Adaptive management of an active services network

The benefits of active services and networks cannot be realised unless the associated increase in system complexity can be efficiently managed. An adaptive management solution is required. Simulation results show that a distributed genetic algorithm, inspired by observations of bacterial communities, can offer many key management functions. The algorithm is fast and efficient, even when the demand for network services is rapidly varying

Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion-based model MOSAIC

This paper deals with the simulation of microbial degradation of organic matter in soil within the pore space at a microscopic scale. Pore space was analysed with micro-computed tomography and described using a sphere network coming from a geometrical modelling algorithm. The biological model was improved regarding previous work in order to include the transformation of dissolved organic compounds and diffusion processes. We tested our model using experimental results of a simple substrate decomposition experiment (fructose) within a simple medium (sand) in the presence of different bacterial strains. Separate incubations were carried out in microcosms using five different bacterial communities at two different water potentials of −10 and −100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content, and we tested the model without changing any parameters at low water content. Same as for the experimental data, our simulation results showed that the decrease in water content caused a decrease of mineralization rate. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content

Reconstructing the Forest of Lineage Trees of Diverse Bacterial Communities Using Bio-inspired Image Analysis

Cell segmentation and tracking allow us to extract a plethora of cell attributes from bacterial time-lapse cell movies, thus promoting computational modeling and simulation of biological processes down to the single-cell level. However, to analyze successfully complex cell movies, imaging multiple interacting bacterial clones as they grow and merge to generate overcrowded bacterial communities with thousands of cells in the field of view, segmentation results should be near perfect to warrant good tracking results. We introduce here a fully automated closed-loop bio-inspired computational strategy that exploits prior knowledge about the expected structure of a colony's lineage tree to locate and correct segmentation errors in analyzed movie frames. We show that this correction strategy is effective, resulting in improved cell tracking and consequently trustworthy deep colony lineage trees. Our image analysis approach has the unique capability to keep tracking cells even after clonal subpopulations merge in the movie. This enables the reconstruction of the complete Forest of Lineage Trees (FLT) representation of evolving multi-clonal bacterial communities. Moreover, the percentage of valid cell trajectories extracted from the image analysis almost doubles after segmentation correction. This plethora of trustworthy data extracted from a complex cell movie analysis enables single-cell analytics as a tool for addressing compelling questions for human health, such as understanding the role of single-cell stochasticity in antibiotics resistance without losing site of the inter-cellular interactions and microenvironment effects that may shape it

Changes in planktonic and sediment bacterial communities under the highly regulated dam in the mid-part of the Three Gorges Reservoir

Bacterial communities play an important role in the biogeochemical cycle in reservoir ecosystems. However, the dynamic changes in both planktonic and sediment bacterial communities in a highly regulated dam reservoir remain unclear. This study investigated the temporal distribution patterns of bacterial communities in a transition section of the Three Gorges Reservoir (TGR) using Illumina MiSeq sequencing. Results suggested that in comparison to the planktonic bacteria, sediment bacteria contributed more to the reservoir microbial communities, accounting for 97% of the 7434 OTUs. The Shannon diversity index in the water (3.22~5.68) was generally lower than that in the sediment (6.72~7.56). In the high water level period (January and March), Proteobacteria, Actinobacteria, Cyanobacteria, and Firmicutes were the most abundant phyla, whereas in the low water level period (May, July, and September), the dominant phyla were Proteobacteria, Actinobacteria, and Bacteroidetes. Sediment samples were dominated by Proteobacteria, Chloroflexi, and Acidobacteria. Principal coordinate analysis of the bacterioplankton communities showed greater sensitivity to monthly changes than that of the sediment bacterial communities. Network analysis suggested that in comparison to planktonic bacterial communities, sediment bacterial communities were more complex and stable. The linear relationship between the CH4/CO2 ratio, water level, and relative abundance of methanotrophs highlighted the potential methane-oxidizing process in the mid-part of the TGR. Moreover, the potential impact of dam regulation on the bacterial communities was revealed by the significant relationship between abundant phyla and the inflow of the TGR.Fil: Qin, Yu. Chongqing Jiaotong University; ChinaFil: Tang, Qiong. Chongqing Jiaotong University; ChinaFil: Lu, Lunhui. Chinese Academy of Sciences; República de ChinaFil: Wang, Yuchun. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin; ChinaFil: Izaguirre, Irina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Li, Zhe. Chinese Academy of Sciences; República de Chin

Probabilistic models to describe the dynamics of migrating microbial communities

In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete) model simulates absolute numbers of individual cells, whereas the other (continuous) model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported

Modelling the emergent dynamics and major metabolites of the human colonic microbiota

Funded by Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS) Acknowledgements We would like to thank Thanasis Vogogias, David Nutter and Alec Mann for their assistance in developing the software for this model. We also acknowledge the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS) for their financial support. Furthermore,many thanks go to the two anonymous reviewers whose hard work has greatly improved this paper.Peer reviewedPublisher PD

Effect of key design parameters on bacteria community and effluent pollutant concentrations in constructed wetlands using mathematical models

Constructed wetlands are currently recognized as an effective environmental biotechnology for wastewater treatment, but the influence of their design parameters on internal functioning and contaminant removal efficiency is still under discussion. In this work, the effect of aspect ratio and water depth on bacteria communities as well as treatment efficiency of horizontal subsurface flow constructed wetlands (HSSF) under the Mediterranean climate was evaluated, using a mathematical model. For this purpose, experimental results from four pilot-scale wetlands of equal surface area but different aspect ratios and water depth were used. The HSSF system was fed with municipal wastewater. The experimental data were simulated using the BIO_PORE model, developed in the COMSOL Multiphysics™ platform. Simulations with the BIO_PORE model fitted well to the experimental results, showing a higher removal efficiency for the shallower HSSF for COD (93.7% removal efficiency) and ammonia nitrogen (73.8%). The aspect ratio had a weak relationship with the bacteria distribution and the removal efficiency. In contrast, the water depth was a factor. The results of the present study confirm a previous hypothesis in which depth has an important impact on the biochemical reactions causing contaminants transformation and degradation.Peer ReviewedPostprint (author's final draft

Assessing the importance of a self-generated detachment process in river biofilm models

1. Epilithic biofilm biomass was measured for 14 months in two sites, located up- and downstream of the city of Toulouse in the Garonne River (south-west France). Periodical sampling provided a biomass data set to compare with simulations from the model of Uehlinger, Bürher and Reichert (1996: Freshwater Biology, 36, 249–263.), in order to evaluate the impact of hydraulic disturbance. 2. Despite differences in application conditions (e.g. river size, discharge, frequency of disturbance), the base equation satisfactorily predicted biomass between low and high water periods of the year, suggesting that the flood disturbance regime may be considered a universal mechanism controlling periphyton biomass. 3. However modelling gave no agreement with biomass dynamics during the 7-month long low water period that the river experienced. The influence of other biomass-regulating factors (temperature, light and soluble reactive phosphorus) on temporal biomass dynamics was weak. 4. Implementing a supplementary mechanism corresponding to a temperature-dependent self-generated loss because of heterotrophic processes allowed us to accurately reproduce the observed pattern: a succession of two peaks. This case study suggests that during typical summer low water periods (flow stability and favourable temperature) river biofilm modelling requires self-generated detachment to be considered