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Carvallo, Lorena; Carrera, Julián; Chamy, Rolando

doi:10.1023/a:1021375523879

Cited by 27 publications

(1 citation statement)

References 8 publications

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“…Physical and chemical aspects of the environment could be adjusted by controlling for example the pH, temperature and dissolved oxygen (DO) for each species without interfering with the rest of the system. The pH could be regulated by adding, acid or base in-line (Keen and Prosser, 1987; Wijffels et al, 1991; Hunik et al, 1994; Gernaey et al, 1998; Carvallo et al, 2002; Park and Bae, 2009), a buffer to the medium (Shieh and LaMotta, 1979; Charley et al, 1980; Hellinga et al, 1999; Chandran and Smets, 2005; Vadivelu et al, 2006), or by inserting a “buffering chamber” between two elements, an abiotic module whose function would be to adapt the pH of the medium before piping it to the next microorganism, should this be necessary. Temperature of bioreactors could be controlled by placing it in a thermostatically controlled bath, by using internal heating coils or external heating jackets (Stanbury et al, 2017).…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia

Said

2017

Front. Microbiol.

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The metabolic diversity present in microbial communities enables cooperation toward accomplishing more complex tasks than possible by a single organism. Members of a consortium communicate by exchanging metabolites or signals that allow them to coordinate their activity through division of labor. In contrast with monocultures, evidence suggests that microbial consortia self-organize to form spatial patterns, such as observed in biofilms or in soil aggregates, that enable them to respond to gradient, to improve resource interception and to exchange metabolites more effectively. Current biotechnological applications of microorganisms remain rudimentary, often relying on genetically engineered monocultures (e.g., pharmaceuticals) or mixed-cultures of partially known composition (e.g., wastewater treatment), yet the vast potential of “microbial ecological power” observed in most natural environments, remains largely underused. In line with the Unified Microbiome Initiative (UMI) which aims to “discover and advance tools to understand and harness the capabilities of Earth's microbial ecosystems,” we propose in this concept paper to capitalize on ecological insights into the spatial and modular design of interlinked microbial consortia that would overcome limitations of natural systems and attempt to optimize the functionality of the members and the performance of the engineered consortium. The topology of the spatial connections linking the various members and the regulated fluxes of media between those modules, while representing a major engineering challenge, would allow the microbial species to interact. The modularity of such spatially linked microbial consortia (SLMC) could facilitate the design of scalable bioprocesses that can be incorporated as parts of a larger biochemical network. By reducing the need for a compatible growth environment for all species simultaneously, SLMC will dramatically expand the range of possible combinations of microorganisms and their potential applications. We briefly review existing tools to engineer such assemblies and optimize potential benefits resulting from the collective activity of their members. Prospective microbial consortia and proposed spatial configurations will be illustrated and preliminary calculations highlighting the advantages of SLMC over co-cultures will be presented, followed by a discussion of challenges and opportunities for moving forward with some designs.

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Section: Challenges and Opportunitiesmentioning

confidence: 99%

Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia

Said

2017

Front. Microbiol.

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Practical identifiability of biokinetic parameters of a model describing two‐step nitrification in biofilms

Brockmann

Rosenwinkel

Morgenroth

2008

Biotech & Bioengineering

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Parameter estimation and model calibration are key problems in the application of biofilm models in engineering practice, where a large number of model parameters need to be determined usually based on experimental data with only limited information content. In this article, identifiability of biokinetic parameters of a biofilm model describing two-step nitrification was evaluated based solely on bulk phase measurements of ammonium, nitrite, and nitrate. In addition to evaluating the impact of experimental conditions and available measurements, the influence of mass transport limitation within the biofilm and the initial parameter values on identifiability of biokinetic parameters was evaluated. Selection of parameters for identifiability analysis was based on global mean sensitivities while parameter identifiability was analyzed using local sensitivity functions. At most, four of the six most sensitive biokinetic parameters were identifiable from results of batch experiments at bulk phase dissolved oxygen concentrations of 0.8 or 5 mg O(2)/L. High linear dependences between the parameters of the subsets (KO2,AOB,muAOB) and (KO2,NOB,muNOB) resulted in reduced identifiability. Mass transport limitation within the biofilm did not influence the number of identifiable parameters but, in fact, decreased collinearity between parameters, especially for parameters that are otherwise correlated (e.g., muAOB) and KO2,AOB, or muNOB and KO2,NOB). The choice of the initial parameter values had a significant impact on the identifiability of two parameter subsets, both including the parameters muAOB and KO2,AOB. Parameter subsets that did not include the subsets muAOB and KO2,AOB or muNOB and KO2,NOB were clearly identifiable independently of the choice of the initial parameter values.

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Modelling microbial competition in nitrifying biofilm reactors

Vannecke

Volcke

2015

Biotech & Bioengineering

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A large variety of microbial parameter values for nitrifying microorganisms has been reported in literature and was revised in this study. Part of the variety was attributed to the variety of analysis methods applied; it also reflects the large biodiversity in nitrifying systems. This diversity is mostly neglected in conventional nitrifying biofilm models. In this contribution, a one-dimensional, multispecies nitrifying biofilm model was set up, taking into account the large variety of the maximum growth rate, the substrate affinity and the yield of nitrifiers reported in literature. Microbial diversity was implemented in the model by considering 60 species of ammonia-oxidizing bacteria (AOB) and 60 species of nitrite-oxidizing bacteria (NOB). A steady-state analysis showed that operational conditions such as the nitrogen loading rate and the bulk liquid oxygen concentration influence both the macroscopic output as well as the microbial composition of the biofilm through the prevailing concentration of substrates throughout the biofilm. Considering two limiting resources (nitrogen and oxygen), the coexistence of two species of the same functional guild (AOB or NOB) was possible at steady state. Their spatial distribution in the biofilm could be explained using the r- and K-selection theory.

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Untitled

Cited by 27 publications

References 8 publications

Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia

Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia

Practical identifiability of biokinetic parameters of a model describing two‐step nitrification in biofilms

Modelling microbial competition in nitrifying biofilm reactors

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