Resource availability shapes microbial motility and mediates early-stage formation of microbial clusters in biological wastewater treatment processes

Chen, Guowei; Zhu, Ning; Tang, Zebing; Peng, Ye; Hu, Zhenhu; Liu, Li

doi:10.1007/s00253-013-5109-1

Cited by 13 publications

(2 citation statements)

References 47 publications

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“…Individual cell shape, cell division, and motility have been used in several models to study cluster formation (Chen et al 2014), complex filamentous floc formation (Storck et al 2014) and fractal patterning of cell layers (Rudge et al 2013), or the formation of mushroom-like biofilm colonies ). The first individualbased model of a biofilm, BacSim, was developed by Kreft et al (1998.…”

Section: Agent-based Models (Abms) and Adaptionsmentioning

confidence: 99%

Modeling microbial growth and dynamics

Esser

Leveau

Meyer

2015

Appl Microbiol Biotechnol

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Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.

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Section: Agent-based Models (Abms) and Adaptionsmentioning

confidence: 99%

Modeling microbial growth and dynamics

Esser

Leveau

Meyer

2015

Appl Microbiol Biotechnol

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“…For example, in a ceramic substrate photo-bioreactor, the optimum biomass productivity of 4.65 ± 0.42 g/m 2 /d was obtained after 8-d cultivation at a light intensity of 17,000 lux and 14 mL/d BG-11 medium [34]. It was reported that the initial nutrient concentration, including nitrogen and phosphate, influences bacterial [35][36][37] and microalgal [38,39] cell attachment/aggregation. For instance, Scenedesmus LX1 was found to increase the attached life form under relatively lower nitrogen and phosphate concentrations as compared with those of high-nutrient circumstances [36].…”

Section: Introductionmentioning

confidence: 99%

Chemotactic movement and zeta potential dominate Chlamydomonas microsphaera attachment and biocathode development

Chen

Ebrahimi

et al. 2021

Environmental Technology

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Microalgal cell attaching and biofilm formation are critical in the application of microalgal biocathode, which severs as one of the hopeful candidates to an original cathode in bioelectrochemical systems. Many efforts have been put in biofilm formation and bioelectrochemical systems for years, but the predominant factors shaping microalgal biocathode formation are sketchy.We launched a pair of researches to investigate microalgal attachment and biofilm formation in the presence/ absence of applied voltages using Chlamydomonas microsphaera as a model unicellular motile microalga. In this study, we presented how microalga attached and biofilm formed on a carbon felt surface without applied voltages and try to manifest the most important aspects in this process. Results showed that while nutrient sources did not directly regulate cell attachment onto the carbon felt, limited initial nutrient concentration nevertheless promoted cell attachment. Specifically, nutrient availability did not influence the early-stage (20 -60 min) of microalgal cell attachment but did significantly impact cell attachment during later stages (240 -720 min). Further analysis revealed that nutrient availability-mediated chemotactic movements and zeta potential are crucial to facilitate the initial attachment and subsequent biofilm formation of C. microsphaera onto the surfaces, serving as an important factor controlling microalgal surface attachment. Our results demonstrate that nutrient availability is a dominant factor controlling microalgal surface attachment and subsequent biofilm formation processes. This study provides mechanistic understanding of microalgal surface attachment and biofilm formation processes on carbon felts surfaces in the absence of applied voltages.

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