Bio-Electrochemical System Depollution Capabilities and Monitoring Applications: Models, Applicability, Advanced Bio-Based Concept for Predicting Pollutant Degradation and Microbial Growth Kinetics via Gene Regulation Modelling

Microbial fuel cells (MFC) are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling-up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod-type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio-based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored.

Comparative Evaluation Of Lactobacillus Plantarum Strains Through Microbial Growth Kinetics

The study of the growth kinetics of lactobacilli with pronounced probiotic properties in their batch cultivation is essential. Various models based on the logistic curve model, containing parameters showing the influence of the accumulating lactic acid on the biosynthesis of the product, as well as parameters showing the sensitivity of the cells to lactic acid were used to model the growth kinetics in the present work. The rate constant of adaptation of the studied strains to the used nutrient medium and the induction period were also determined. The kinetics of lactic acid synthesis was determined according to the Weibull model.

Soil depth gradients in microbial growth kinetics under deeply- vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy and growth in models can improve our ability to predict the capacity of soil to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we investigated whether a change in crop rooting depth affects microbial growth kinetics in deep soils compared to surface soils. We used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted plants (switch grass) 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14C, dissolved organic carbon, specific UV absorbance, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was higher and rooting depth was deeper under switch grass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability, and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210-240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that > 10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in models to simulate carbon dynamics in deep soil layers.

Droplet-Based Screening for the Investigation of Microbial Nonlinear Dose–Response Characteristics System, Background and Examples

Droplet-based microfluidics is a versatile tool to reveal the dose–response relationship of different effectors on the microbial proliferation. Traditional readout parameter is the temporal development of the cell density for different effector concentrations. To determine nonlinear or unconventional dose–response relationships, data with high temporal resolution and dense concentration graduation are essential. If microorganisms with slow microbial growth kinetics are investigated, a sterile and evaporation-free long-term incubation technique is required. Here, we present a modular droplet-based screening system which was developed to solve these issues. Beside relevant technical aspects of the developed modules, the procedural workflow, and exemplary dose–response data for 1D and 2D dose–response screenings are presented.

Co-metabolism kinetics and electrogenesis change during cyanide degradation in a microbial fuel cell

The co-metabolic degradation kinetics, microbial growth kinetics and electricity generation capacity were researched for strain MC-1 in a MFC.