Polyoxometalates have attracted significant interest owing to their structural diversity, redox stability, and functionality at the nanoscale. In this work, density functional theory calculations have been employed to systematically study the accuracy of various exchange-correlation functionals in reproducing experimental redox potentials, U0Red in [PW11M(H2O)O39]q- M = Mn(III/II), Fe(III/II), Co(III/II), and Ru(III/II). U0Red calculations for [PW11M(H2O)O39]q- were calculated using a conductor-like screening model to neutralize the charge in the cluster. We explicitly located K+ counterions which induced positive shifting of potentials by > 500 mV. This approximation improved the reproduction of redox potentials for Kx[XW11M(H2O)O39]q-x M = Mn(III/II)/Co(III/II). However, uncertainties in U0Red for Kx[PW11M(H2O)O39]q-x M = Fe(III/II)/Ru(III/II) were observed because of the over-stabilization of the ion-pairs. Hybrid functionals exceeding 25% Hartree-Fock exchange are not recommended because of large uncertainties in ΔU0Red attributed to exaggerated proximity of the ion-pairs. Our results emphasize that understanding the nature of the electrode and electrolyte environment is essential to obtain a reasonable agreement between theoretical and experimental results.

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.

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.

The lipid fraction of the effluents generated in several food-processing activities can be transformed into polyhydroxyalkanoates (PHAs) and triacylglycerides (TAGs), through open culture biotechnologies. Although competition between storing and non-storing populations in mixed microbial cultures (MMCs) has been widely studied, the right selective environment allowing for the robust enrichment of a community when different types of accumulators coexist is still not clear. In this research, comprehensive metabolic analyses of PHA and TAG synthesis and degradation, and concomitant respiration of external carbon, were used to understand and explain the changes observed in a laboratory-scale bioreactor fed with the lipid-rich fraction (mainly oleic acid) of a wastewater stream produced in the fish-canning industry. It was concluded that the mode of oxygen, carbon, and nitrogen supply determines the enrichment of the culture in specific populations, and hence the type of intracellular compounds preferentially accumulated. Coupled carbon and nitrogen feeding regime mainly selects for TAG producers whereas uncoupled feeding leads to PHA or TAG production function of the rate of carbon supply under specific aeration rates and feast and famine phases lengths.

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 (Y_XS) and ammonia affinity (a⁰_NH3) and lower growth rate (µ_max) 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 a⁰_NH3 and lower µ_max than some AOA. Although we were able to correlate the presence of specific terminal oxidases with observed oxygen affinities (a⁰_O2) 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 a⁰_O2 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.

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.

Industrial waste fish oil streams contain high concentrations of medium and long-chain fatty acids suitable to produce value-added compounds. However, to process them dilution is required, and the water produced in the fish-canning industry commonly contains high salinity, which might limit its reuse as a dilution stream. Although NaCl is well-known to negatively affect biological activity, its effect on triacylglycerides (TAG) and polyhydroxyalkanoates (PHA) storage has not been well studied yet. Here, it was explored if intracellular TAG and PHA production can be efficient under saline conditions (10 g NaCl/L). For that purpose, waste fish oil was valorised using a mixed microbial culture (MMC) in a two-stage process (culture selection plus accumulation). Results showed that salinity influenced not only the activity but the structure of the microbial communities developed in the bioreactors. The bacterial genera Acinetobacter and Rhizobium and the mold Candida glaebosa clade were observed as the storing microorganisms which abundance increased under saline conditions whereas Dipodascus and Mortierella notably decreased. Nonetheless, despite the osmotic stress, promising results were obtained and maximum intracellular accumulations of 54.2 wt% (TAG:PHA = 28:72, 0.131 Cmmol_TAG/Cmmol_S, 0.303 Cmmol_PHA/Cmmol_S) and 50.9 wt% (TAG:PHA = 63:37, 0.291 Cmmol_TAG/Cmmol_S, 0.114 Cmmol_PHA/Cmmol_S) were observed when PHA and TAG were preferentially stored, respectively.

Fast and reliable industrial production of ammonia (NH₃) is fundamentally sustaining modern society. Since the early 20^th Century, NH₃ has been synthesized via the Haber–Bosch process, running at conditions of around 350–500°C and 100–200 times atmospheric pressure (15–20 MPa). Industrial ammonia production is currently the most energy-demanding chemical process worldwide and contributes up to 3% to the global carbon dioxide emissions. Therefore, the development of more energy-efficient pathways for ammonia production is an attractive proposition. Over the past 20 years, scientists have imagined the possibility of developing a milder synthesis of ammonia by mimicking the nitrogenase enzyme, which fixes nitrogen from the air at ambient temperatures and pressures to feed leguminous plants. To do this, we propose the use of highly reconfigurable molecular metal oxides or polyoxometalates (POMs). Our proposal is an informed design of the polyoxometalate after exploring the catabolic pathways that cyanobacteria use to fix N₂ in nature, which are a different route than the one followed by the Haber–Bosch process. Meanwhile, the industrial process is a “brute force” system towards breaking the triple bond N-N, needing high pressure and high temperature to increase the rate of reaction, nature first links the protons to the N₂ to later easier breaking of the triple bond at environmental temperature and pressure. Computational chemistry data on the stability of different polyoxometalates will guide us to decide the best design for a catalyst. Testing different functionalized molecular metal oxides as ammonia catalysts laboratory conditions will allow for a sustainable reactor design of small-scale production.