lactic acid with other bacterial groups that, for instance, ferment lactic acid to propionic and acetic acid. Understanding the drivers that control the competition between these two pathways is essential to maximizing MCCA production. This study aimed to investigate the competition between chain elongating and propionic acid producing organisms as a function of operational pH. Operation of long-term lactic acid fermenting reactors with varying pH values showed that pH values above 6 resulted in a propionic acid producing community dominated by Veillonella and Aminobacterium. At pH values below 6, the community moved towards chain elongation, with communities dominated by Caproiciproducens. Short-term incubations showed that rates of lactic acid consumption were strongly reduced at pH below 6 (7.7 ± 1.2 mM lactic acid·h-1 at pH 6.5; 0.74 ± 0.33 mM lactic acid·h-1 at pH 5.5). Similar to observations in long-term reactors, when a chain elongating community adapted to pH 5.5 was used for short-term incubations at pH 6.5, propionic acid was the dominant product. The results of this study show that pH below 6 stimulate lactic acid chain elongators through kinetic effects, and potentially improved energetics, providing a tool for microbial management of MCCA-producing systems.

Online microbial fingerprinting for quality management of drinking water: Full-scale event detection.

Microbial regrowth during drinking water distribution can result in a variety of problems such as a deviating taste and odor, and may even pose a risk to public health. Frequent monitoring is essential to anticipate events of biological instability, and relevant microbial parameters for operational control of biostability of drinking water should be developed. Here, online flow cytometry and derived biological metrics were used to assess the biological stability of a full-scale drinking water tower during normal and disturbed flow regime. Pronounced operational events, such as switching from drinking water source, and seasonal changes, were detected in the total cell counts, and regrowth was observed despite the short hydraulic residence time of 6-8 h. Based on the flow cytometric fingerprints, the Bray-Curtis dissimilarity was calculated and was developed as unambiguous parameter to indicate or warn for changing microbial drinking water quality during operational events. In the studied water tower, drastic microbial water quality changes were reflected in the Bray-Curtis dissimilarity, which demonstrates its use as an indicator to follow-up and detect microbial quality changes in practice. Hence, the Bray-Curtis dissimilarity can be used in an online setup as a straightforward parameter during full-scale operation of drinking water distribution, and combined with the cell concentration, it serves as an early-warning system for biological instability.