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.

Future directions for studying resilience of the oral ecosystem.

The oral ecosystem is shaped by complex interactions between systemic health disease and the resident oral microbiota. Research in the last two decades has produced datasets describing the genetics and physiology of the host and the oral microbiome in health and disease. There are inter-individual differences in the ability to tolerate oral disease-promoting challenges. Identification of the key factors that drive a healthy and resilient oral ecosystem is urgently needed. So far, progress is being made towards replicating the host-microbiota interplay in vitro. Clinical studies may shed light on the mechanisms of oral health resilience. However, most clinical studies are cross-sectional and are insufficient for understanding resilience or for identifying biomarkers that correlate with the point of transition from oral health to dysbiosis. Mathematical and computational models, including artificial intelligence approaches, offer an opportunity to inform the design of clinical studies by identifying key biomarkers and interaction networks in complex datasets and predicting important parameters. This paper discusses some of the challenges and opportunities for understanding the biological basis of resilience of the oral ecosystem. It discusses the current status and challenges, and proposes a way forward to better understand resilience towards oral diseases.

Capturing Multicellular System Designs Using Synthetic Biology Open Language (SBOL).

Synthetic biology aims to develop novel biological systems and increase their reproducibility using engineering principles such as standardization and modularization. It is important that these systems can be represented and shared in a standard way to ensure they can be easily understood, reproduced, and utilized by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterization. Previously, this standard has only been used to represent designs in systems where the same design is implemented in every cell; however, there is also much interest in multicellular systems, in which designs involve a mixture of different types of cells with differing genotype and phenotype. Here, we show how the SBOL standard can be used to represent multicellular systems, and, hence, how researchers can better share designs with the community and reliably document intended system functionality.

NUFEB: A massively parallel simulator for individual-based modelling of microbial communities.

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 Model Links Thermodynamics, Chemical Speciation and Environmental Conditions to Microbial Growth.

Individual based Models (IbM) must transition from research tools to engineering tools. To make the transition we must aspire to develop large, three dimensional and physically and biologically credible models. Biological credibility can be promoted by grounding, as far as possible, the biology in thermodynamics. Thermodynamic principles are known to have predictive power in microbial ecology. However, this in turn requires a model that incorporates pH and chemical speciation. Physical credibility implies plausible mechanics and a connection with the wider environment. Here, we propose a step toward that ideal by presenting an individual based model connecting thermodynamics, pH and chemical speciation and environmental conditions to microbial growth for 5·105 individuals. We have showcased the model in two scenarios: a two functional group nitrification model and a three functional group anaerobic community. In the former, pH and connection to the environment had an important effect on the outcomes simulated. Whilst in the latter pH was less important but the spatial arrangements and community productivity (that is, methane production) were highly dependent on thermodynamic and reactor coupling. We conclude that if IbM are to attain their potential as tools to evaluate the emergent properties of engineered biological systems it will be necessary to combine the chemical, physical, mechanical and biological along the lines we have proposed. We have still fallen short of our ideals because we cannot (yet) calculate specific uptake rates and must develop the capacity for longer runs in larger models. However, we believe such advances are attainable. Ideally in a common, fast and modular platform. For future innovations in IbM will only be of use if they can be coupled with all the previous advances.

Bioenergetics analysis of ammonia-oxidizing bacteria and the estimation of their maximum growth yield.

The currently accepted biochemistry and bioenergetics of ammonia-oxidizing bacteria (AOB) show an inefficient metabolism: only 53.8% of the energy released when a mole of ammonia is oxidised and less than two of the electrons liberated can be directed to the autotrophic anabolism. However, paradoxically, AOB seem to thrive in challenging conditions: growing readily in virtually most aerobic environment, yet limited AOB exist in pure culture. In this study, a comprehensive model of the biochemistry of the metabolism of AOB is presented. Using bioenergetics calculations and selecting the minimum estimation for the energy dissipated in each of the metabolic steps, the model predicts the highest possible true yield of 0.16 gBio/gN and a yield of 0.13 gBio/gN when cellular maintenance is considered. Observed yields should always be lower than these values but the range of experimental values in literature vary between 0.04 and 0.45 gBio/gN. In this work, we discuss if this variance of observed values for AOB growth yield could be understood if other non-considered alternative energy sources are present in the biochemistry of AOB. We analyse how the predicted maximum growth yield of AOB changes considering co-metabolism, the use of hydroxylamine as a substrate, the abiotic oxidation of NO, energy harvesting in the monooxygenase enzyme or the use of organic carbon sources.

Neutral mechanisms and niche differentiation in steady-state insular microbial communities revealed by single cell analysis.

In completely insular microbial communities, evolution of community structure cannot be shaped by the immigration of new members. In addition, when those communities are run in steady state, the influence of environmental factors on their assembly is reduced. Therefore, one would expect similar community structures under steady-state conditions. Yet, in parallel setups, variability does occur. To reveal ecological mechanisms behind this phenomenon, five parallel reactors were studied at the single-cell level for about 100 generations and community structure variations were quantified by ecological measures. Whether community variability can be controlled was tested by implementing soft temperature stressors as potential synchronizers. The low slope of the lognormal rank-order abundance curves indicated a predominance of neutral mechanisms, i.e., where species identity plays no role. Variations in abundance ranks of subcommunities and increase in inter-community pairwise ß-diversity over time support this. Niche differentiation was also observed, as indicated by steeper geometric-like rank-order abundance curves and increased numbers of correlations between abiotic and biotic parameters during initial adaptation and after disturbances. Still, neutral forces dominated community assembly. Our findings suggest that complex microbial communities in insular steady-state environments can be difficult to synchronize and maintained in their original or desired structure, as they are non-equilibrium systems.

SynBioHub: A Standards-Enabled Design Repository for Synthetic Biology.

The SynBioHub repository ( https://synbiohub.org ) is an open-source software project that facilitates the sharing of information about engineered biological systems. SynBioHub provides computational access for software and data integration, and a graphical user interface that enables users to search for and share designs in a Web browser. By connecting to relevant repositories (e.g., the iGEM repository, JBEI ICE, and other instances of SynBioHub), the software allows users to browse, upload, and download data in various standard formats, regardless of their location or representation. SynBioHub also provides a central reference point for other resources to link to, delivering design information in a standardized format using the Synthetic Biology Open Language (SBOL). The adoption and use of SynBioHub, a community-driven effort, has the potential to overcome the reproducibility challenge across laboratories by helping to address the current lack of information about published designs.

A mechanistic Individual-based Model of microbial communities.

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.

Conditional confined oscillatory dynamics of Escherichia coli strain K12-MG1655 in chemostat systems.

A series of continuous- and sequencing-batch reactor experiments were performed to assess the growth dynamics of Escherichia coli strain K12-MG1655 in chemostat systems. Previous mathematical predictions and early experimental results had shown that confined oscillatory dynamics ensue in bioreactor populations, which relates to "group birth and death" events within the population. New results are reported here that generally verify the predictions of the model and show that confined oscillations occur under different initial conditions, but the characteristics of the oscillatory dynamics vary as a function of the hydraulic retention time (HRT). Bioreactors were operated at HRTs ranging from 2.7 to 35 h and, regardless of initial conditions or the imposition of transient operational instabilities, highly patterned oscillations developed when HRT was between ∼3 and 8 h. However, outside of this range, bioreactor populations tended to form biofilms on the reactor walls (although the majority of the cells remained suspended in the bulk solution) and stable oscillations were not seen in the bulk phase. This suggests that alternate operating "states" might exist in chemostat populations with biofilm formation and non-homogenous spatial growth influencing "system" dynamics at very low and high HRTs. Although the model accurately predicts a confined dynamic equilibrium for mid-range HRT operations, experimental data show that model predictions do not extend outside of this range, when an alternate stable-state seems to be attained.

Non-linear population dynamics in chemostats associated with live-dead cell cycling in Escherichia coli strain K12-MG1655.

Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live-dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between OD600 and live-dead cell oscillations (within ~33-38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local OD600 maxima and lowest at local OD600 minima, showing that oscillations followed live-dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology.

Combined niche and neutral effects in a microbial wastewater treatment community.

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.

Continuous hybridoma bioreactor: sensitivity analysis and optimal control.

Animal cell culture has already established itself as a mature technology able to make a wide range of valuable products, the actual focus being to find the competitive bioreactor design and operating conditions for increasing production. A complex analysis, implying sensitivity calculus and optimal control computation, is done for a system composed of a continuous perfectly mixed bioreactor, with cell recirculation, a cell separator, a mixer and a purge. The bioreactor's sensitivity to the control parameters is measured by a new concept, entropic density, developed from the notion of Shannon entropy. An optimization procedure based on a genetic-algorithms approach is applied for the computation of the inlet flow profile in time, which guarantees optimum monoclonal-antibody production. Our studies, including the present one, proved that the best approach to obtain high production is to use a hybrid operating sequence: fed-batch mode followed by the continuous mode.

A sensitivity analysis of the fed-batch animal-cell bioreactor with respect to some control parameters.

Animal cell culture is widely used in the manufacture of valuable products, and this process is nowadays seeing a rapid expansion. The growth of animal cells is a complex process, because the cells are very sensitive to environmental changes (in, for example, nutrients, pH, temperature, oxygen and osmolarity) during this phase and to the toxic compounds produced by the cell itself. Ammonia and lactate are the two major waste materials of cell culture. They can have inhibitory effects on cell growth and product (monoclonal antibodies among others) formation. In order to model the behaviour of a fed-batch animal cell bioreactor producing monoclonal antibodies, it is necessary to use a complex kinetic model with optimal operating patterns ensuring high productivities. Good knowledge of such domains of operating parameters, together with the understanding of the response of this rather complex system to small modifications in the working conditions, are essential for on-line control to improve the quality of product and the yield of an animal cell culture. The present study focuses on the sensitivity analysis of a fed-batch animal cell bioreactor with respect to some candidate control parameters (substrate set-point concentrations, feeding time-step patterns and concentration of feeding solutions), emphasizing the influence of these on the overall performance of the system.