A cross-reactive plasmonic sensing array for drinking water assessment.

The continuous monitoring of remote drinking water purification systems is a global challenge with direct consequences for human and environmental health. Here, we utilise a "nano-tastebud" sensor comprised of eight chemically-tailored plasmonic metasurfaces, for testing the composition of drinking water. Through undertaking a full chemometric analysis of the water samples and likely contaminants we were able to optimise the sensor specification to create an array of suitable tastebuds. By generating a unique set of optical responses for each water sample, we show that the array-based sensor can differentiate between untreated influent and treated effluent water with over 95% accuracy in flow and can detect compositional changes in distributed modified tap water. Once fully developed, this system could be integrated into water treatment facilities and distribution systems to monitor for changes in water composition.

The Role of Chlorine in the Formation and Development of Tap Water Biofilms under Different Flow Regimes.

Water companies make efforts to reduce the risk of microbial contamination in drinking water. A widely used strategy is to introduce chlorine into the drinking water distribution system (DWDS). A subtle potential risk is that non-lethal chlorine residuals may select for chlorine resistant species in the biofilms that reside in DWDS. Here, we quantify the thickness, density, and coverage of naturally occurring multi-species biofilms grown on slides in tap water with and without chlorine, using fluorescence microscopy. We then place the slides in an annular rotating reactor and expose them to fluid-wall shears, which are redolent of those on pipe walls in DWDS. We found that biofilms in chlorine experiment were thicker, denser and with higher coverage than in non-chlorine conditions under all flow regimes and during incubation. This suggests that the formation and development of biofilms was promoted by chlorine. Surprisingly, for both chlorinated and non-chlorinated conditions, biofilm thickness, density and coverage were all positively correlated with shear stress. More differences were detected in biofilms under the different flow regimes in non-chlorine than in chlorine experiments. This suggests a more robust biofilm under chlorine conditions. While this might imply less mobilization of biofilms in high shear events in pipe networks, it might also provide refuge from chlorine residuals for pathogens.

intI1 gene abundance from septic tanks in Thailand using validated intI1 primers.

IMPORTANCE: Antimicrobial resistance is a global crisis, and wastewater treatment, including septic tanks, remains an important source of antimicrobial resistance (AMR) genes. The role of septic tanks in disseminating class 1 integron, and by extension AMR genes, in Thailand, where antibiotic use is unregulated remains understudied. We aimed to monitor gene abundance as a proxy to infer potential AMR from septic tanks in Thailand. We evaluated published intI1 primers due to the lack of consensus on optimal Q-PCR primers and the absence of standardization. Our findings confirmed septic tanks are a source of class 1 integron to the environment. We highlighted the significance of intI1 primer choice, in the context of interpretation of risk associated with AMR spread from septic tanks. We recommend the validated set (F3-R3) for optimal intI1 quantification toward the goal of achieving standardization across studies.

Temporal stability and community assembly mechanisms in healthy broiler cecum.

In recent years, there has been an unprecedented advancement in in situ analytical approaches that contribute to the mechanistic understanding of microbial communities by explicitly incorporating ecology and studying their assembly. In this study, we have analyzed the temporal profiles of the healthy broiler cecal microbiome from day 3 to day 35 to recover the stable and varying components of microbial communities. During this period, the broilers were fed three different diets chronologically, and therefore, we have recovered signature microbial species that dominate during each dietary regime. Since broilers were raised in multiple pens, we have also parameterized these as an environmental condition to explore microbial niches and their overlap. All of these analyses were performed in view of different parameters such as body weight (BW-mean), feed intake (FI), feed conversion ratio (FCR), and age (days) to link them to a subset of microbes that these parameters have a bearing upon. We found that gut microbial communities exhibited strong and statistically significant specificity for several environmental variables. Through regression models, genera that positively/negatively correlate with the bird's age were identified. Some short-chain fatty acids (SCFAs)-producing bacteria, including Izemoplasmatales, Gastranaerophilales, and Roseburia, have a positive correlation with age. Certain pathogens, such as Escherichia-Shigella, Sporomusa, Campylobacter, and Enterococcus, negatively correlated with the bird's age, which indicated a high disease risk in the initial days. Moreover, the majority of pathways involved in amino acid biosynthesis were also positively correlated with the bird's age. Some probiotic genera associated with improved performance included Oscillospirales; UCG-010, Shuttleworthia, Bifidobacterium, and Butyricicoccaceae; UCG-009. In general, predicted antimicrobial resistance genes (piARGs) contributed at a stable level, but there was a slight increase in abundance when the diet was changed. To the best of the authors' knowledge, this is one of the first studies looking at the stability, complexity, and ecology of natural broiler microbiota development in a temporal setting.

Competitive and substrate limited environments drive metabolic heterogeneity for comammox Nitrospira.

Nitrospira has been revealed as a high versatile genus. Although previously considered only responsible for the conversion of nitrite to nitrate, now we know that Nitrospira can perform complete ammonia oxidation to nitrate too (comammox). Comammox activity was firstly reported as dominant in extremely limited oxygen environments, where anaerobic ammonia oxidation was also occurring (anammox). To explain the comammox selection, we developed an Individual-based Model able to describe Nitrospira and anammox growth in suspended flocs assembled in a dynamic nitrogen and oxygen-limiting environment. All known and hypothesized nitrogen transformations of Nitrospira were considered: ammonia and nitrite oxidation, comammox, nitrate-reducing ammonia oxidation, and anaerobic nitrite-reducing ammonia oxidation. Through bioenergetics analysis, the growth yield associated to each activity was estimated. The other kinetic parameters necessary to describe growth were calibrated according to the reported literature values. Our modeling results suggest that even extremely low oxygen concentrations (~1.0 µM) allow for a proportional growth of anammox versus Nitrospira similar to the one experimentally observed. The strong oxygen limitation was followed by a limitation of ammonia and nitrite, because anammox, without strong competitors, were able to grow faster than Nitrospira depleting the environment in nitrogen. These substrate limitations created an extremely competitive environment that proved to be decisive in the community assembly of Nitrospira and anammox. Additionally, a diversity of metabolic activities for Nitrospira was observed in all tested conditions, which in turn, explained the transient nitrite accumulation observed in aerobic environments with higher ammonia availability.

Engineering biology in the face of uncertainty.

Combining engineering and biology surely must be a route to delivering solutions to the world's most pressing problems in depleting resources, energy and the environment. Engineers and biologists have long recognized the power in coupling their disciplines and have evolved a healthy variety of approaches to realizing technologies. Yet recently, there has been a movement to narrow the remit of engineering biology. Its definition as 'the application of engineering principles to the design of biological systems' ought to encompass a broad church. However, the emphasis is firmly on construction '…of novel biological devices and systems from standardized artificial parts' within cells. Thus, engineering biology has become synonymous with synthetic biology, despite the many longstanding technologies that use natural microbial communities. The focus on the nuts and bolts of synthetic organisms may be deflecting attention from the significant challenge of delivering solutions at scale, which cuts across all engineering biology, synthetic and natural. Understanding, let alone controlling, every component of an engineered system is an unrealistic goal. To realize workable solutions in a timely manner we must develop systematic ways of engineering biology in the face of the uncertainties that are inherent in biological systems and that arise through lack of knowledge.

Multiscale models driving hypothesis and theory-based research in microbial ecology.

Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the improvement of current environmental biotechnologies. We propose that a multiscale modelling bottom-up approach (piecing together sub-systems to give rise to more complex systems) can be used as a framework to generate mechanistic hypotheses and theories (in-silico bottom-up methodology). To accomplish this, formal comprehension of the mathematical model design is required together with a systematic procedure for the application of the in-silico bottom-up methodology. Ruling out the belief that experimentation before modelling is indispensable, we propose that mathematical modelling can be used as a tool to direct experimentation by validating theoretical principles of microbial ecology. Our goal is to develop methodologies that effectively integrate experimentation and modelling efforts to achieve superior levels of predictive capacity.

Diversity and metabolic energy in bacteria.

Why are some groups of bacteria more diverse than others? We hypothesize that the metabolic energy available to a bacterial functional group (a biogeochemical group or 'guild') has a role in such a group's taxonomic diversity. We tested this hypothesis by looking at the metacommunity diversity of functional groups in multiple biomes. We observed a positive correlation between estimates of a functional group's diversity and their metabolic energy yield. Moreover, the slope of that relationship was similar in all biomes. These findings could imply the existence of a universal mechanism controlling the diversity of all functional groups in all biomes in the same way. We consider a variety of possible explanations from the classical (environmental variation) to the 'non-Darwinian' (a drift barrier effect). Unfortunately, these explanations are not mutually exclusive, and a deeper understanding of the ultimate cause(s) of bacterial diversity will require us to determine if and how the key parameters in population genetics (effective population size, mutation rate, and selective gradients) vary between functional groups and with environmental conditions: this is a difficult task.

Risk stratification for the detection of metachronous polyps after bowel screening polypectomy: clinical outcomes from the Integrated Technologies for Improved Polyp Surveillance (INCISE) study cohort.

BACKGROUND: After colorectal polypectomy, 20-50 per cent of patients develop metachronous polyps and some have increased colorectal cancer risk. British Society of Gastroenterology (BSG) 2020 guidelines recommend surveillance colonoscopy for high-risk patients based on index pathology. The aim of this study was to evaluate metachronous lesion outcome using BSG 2020 criteria. METHODS: A retrospective, multicentred study was conducted including patients who had polypectomy during screening colonoscopy (2009-2016) followed by surveillance. Demographics, index pathology, and BSG 2020 risk criteria were compared with regard to metachronous lesion pathology (non-advanced versus advanced lesions) and timing of detection (early versus late). Advanced lesions were defined as adenomas/serrated polyps greater than or equal to 10 mm, high-grade dysplasia, serrated polyps with dysplasia, or colorectal cancer, and late lesions those detected greater than 2 years after the index procedure. RESULTS: Of 3090 eligible patients, 2643 were included. Among these, retrospective BSG 2020 application would have excluded 51.5 per cent from surveillance. After a median of 36 months, the advanced polyp/colorectal cancer rate in BSG 2020 high-risk patients was 16.3 versus 13.0 per cent in low-risk patients. Older age (P = 0.008) correlated with advanced metachronous lesions. Male sex, greater than five polyps, and BSG 2020 high-risk criteria correlated with non-advanced and advanced lesions (P < 0.001). Older age (P < 0.001), villous features (P = 0.006), advanced index polyp (P = 0.020), and greater than five polyps (P < 0.001) correlated with early metachronous lesions. Male sex and BSG 2020 high-risk criteria correlated with early and late lesions (P < 0.001). On multivariable regression, increased polyp number (odds ratio (OR) 1.15 (95 per cent c.i. 1.07 to 1.25); P < 0.001) and villous features (OR 1.49 (95 per cent c.i. 1.05 to 2.10); P = 0.025) independently correlated with early advanced lesions. The rate of non-advanced and advanced metachronous polyps was higher in BSG 2020 high- versus low-risk patients (44.4 versus 35.4 per cent for non-advanced and 15.7 versus 11.8 per cent for advanced; P < 0.001), but the colorectal cancer rate was similar (0.6 versus 1.2 per cent). However, when examining only lesions detected greater than 2 years after the index colonoscopy in high- versus low-risk patients, no significant differences were observed (P = 0.140). CONCLUSION: BSG 2020 criteria correlated with metachronous polyps, but did not differentiate advanced and non-advanced lesions and were not predictive of late lesions.

Groundwater recharge estimation using in-situ and GRACE observations in the eastern region of the United Arab Emirates.

The intensive agricultural expansion and rapid urban development in Abu Dhabi Emirate, United Arab Emirates (UAE) have resulted in a major decline in local and regional groundwater levels. By using the latest release (RL06) of Gravity Recovery and Climate Experiment (GRACE) satellite measurements and Global Land Data Assimilation System (GLDAS) products, the groundwater storage change was computed and compared with the time series of in-situ monitoring wells over the period of 2010-2016. The RL06 GRACE products from Jet Propulsion Laboratory (JPL), University of Texas Center for Space Research (CSR), German Research Center for Geosciences (GFZ), and JPL mass concentrations (MASCON) were assessed and have shown satisfactory agreements with the monitoring wells. The JPL MASCON reflected the in-situ groundwater storage change better than the other GRACE products (R = 0.5, lag =1 month, RMSE = 13 mm). The groundwater recharge is estimated for the study area and compared with the in-situ recharge method that considers multi recharge components from the rainfall, irrigation return flow and internal fluxes. The results show that the agreements between in-situ and GRACE-derived recharge estimates are highly agreeable (e.g., R2 = 0.91, RMSE = 1.5 Mm3 to 7.8 Mm3, and Nash-Sutcliff Efficiency = 0.7). Using the Mann-Kendall trend test and Sen's slope, the analyses of policies, number of wells, and farm areal expansion with groundwater time series derived from GRACE helped to validate GRACE and emphasize the importance of regulations for sustainable development of groundwater resources. The impacts of subsidy cuts after 2010 can be captured from the GRACE data in the eastern region of Abu Dhabi Emirate. The linear trend of groundwater storage anomaly obtained from GRACE over the period from 2003 to 2010 is -6.36 ± 0.6 mm/year while it showed a decline trend of -1.2 ± 0.6 mm/year after the subsidy cut. The proposed approach has a potential application for estimating groundwater recharge in other arid regions where in-situ monitoring wells are limited or absent.

Integration of anaerobic digestion with heat Pump: Machine learning-based technical and environmental assessment.

Anaerobic digestion (AD)-based biogas production mitigates the environmental footprint of organic wastes (e.g., food waste and sewage sludge) and facilitates a circular economy. The work proposed an integrated system where the thermal energy demand of an AD is supplied using an air source heat pump (ASHP). The proposed system is compared to a baseline system, where the thermal energy is supplied by a natural gas-based heating system. Several machine learning models are developed for predicting biogas production, among which the Gaussian Process Regression (GPR) showed a superior performance (R2 = 0.84 and RMSE = 0.0755 L gVS-1 day-1). The GPR model further informed a thermodynamic model of the ASHP, which revealed the maximum biogas yield to be approximately 0.585 L.gVS-1.day-1 at an optimal temperature of 55 °C (thermophilic). Subsequently, life cycle assessment showed that ASHP-based AD heating systems achieved 28.1 % (thermophilic) and 36.8 % (mesophilic) carbon abatement than the baseline system.

Environmental and ecological controls of the spatial distribution of microbial populations in aggregates.

In microbial communities, the ecological interactions between species of different populations are responsible for the spatial distributions observed in aggregates (granules, biofilms or flocs). To explore the underlying mechanisms that control these processes, we have developed a mathematical modelling framework able to describe, label and quantify defined spatial structures that arise from microbial and environmental interactions in communities. An artificial system of three populations collaborating or competing in an aggregate is simulated using individual-based modelling under different environmental conditions. In this study, neutralism, competition, commensalism and concurrence of commensalism and competition have been considered. We were able to identify interspecific segregation of communities that appears in competitive environments (columned stratification), and a layered distribution of populations that emerges in commensal (layered stratification). When different ecological interactions were considered in the same aggregate, the resultant spatial distribution was identified as the one controlled by the most limiting substrate. A theoretical modulus was defined, with which we were able to quantify the effect of environmental conditions and ecological interactions to predict the most probable spatial distribution. The specific microbial patterns observed in our results allowed us to identify the optimal spatial organizations for bacteria to thrive when building a microbial community and how this permitted co-existence of populations at different growth rates. Our model reveals that although ecological relationships between different species dictate the distribution of bacteria, the environment controls the final spatial distribution of the community.

Interpretable machine learning to model biomass and waste gasification.

Machine learning has been regarded as a promising method to better model thermochemical processes such as gasification. However, their black box nature can limit how much one can trust and learn from the developed models. Here seven different machine learning methods have been adopted to model the gasification of biomass and waste across a wide range of operating conditions. Gradient boosting regression has been found to outperform the other model types with a coefficient of determination (R2) of 0.90 when averaged across ten key gasification outputs. Global and local model interpretability methods have been used to illuminate the developed black box models. The studied models were most strongly influenced by the feedstock's particle size and the type of gasifying agent employed. By combining global and local interpretability methods, the understanding of black box models has been improved. This allows policy makers and investors to make more educated decisions about gasification process design.

A meta-analysis of acetogenic and methanogenic microbiomes in microbial electrosynthesis.

A meta-analysis approach was used, to study the microbiomes of biofilms and planktonic communities underpinning microbial electrosynthesis (MES) cells. High-throughput DNA sequencing of 16S rRNA gene amplicons has been increasingly applied to understand MES systems. In this meta-analysis of 22 studies, we find that acetogenic and methanogenic MES cells share 80% of a cathodic core microbiome, and that different inoculum pre-treatments strongly affect community composition. Oxygen scavengers were more abundant in planktonic communities, and several key organisms were associated with operating parameters and good cell performance. We suggest Desulfovibrio sp. play a role in initiating early biofilm development and shaping microbial communities by catalysing H2 production, to sustain either Acetobacterium sp. or Methanobacterium sp. Microbial community assembly became more stochastic over time, causing diversification of the biofilm (cathodic) community in acetogenic cells and leading to re-establishment of methanogens, despite inoculum pre-treatments. This suggests that repeated interventions may be required to suppress methanogenesis.

Life cycle assessment of waste-to-hydrogen systems for fuel cell electric buses in Glasgow, Scotland.

Waste-to-hydrogen (WtH) technologies are proposed as a dual-purpose method for simultaneous non-fossil-fuel based hydrogen production and sustainable waste management. This work applied the life cycle assessment approach to evaluate the carbon saving potential of two main WtH technologies (gasification and fermentation) in comparison to the conventional hydrogen production method of steam methane reforming (SMR) powering fuel cell electric buses in Glasgow. It was shown that WtH technologies could reduce CO2-eq emissions per kg H2 by 50-69% as compared to SMR. Gasification treating municipal solid waste and waste wood had global warming potentials of 4.99 and 4.11 kg CO2-eq/kg H2 respectively, which were lower than dark fermentation treating wet waste at 6.6 kg CO2-eq/kg H2 and combined dark and photo fermentation at 6.4 kg CO2-eq/kg H2. The distance emissions of WtH-based fuel cell electric bus scenarios were 0.33-0.44 kg CO2-eq/km as compared to 0.89 kg CO2-eq/km for the SMR-based scenario.

Life cycle assessment of biodiesel production from rapeseed oil: Influence of process parameters and scale.

Biodiesel has the potential to mitigate the fossil fuel-related carbon emission and energy insecurity challenges. There are limited studies examining the impacts of biodiesel production scales on the environmental impacts, while such information will be valuable for guiding practical system design. This work applied the approach of life cycle assessment to evaluate the environmental impacts of biodiesel production from rapeseed oil which accounts for 80% of the European biofuel market. It was shown that the centralized large-scale and localized small-scale biodiesel production schemes have annual global warming potential (GWP) of 2.63 and 2.88 tCO2-eq/t biodiesel, where the rapeseed agriculture stage caused more than 65% carbon emissions. Sensitivity analysis revealed a high dependence of GWP on rapeseed yields, glycerol re-utilization strategy, and nitrogen nutrient in fertilizer. An alternative scenario was proposed for the large- and small-scale systems that could reduce carbon emissions by 14.1% and 33.6%.

Deploying an In Vitro Gut Model to Assay the Impact of the Mannan-Oligosaccharide Prebiotic Bio-Mos on the Atlantic Salmon (Salmo salar) Gut Microbiome.

Alpha mannose-oligosaccharide (MOS) prebiotics are widely deployed in animal agriculture as immunomodulators as well as to enhance growth and gut health. Their mode of action is thought to be mediated through their impact on host microbial communities and their associated metabolism. Bio-Mos is a commercially available prebiotic currently used in the agri-feed industry, but studies show contrasting results of its effect on fish performance and feed efficiency. Thus, detailed studies are needed to investigate the effect of MOS supplements on the fish microbiome to enhance our understanding of the link between MOS and gut health. To assess Bio-Mos for potential use as a prebiotic growth promoter in salmonid aquaculture, we have modified an established Atlantic salmon in vitro gut model, SalmoSim, to evaluate its impact on the host microbial communities. The microbial communities obtained from ceca compartments from four adult farmed salmon were inoculated in biological triplicate reactors in SalmoSim. Prebiotic treatment was supplemented for 20 days, followed by a 6-day washout period. Inclusion of Bio-Mos in the media resulted in a significant increase in formate (P = 0.001), propionate (P = 0.037) and 3-methyl butanoic acid (P = 0.024) levels, correlated with increased abundances of several, principally, anaerobic microbial genera (Fusobacterium, Agarivorans, Pseudoalteromonas). DNA metabarcoding with the 16S rDNA marker confirmed a significant shift in microbial community composition in response to Bio-Mos supplementation with observed increase in lactic acid producing Carnobacterium. In conjunction with previous in vivo studies linking enhanced volatile fatty acid production alongside MOS supplementation to host growth and performance, our data suggest that Bio-Mos may be of value in salmonid production. Furthermore, our data highlights the potential role of in vitro gut models to complementin vivo trials of microbiome modulators. IMPORTANCE In this paper we report the results of the impact of a prebiotic (alpha-MOS supplementation) on microbial communities, using an in vitro simulator of the gut microbial environment of the Atlantic salmon. Our data suggest that Bio-Mos may be of value in salmonid production as it enhances volatile fatty acid production by the microbiota from salmon pyloric ceca and correlates with a significant shift in microbial community composition with observed increase in lactic acid producing Carnobacterium. In conjunction with previous in vivo studies linking enhanced volatile fatty acid production alongside MOS supplementation to host growth and performance, our data suggest that Bio-Mos may be of value in salmonid production. Furthermore, our data highlights the potential role of in vitro gut models to augment in vivo trials of microbiome modulators.

The role of shear dynamics in biofilm formation.

There is growing evidence that individual bacteria sense and respond to changes in mechanical loading. However, the subtle responses of multispecies biofilms to dynamic fluid shear stress are not well documented because experiments often fail to disentangle any beneficial effects of shear stress from those delivered by convective transport of vital nutrients. We observed the development of biofilms with lognormally distributed microcolony sizes in drinking water on the walls of flow channels underflow regimes of increasing complexity. First, where regular vortices induced oscillating wall shear and simultaneously enhanced mass transport, which produced the thickest most extensive biofilms. Second, where unsteady uniform flow imposed an oscillating wall shear, with no enhanced transport, and where the biomass and coverage were only 20% smaller. Finally, for uniform steady flows with constant wall shear where the extent, thickness, and density of the biofilms were on average 60% smaller. Thus, the dynamics of shear stress played a significant role in promoting biofilm development, over and above its magnitude or mass transfer effects, and therefore, mechanosensing may prevail in complex multispecies biofilms which could open up new ways of controlling biofilm structure.

Validating Flow Cytometry as a Method for Quantifying Bdellovibrio Predatory Bacteria and Its Prey for Microbial Ecology.

Bdellovibrio bacteriovorus is a predatory, Gram-negative bacteria that feeds on many pathogenic bacteria and has been investigated as a possible solution for mitigating biofilms in different fields. The application depends on more fundamental ecological studies into the dynamics between Bdellovibrio and their prey. To do so requires an accurate, reliable, and, preferably rapid, way of enumerating the cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated in the enumeration of Bdellovibrio. In this study, we developed a protocol to measure the number of Bdellovibrio in samples of various densities using FCM and compared the results with those of other methods: optical density (OD), PFU assay (PFU), and quantitative PCR (qPCR). We observed a strong correlation between values obtained using FCM and PFU (ρ = 0.923) and FCM and qPCR (ρ = 0.987). Compared to optical density there was a much weaker correlation (ρ = 0.784), which was to be expected given the well-documented uncertainty in converting optical density (OD) to cell numbers. The FCM protocol was further validated by demonstrating its ability to distinguish and count mixed populations of Bdellovibrio and the prey Pseudomonas. Thus, the accuracy of FCM as well as its speed and reproducibility make it a suitable alternative for measuring Bdellovibrio cell numbers, especially where many samples are required to capture the dynamics of predator-prey interactions. IMPORTANCE The rise of antibiotic resistance and the unwanted growth of bacteria is a universally growing problem. Predatory bacteria can be used as a biological alternative to antibiotics because they grow by feeding on other bacteria. To apply this effectively requires further study and a deeper understanding of the forces that drive a prey population to elimination. Initially, such studies require more reliable methods to count these cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated for predatory bacteria. This study develops a protocol to count the predatory bacteria Bdellovibrio bacteriovorus and its Pseudomonas prey using FCM and compare the results with those of other methods, demonstrating its ability for studies into B. bacteriovorus predation dynamics. This could lead to the use of B. bacteriovorus for killing bacterial biofilms in fields, such as drinking water and agriculture.

Biochemistry shapes growth kinetics of nitrifiers and defines their activity under specific environmental conditions.

Is it possible to find trends between the parameters that define microbial growth to help us explain the vast microbial diversity? Through an extensive database of kinetic parameters of nitrifiers, we analyzed if the dominance of specific populations of nitrifiers could be predicted and explained. We concluded that, in general, higher growth yield (YXS ) and ammonia affinity (a0NH3 ) and lower growth rate (µmax ) are observed for ammonia-oxidizing archaea (AOA) than bacteria (AOB), which would explain their considered dominance in oligotrophic environments. However, comammox (CMX), with the maximum energy harvest per mole of ammonia, and some AOB, have higher a0NH3 and lower µmax than some AOA. Although we were able to correlate the presence of specific terminal oxidases with observed oxygen affinities (a0O2 ) for nitrite-oxidizing bacteria (NOB), that correlation was not observed for AOB. Moreover, the presumed dominance of AOB over NOB in O2 -limiting environments is discussed. Additionally, lower statistical variance of a0O2 values than for ammonia and nitrite affinities was observed, suggesting nitrogen limitation as a stronger selective pressure. Overall, specific growth strategies within nitrifying groups were not identified through the reported kinetic parameters, which might suggest that mostly, fundamental differences in biochemistry are responsible for underlying kinetic parameters.