It has long been assumed that differences in the relative abundance of taxa in microbial communities reflect differences in environmental conditions. Here we show that in the economically and environmentally important microbial communities in a wastewater treatment plant, the population dynamics are consistent with neutral community assembly, where chance and random immigration play an important and predictable role in shaping the communities. Using dynamic observations, we demonstrate a straightforward calibration of a purely neutral model and a parsimonious method to incorporate environmental influence on the reproduction (or birth) rate of individual taxa. The calibrated model parameters are biologically plausible, with the population turnover and diversity in the heterotrophic community being higher than for the ammonia oxidizing bacteria (AOB) and immigration into AOB community being relatively higher. When environmental factors were incorporated more of the variance in the observations could be explained but immigration and random reproduction and deaths remained the dominant driver in determining the relative abundance of the common taxa. Consequently we suggest that neutral community models should be the foundation of any description of an open biological system.

In wastewater treatment plants, nitrifying systems are usually operated with elevated levels of aeration to avoid nitrification failures. This approach contributes significantly to operational costs and the carbon footprint of nitrifying wastewater treatment processes. In this study, we tested the effect of aeration rate on nitrification by correlating ammonia oxidation rates with the structure of the ammonia-oxidizing bacterial (AOB) community and AOB abundance in four parallel continuous-flow reactors operated for 43 days. Two of the reactors were supplied with a constant airflow rate of 0.1 liter/min, while in the other two units the airflow rate was fixed at 4 liters/min. Complete nitrification was achieved in all configurations, though the dissolved oxygen (DO) concentration was only 0.5 ± 0.3 mg/liter in the low-aeration units. The data suggest that efficient performance in the low-DO units resulted from elevated AOB levels in the reactors and/or putative development of a mixotrophic AOB community. Denaturing gel electrophoresis and cloning of AOB 16S rRNA gene fragments followed by sequencing revealed that the AOB community in the low-DO systems was a subset of the community in the high-DO systems. However, in both configurations the dominant species belonged to theNitrosomonas oligotrophalineage. Overall, the results demonstrated that complete nitrification can be achieved at low aeration in lab-scale reactors. If these findings could be extended to full-scale plants, it would be possible to minimize the operational costs and greenhouse gas emissions without risk of nitrification failure.

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

We present NUFEB (Newcastle University Frontiers in Engineering Biology), a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator), which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems, with particular emphasis on biofilms. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (10⁷ individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEB’s functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate. Individual-based Models (IbM) are one of the most promising frameworks to study microbial communities, as they can explicitly describe the behaviour of each cell. The development of a general-purpose IbM solver should focus on efficiency and flexibility due to the unique characteristics of microbial systems. However, available tools for these purposes present significant limitations. Most of them only facilitate serial computing for single simulation, or only focus on biological processes, but do not model mechanical and chemical processes in detail. In this work, we introduce the IbM solver NUFEB that addresses some of these shortcomings. The tool facilitates the modelling of much needed biological, chemical, physical and individual microbes in detail, and offers the flexibility of model extension and customisation. NUFEB is also fully parallelised and allows for the simulation of large complex microbial system. In this paper, we first give an overview of NUFEB’s functionalities and implementation details. Then, we use NUFEB to model and simulate a biofilm system with fluid dynamics, and a large and complex biofilm system with multiple microbial functional groups and multiple nutrients.

Anaerobic fermentation of organic wastes using microbial mixed cultures is a promising avenue to treat residues and obtain added-value products. However, the process has some important limitations that prevented so far any industrial application. One of the main issues is that we are not able to predict reliably the product spectrum (i.e. the stoichiometry of the process) because the complex microbial community behaviour is not completely understood. To address this issue, in this work we propose a new metabolic network of glucose fermentation by microbial mixed cultures that incorporates electron bifurcation and homoacetogenesis. Our methodology uses NADH balances to analyse published experimental data and evaluate the new stoichiometry proposed. Our results prove for the first time the inclusion of electron bifurcation in the metabolic network as a better description of the experimental results. Homoacetogenesis has been used to explain the discrepancies between observed and theoretically predicted yields of gaseous H2 and CO2 and it appears as the best solution among other options studied. Overall, this work supports the consideration of electron bifurcation as an important biochemical mechanism in microbial mixed cultures fermentations and underlines the importance of considering homoacetogenesis when analysing anaerobic fermentations.

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.