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Pure (single) cultures of microorganisms and mixed microbial communities (microbiomes) have been important for centuries in providing renewable energy, clean water and food products to human society and will continue to play a crucial role to pursue the Sustainable Development Goals. To use microorganisms effectively, microbial engineered processes require adequate control. Microbial communities are shaped by manageable deterministic processes, but also by stochastic processes, which can promote unforeseeable variations and adaptations. Here, we highlight the impact of stochasticity in single culture and microbiome engineering. First, we discuss the concepts and mechanisms of stochasticity in relation to microbial ecology of single cultures and microbiomes. Second, we discuss the consequences of stochasticity in relation to process performance and human health, which are reflected in key disadvantages and important opportunities. Third, we propose a suitable decision tool to deal with stochasticity in which monitoring of stochasticity and setting the boundaries of stochasticity by regulators are central aspects. Stochasticity may give rise to some risks, such as the presence of pathogens in microbiomes. We argue here that by taking the necessary precautions and through clever monitoring and interpretation, these risks can be mitigated.

Novel application of bio-Pd NPs

Over time, humanity has addressed microbial water contamination in various ways. Historically, individuals resorted to producing beer to combat the issue. Fast forward to the 19th century, and we witnessed a scientific approach by Robert Koch. His groundbreaking gelatine plating method aimed to identify and quantify bacteria, with a proposed limit of 100 colony‐forming units per millilitre (CFU/mL) to avoid Cholera outbreaks. Despite considerable advancements in plating techniques through experimentation with media compositions and growth temperatures, the reliance on a century‐old method for water safety remains the state‐of‐the‐art. Even though most countries succeed in producing qualitative water at the end of the production centres, it is difficult to control, and guarantee, the same quality during distribution. Rather than focusing solely on specific sampling points, we propose a holistic examination of the entire water network to ensure comprehensive safety. Current practices leave room for uncertainties, especially given the low concentrations of pathogens. Innovative methods like flow cytometry and flow cytometric fingerprinting offer the ability to detect changes in the microbiome of drinking water. Additionally, molecular techniques and emerging sequencing technologies, such as third‐generation sequencing (MinION), mark a significant leap forward, enhancing detection limits and emphasizing the identification of unwanted genes rather than the unwanted bacteria/microorganisms itself. Over the last decades, there has been the realization that the drinking water distribution networks are complex ecosystems that, beside bacteria, comprise of viruses, protozoans and even isopods. Sequencing techniques to find eukaryotic DNA are necessary to monitor the entire microbiome of the drinking water distribution network. Or will artificial intelligence, big data and machine learning prove to be the way to go for (microbial) drinking water monitoring? In essence, it is time to transcend century‐old practices and embrace modern technologies to ensure the safety of our drinking water from production to consumption. [ABSTRACT FROM AUTHOR]

As an alternative to the usage of axenic bacteria to achieve microbially induced calcium carbonate precipitation (MICP), this study evaluates the usage of two non-axenic biomasses as self-healing agents. A fungi-based consortium (Yeast) and heterotrophic nitrifiers (HTN) were harvested from the incubation of agricultural side streams. The characteristics of the two biomasses were identified through flow cytometry, total suspended solids and volatile suspended solids tests. The incorporation of the biomasses into concrete was evaluated in terms of compressive strength, flow and healing ability. Self-healing ability was analyzed through microscope imaging on prismatic (60x60x220 mm) samples. Cracks were induced with a three-point bending test where the widths were controlled with an LVDT sensor. A curing period of 56 days was applied to the samples and visual inspection was conducted at the start and end of the healing period with an optical microscope. Results compare and discuss the differing effects of active and autoclaved biomasses on the concrete properties and crack closure.

The capacity of hydrated lime to reabsorb CO2 as it hardens has made it a desirable replacement for cement to produce mortars with an overall lower environmental footprint. Still, research into lime-cement formulations remains limited, especially when it comes to their self-healing capacity. Some studies show that hydrated lime can improve self-healing in cement mixes, but addition rates are low. Here we present how high lime-cement ratios influence the self-healing capacity of lime mortars. Four mixes of increasing lime-cement ratios were cracked with tensile loading and placed under 1 hour wet, 23 hours dry cycles to stimulate self-healing. The mix design of 50 % lime-50 % cement volume (L50C50) showed self-healing abilities and was tested against a pure cement mixture (L0C100). Microscopy and water flow tests were performed at a cracking age of 7 days and then again after 28 days of healing in three regimes. Overall, submersion was the best healing regime for both L0C100 and L50C50 and crack self-healing was close to total (100 ± 1 % and 98 ± 6 %, respectively). Nevertheless, the water flow tests show that self-healing in L50C50 was in fact less efficient than that of the L0C100, achieving a 39 ± 21 % reduction in water flow versus 86 ± 11 %.

Methane-producing Archaea can be found in a variety of habitats, including the gastrointestinal tract, where they are linked to various diseases. The majority of current monitoring methods can be slow and laborious. To facilitate gut methanogenic Archaea detection, we investigated flow cytometry for rapid quantification based on the autofluorescent F420 cofactor, an essential coenzyme in methanogenesis. The methanogenic population was distinguishable from the SYBR green (SG) and SYBR green/propidium iodide (SGPI) stained background microbiome based on elevated 452 nm emission in Methanobrevibacter smithii spiked controls. As a proof-of-concept, elevated F420-autofluorescence was used to detect and quantify methanogens in 10 faecal samples and 241 in vitro incubated faecal samples. The methanogenic population in faeces, determined through Archaea-specific 16S rRNA gene amplicon sequencing, consisted of Methanobrevibacter and Methanomassiliicoccus. F420-based methanogen quantification in SG and SGPI-stained faecal samples showed an accuracy of 90 and 100% against Archaea proportions determined with universal primers. When compared to methane and Archaea presence, methanogen categorisation in in vitro incubated faeces exhibited an accuracy of 71 and 75%, with a precision of 42 and 70%, respectively. To conclude, flow cytometry is a reproducible and fast method for the detection and quantification of gut methanogenic Archaea. [ABSTRACT FROM AUTHOR]