A biofilm model to understand the onset of sulfate reduction in denitrifying membrane biofilm reactors

This work presents a multispecies biofilm model that describes the co‐existence of nitrate‐ and sulfate‐reducing bacteria in the H₂‐based membrane biofilm reactor (MBfR). The new model adapts the framework of a biofilm model for simultaneous nitrate and perchlorate removal by considering the unique metabolic and physiological characteristics of autotrophic sulfate‐reducing bacteria that use H₂ as their electron donor. To evaluate the model, the simulated effluent H₂, UAP (substrate‐utilization‐associated products), and BAP (biomass‐associated products) concentrations are compared to experimental results, and the simulated biomass distributions are compared to real‐time quantitative polymerase chain reaction (qPCR) data in the experiments for parameter optimization. Model outputs and experimental results match for all major trends and explain when sulfate reduction does or does not occur in parallel with denitrification. The onset of sulfate reduction occurs only when the nitrate concentration at the fiber's outer surface is low enough so that the growth rate of the denitrifying bacteria is equal to that of the sulfate‐reducing bacteria. An example shows how to use the model to design an MBfR that achieves satisfactory nitrate reduction, but suppresses sulfate reduction. Biotechnol. Bioeng. 2013; 110: 763–772. © 2012 Wiley Periodicals, Inc.     

Biofilm model calibration and microbial diversity study using Monte Carlo simulations

Mathematical models are useful tools for studying and exploring biological conversion processes as well as microbial competition in biological treatment processes. A single‐species biofilm model was used to describe biofilm reactor operation at three different hydraulic retention times (HRT). The single‐species biofilm model was calibrated with sparse experimental data using the Monte Carlo filtering method. This calibrated single‐species biofilm model was then extended to a multi‐species model considering 10 different heterotrophic bacteria. The aim was to study microbial diversity in bulk phase biomass and biofilm, as well as the competition between suspended and attached biomass. At steady state and independently of the HRT, Monte Carlo simulations resulted only in one unique dominating bacterial species for suspended and attached biomass. The dominating bacterial species was determined by the highest specific substrate affinity (ratio of µ/K_S). At a short HRT of 20 min, the structure of the microbial community in the bulk liquid was determined by biomass detached from the biofilm. At a long HRT of 8 h, both biofilm detachment and microbial growth in the bulk liquid influenced the microbial community distribution. Biotechnol. Bioeng. 2013; 110: 1323–1332. © 2012 Wiley Periodicals, Inc.     

Luxury uptake of magnesium by peas,Pisum sativum

Increasing the magnesium (Mg) concentration of vegetables (biofortification) will often require ‘luxury’ uptake where the whole‐plant concentration of Mg (c_p) is greater than required for maximum yield. Our aim was to quantify some of the physiological factors influencing luxury uptake of Mg to aid subsequent development of agronomic techniques for biofortification. Peas, Pisum sativum, were used as a test species. A sand culture experiment related vegetative growth and c_p for plants grown with a range of Mg and potassium (K) supply rates. We developed a model of Mg uptake including feedback control exerted by c_p. The model was parameterised with results from a solution culture experiment and then used to explore ways to increase luxury uptake of Mg. Feedback control of Mg uptake by c_p was weak. Biomass did not increase if the Mg concentration exceeded 0.11% in the whole plant or 0.13% in the shoots. Values obtained in the field are often larger than this. Our results indicate that luxury uptake of Mg by peas is readily achieved, provided that there is ample supply of Mg²⁺ to the root surfaces. In field soils though, transport of Mg²⁺ to the roots may limit uptake and cation exchange processes restrict the ability of Mg fertilisers to substantially increase Mg uptake. Increasing root growth will usually increase Mg uptake, but c_p may not rise if biomass is also increased.     

Genetic Mapping and Genomic Selection Using Recombination Breakpoint Data

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.     

Late‐glacial recolonization and phylogeography of European red deer (Cervus elaphus L.)

The Pleistocene was an epoch of extreme climatic and environmental changes. How individual species responded to the repeated cycles of warm and cold stages is a major topic of debate. For the European fauna and flora, an expansion–contraction model has been suggested, whereby temperate species were restricted to southern refugia during glacial times and expanded northwards during interglacials, including the present interglacial (Holocene). Here, we test this model on the red deer (Cervus elaphus) a large and highly mobile herbivore, using both modern and ancient mitochondrial DNA from the entire European range of the species over the last c. 40 000 years. Our results indicate that this species was sensitive to the effects of climate change. Prior to the Last Glacial Maximum (LGM) haplogroups restricted today to South‐East Europe and Western Asia reached as far west as the UK. During the LGM, red deer was mainly restricted to southern refugia, in Iberia, the Balkans and possibly in Italy and South‐Western Asia. At the end of the LGM, red deer expanded from the Iberian refugium, to Central and Northern Europe, including the UK, Belgium, Scandinavia, Germany, Poland and Belarus. Ancient DNA data cannot rule out refugial survival of red deer in North‐West Europe through the LGM. Had such deer survived, though, they were replaced by deer migrating from Iberia at the end of the glacial. The Balkans served as a separate LGM refugium and were probably connected to Western Asia with genetic exchange between the two areas.     

Exploring the effects of immunity and life history on the dynamics of an endogenous retrovirus

Mammalian DNA is littered with the signatures of past retroviral infections. For example, at least 8% of the human genome can be attributed to endogenous retroviruses (ERVs). We take a single-locus approach to develop a simple susceptible–infected–recovered model to investigate the circumstances under which a disease-causing retrovirus can become incorporated into the host genome and spread through the host population if it were to confer an immunological advantage. In the absence of any fitness benefit provided by the long terminal repeat (LTR), we conclude that signatures of ERVs are likely to go to fixation within a population when the probability of evolving cellular/humoral immunity to a related exogenous version of the virus is extremely small. We extend this model to examine whether changing the speed of the host life history influences the likelihood that an exogenous retrovirus will incorporate and spread to fixation. Our results reveal the parameter space under which incorporation of exogenous retroviruses into a host genome may be beneficial to the host. In our final model, we find that the likelihood of an LTR reaching fixation in a host population is not strongly affected by host life history.     

Using multilevel models to identify drivers of landscape‐genetic structure among management areas

Landscape genetics offers a powerful approach to understanding species' dispersal patterns. However, a central obstacle is to account for ecological processes operating at multiple spatial scales, while keeping research outcomes applicable to conservation management. We address this challenge by applying a novel multilevel regression approach to model landscape drivers of genetic structure at both the resolution of individuals and at a spatial resolution relevant to management (i.e. local government management areas: LGAs) for the koala (Phascolartos cinereus) in Australia. Our approach allows for the simultaneous incorporation of drivers of landscape‐genetic relationships operating at multiple spatial resolutions. Using microsatellite data for 1106 koalas, we show that, at the individual resolution, foliage projective cover (FPC) facilitates high gene flow (i.e. low resistance) until it falls below approximately 30%. Out of six additional land‐cover variables, only highways and freeways further explained genetic distance after accounting for the effect of FPC. At the LGA resolution, there was significant variation in isolation‐by‐resistance (IBR) relationships in terms of their slopes and intercepts. This was predominantly explained by the average resistance distance among LGAs, with a weaker effect of historical forest cover. Rates of recent landscape change did not further explain variation in IBR relationships among LGAs. By using a novel multilevel model, we disentangle the effect of landscape resistance on gene flow at the fine resolution (i.e. among individuals) from effects occurring at coarser resolutions (i.e. among LGAs). This has important implications for our ability to identify appropriate scale‐dependent management actions.