Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

We present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. More importantly, we derive a number of consequences from the model that are independent of parameter values. First, that the ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties invariant across perfusion systems. This conclusion is robust even in the presence of multi-stability, which is explained in our model by the negative feedback loop on cell growth due to toxic byproduct accumulation. Moreover, a complex landscape of steady states in continuous cell culture emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. Thus, in order to actually reflect the expected behavior in perfusion, performance benchmarks of cell-lines and culture media should be carried out in a chemostat

The Operating Diagram for a Two-Step Anaerobic Digestion Model

The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its analytical study. Here, we consider the two-step reduced model of anaerobic digestion (AM2) which is a four-dimensional system of ordinary differential equations. The AM2 model is able to adequately capture the main dynamical behavior of the full anaerobic digestion model ADM1 and has the advantage that a complete analysis for the existence and local stability of its steady states is available. We describe its operating diagram, which is the bifurcation diagram which gives the behavior of the system with respect to the operating parameters represented by the dilution rate and the input concentrations of the substrates. This diagram, is very useful to understand the model from both the mathematical and biological points of view

Costless metabolic secretions as drivers of interspecies interactions in microbial ecosystems

Metabolic exchange mediates interactions among microbes, helping explain diversity in microbial communities. As these interactions often involve a fitness cost, it is unclear how stable cooperation can emerge. Here we use genome-scale metabolic models to investigate whether the release of “costless” metabolites (i.e. those that cause no fitness cost to the producer), can be a prominent driver of intermicrobial interactions. By performing over 2 million pairwise growth simulations of 24 species in a combinatorial assortment of environments, we identify a large space of metabolites that can be secreted without cost, thus generating ample cross-feeding opportunities. In addition to providing an atlas of putative interactions, we show that anoxic conditions can promote mutualisms by providing more opportunities for exchange of costless metabolites, resulting in an overrepresentation of stable ecological network motifs. These results may help identify interaction patterns in natural communities and inform the design of synthetic microbial consortia.We thank Dr. Niels Klitgord for pioneering ideas that inspired launch of this work. We are also grateful to David Bernstein, Joshua E. Goldford, Meghan Thommes, Demetrius DiMucci, and all members of the Segre Lab for helpful discussions. A.R.P. is supported by a National Academies of Sciences, Engineering, and Medicine Ford Foundation Predoctoral Fellowship and a Howard Hughes Medical Institute Gilliam Fellowship. This work was supported by funding from the Defense Advanced Research Projects Agency (purchase request no. HR0011515303, contract no. HR0011-15-C-0091), the U.S. Department of Energy (grants DE-SC0004962 and DE-SC0012627), the NIH (grants 5R01DE024468, R01GM121950, and Sub_P30DK036836_P&F), the National Science Foundation (grants 1457695 and NSFOCE-BSF 1635070), MURI Grant W911NF-12-1-0390, the Human Frontiers Science Program (grant RGP0020/2016), and the Boston University Inter-disciplinary Biomedical Research Office. (National Academies of Sciences, Engineering, and Medicine Ford Foundation Predoctoral Fellowship; Howard Hughes Medical Institute Gilliam Fellowship; HR0011515303 - Defense Advanced Research Projects Agency; HR0011-15-C-0091 - Defense Advanced Research Projects Agency; DE-SC0004962 - U.S. Department of Energy; DE-SC0012627 - U.S. Department of Energy; 5R01DE024468 - NIH; R01GM121950 - NIH; Sub_P30DK036836_PF - NIH; 1457695 - National Science Foundation; NSFOCE-BSF 1635070 - National Science Foundation; W911NF-12-1-0390 - MURI Grant; RGP0020/2016 - Human Frontiers Science Program; Boston University Inter-disciplinary Biomedical Research Office)Published versio

Atmosphere Behavior in Gas-Closed Mouse-Algal Systems: An Experimental and Modelling Study

A dual approach of mathematical modelling and laboratory experimentation aimed at examining the gas exchange characteristics of artificial animal/plant systems closed to the ambient atmosphere was initiated. The development of control techniques and management strategies for maintaining the atmospheric levels of carbon dioxide and oxygen at physiological levels is examined. A mathematical model simulating the atmospheric behavior in these systems was developed and an experimental gas closed system was constructed. These systems are described and preliminary results are presented

Stability of Cross-Feeding Polymorphisms in Microbial Communities

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cross-feeding, a relationship wherein one organism consumes metabolites excreted by another, is a ubiquitous feature of natural and clinically-relevant microbial communities and could be a key factor promoting diversity in extreme and/or nutrient-poor environments. However, it remains unclear how readily cross-feeding interactions form, and therefore our ability to predict their emergence is limited. In this paper we developed a mathematical model parameterized using data from the biochemistry and ecology of an E. coli cross-feeding laboratory system. The model accurately captures short-term dynamics of the two competitors that have been observed empirically and we use it to systematically explore the stability of cross-feeding interactions for a range of environmental conditions. We find that our simple system can display complex dynamics including multi-stable behavior separated by a critical point. Therefore whether cross-feeding interactions form depends on the complex interplay between density and frequency of the competitors as well as on the concentration of resources in the environment. Moreover, we find that subtly different environmental conditions can lead to dramatically different results regarding the establishment of cross-feeding, which could explain the apparently unpredictable between-population differences in experimental outcomes. We argue that mathematical models are essential tools for disentangling the complexities of cross-feeding interactions.IG was supported by a Natural Environment Research Council (NERC) Advanced Fellowship NE/E013007/3 and a European Research Council (ERC) Consolidator grant MathModExp 647292, MK was funded by a National Aeronautics and Space Administration (NASA) NPP Fellowship and NASA NNX12AD87G, IG and PR were funded by a Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/J010340/1, KS was supported by National Human Genome Research Institute (NHGRI) 2R01HG003328 - 07A1 and FR was supported by NASA NNX12AD87G. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

EvoBot: Towards a Robot-Chemostat for Culturing and Maintaining Microbial Fuel Cells (MFCs)

In this paper we present EvoBot, a RepRap open-source 3D-printer modified to operate like a robot for culturing and maintaining Microbial Fuel Cells (MFCs). EvoBot is a modular liquid handling robot that has been adapted to host MFCs in its experimental layer, gather data from the MFCs and react on the set thresholds based on a feedback loop. This type of robot-MFC interaction, based on the feedback loop mechanism, will enable us to study further the adaptability and stability of these systems. To date, EvoBot has automated the nurturing process of MFCs with the aim of controlling liquid delivery, which is akin to a chemostat. The chemostat is a well-known microbiology method for culturing bacterial cells under controlled conditions with continuous nutrient supply. EvoBot is perhaps the first pioneering attempt at functionalizing the 3D printing technology by combining it with the chemostat methods. In this paper, we will explore the experiments that EvoBot has carried out so far and how the platform has been optimised over the past two years

Optimization of light and nutrients supply to stabilize long-term industrial cultivation of metabolically engineered cyanobacteria: a model-based analysis

5partially_openopenBattaglino, Beatrice; Arduino, Alessandro; Pagliano, Cristina; Sforza, Eleonora; Bertucco, AlbertoBattaglino, Beatrice; Arduino, Alessandro; Pagliano, Cristina; Sforza, Eleonora; Bertucco, Albert

Optimization of Light and Nutrients Supply to Stabilize Long-Term Industrial Cultivation of Metabolically Engineered Cyanobacteria: A Model-Based Analysis

partially_open5noMetabolically engineered cyanobacteria are promising photosynthetic cell factories to produce valuable compounds in view of a bio-based industry. However, when the producer population is affected by a production burden, it usually experiences genetic instability leading to cells that lose the production capability, here defined as retro-mutants, which in the long-term take over the culture. Here we show that by exploitation of differences in nutrient and light use between these two phenotypes, in a continuous culture the operative conditions can be set to specifically select the producers. A mathematical model-based analysis used to investigate the effect of kinetic parameters shows that in specific combinations of their values, a continuous stirred-tank reactor (CSTR) can be operated to favor the producer's growth. The feasibility of the approach proposed is discussed in the context of literature data. On the basis of overall mass and energy balance analysis, a new approach to stabilize the producer phenotype in long-term industrial cultivation is proposed.embargoed_20220209Battaglino, Beatrice; Arduino, Alessandro; Pagliano, Cristina; Sforza, Eleonora; Bertucco, AlbertoBattaglino, Beatrice; Arduino, Alessandro; Pagliano, Cristina; Sforza, Eleonora; Bertucco, Albert

Degradation of Toluene and Trichloroethylene by Burkholderia cepacia G4 in Growth-Limited Fed-Batch Culture

Burkholderia (Pseudomonas) cepacia G4 was cultivated in a fed-batch bioreactor on either toluene or toluene plus trichloroethylene (TCE). The culture was allowed to reach a constant cell density under conditions in which the amount of toluene supplied equals the maintenance energy demand of the culture. Compared with toluene only, the presence of TCE at a toluene/TCE ratio of 2.3 caused a fourfold increase in the specific maintenance requirement for toluene from 22 to 94 nmol mg of cells (dry weight)-1 h-1. During a period of 3 weeks, approximately 65% of the incoming TCE was stably converted to unidentified products from which all three chlorine atoms were liberated. When toluene was subsequently omitted from the culture feed while TCE addition continued, mutants which were no longer able to grow on toluene or to degrade TCE appeared. These mutants were also unable to grow on phenol or m- or o-cresol but were still able to grow on catechol and benzoate. Plasmid analysis showed that the mutants had lost the plasmid involved in toluene monooxygenase formation (pTOM). Thus, although strain G4 is much less sensitive to TCE toxicity than methanotrophs, deleterious effects may still occur, namely, an increased maintenance energy demand in the presence of toluene and plasmid loss when no toluene is added.