Achieving Optimal Growth through Product Feedback Inhibition in Metabolism

Recent evidence suggests that the metabolism of some organisms, such as Escherichia coli, is remarkably efficient, producing close to the maximum amount of biomass per unit of nutrient consumed. This observation raises the question of what regulatory mechanisms enable such efficiency. Here, we propose that simple product-feedback inhibition by itself is capable of leading to such optimality. We analyze several representative metabolic modules—starting from a linear pathway and advancing to a bidirectional pathway and metabolic cycle, and finally to integration of two different nutrient inputs. In each case, our mathematical analysis shows that product-feedback inhibition is not only homeostatic but also, with appropriate feedback connections, can minimize futile cycling and optimize fluxes. However, the effectiveness of simple product-feedback inhibition comes at the cost of high levels of some metabolite pools, potentially associated with toxicity and osmotic imbalance. These large metabolite pool sizes can be restricted if feedback inhibition is ultrasensitive. Indeed, the multi-layer regulation of metabolism by control of enzyme expression, enzyme covalent modification, and allostery is expected to result in such ultrasensitive feedbacks. To experimentally test whether the qualitative predictions from our analysis of feedback inhibition apply to metabolic modules beyond linear pathways, we examine the case of nitrogen assimilation in E. coli, which involves both nutrient integration and a metabolic cycle. We find that the feedback regulation scheme suggested by our mathematical analysis closely aligns with the actual regulation of the network and is sufficient to explain much of the dynamical behavior of relevant metabolite pool sizes in nutrient-switching experiments

Food waste composting

The objective of this thesis was to increase our knowledge of issues relevant to process problems in large-scale composting. The investigations focused on acid-related process inhibition and the relationships between temperature, aeration, evaporation and the scale of the process. Three manuscripts are summarised in the thesis proper. The first investigated composting at different scales; at full-scale, in a 2 m high reactor and in a one-litre vessel. The process in the reactor resembled the full-scale process, but the theoretical calculations showed that the heat losses from the reactor were large. About 0.45 m of glass wool would be necessary to produce similar thermal properties in the reactor as in the full scale plant. Accumulation of acids was studied in the second investigation. Different amounts of active compost were used as a starting culture in rotating three-litre reactors, which were fed daily with fresh waste and water. In reactors with a large amount of starting culture, more than four times the daily feed, a well-functioning process with high temperature, high CO2 production and high pH was established. In reactors with a starting culture less than twice the daily feed, the composting process failed. The temperature was below 42 °C and the CO2 production was small. In these reactors the pH was low and organic acids accumulated. It was concluded that acid inhibition of fed-batch processes can be avoided if sufficient amounts of a good starting culture are used. In the third investigation, the combined effects of temperature and pH on the degradation were studied. Small samples of compost from the initial acidic phase were treated with sodium hydroxide to raise the pH. This resulted in high respiratory activity in samples at all pH levels at 36 °C and in those with pH over 6.5 at 46 °C. However, at 46 °C the activity was very low in samples with pH below 6.0. This shows that a combination of high temperature and low pH can inhibit the composting process. The influence of the composting temperature on the evaporation was also analysed. Simulations showed that the difference in evaporation at different temperatures was very small for the same degradation, although there were large variations in airflow. Finally, addition of water to compost is discussed. It is often necessary to add water when composting energy-rich substrates, since otherwise the process may be halted due to drying before the compost has stabilised

A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

Electro-extractive fermentation for efficient biohydrogen production

Electrodialysis, an electrochemical membrane technique, was found to prolong and enhance the production of biohydrogen and purified organic acids via the anaerobic fermentation of glucose by Escherichia coli. Through the design of a model electrodialysis medium using cationic buffer, pH was precisely controlled electrokinetically, i.e. by the regulated extraction of acidic products with coulombic efficiencies of organic acid recovery in the range 50–70% maintained over continuous 30-day experiments. Contrary to\ud previous reports, E. coli produced H2 after aerobic growth in minimal medium without inducers and with a mixture of organic acids dominated by butyrate. The selective separation of organic acids from fermentation provides a potential nitrogen-free carbon source for further biohydrogen production in a parallel photofermentation. A parallel study incorporated this fermentation system into an integrated biohydrogen refinery (IBR) for the conversion of organic waste to hydrogen and energy

Extended metabolic biosensor design for dynamic pathway regulation of cell factories

[EN] Transcription factor-based biosensors naturally occur in metabolic pathways to maintain cell growth and to provide a robust response to environmental fluctua-tions. Extended metabolic biosensors, i.e., the cascading of a bio-conversion pathway and a transcription factor (TF) responsive to the downstream effector metabolite, provide sensing capabilities beyond natural effectors for implement-ing context-aware synthetic genetic circuits and bio-observers. However, the engineering of such multi-step circuits is challenged by stability and robustness issues. In order to streamline the design of TF-based biosensors in metabolic pathways, here we investigate the response of a genetic circuit combining a TF-based extended metabolic biosensor with an antithetic integral circuit, a feed-back controller that achieves robustness against environmental fluctuations. The dynamic response of an extended biosensor-based regulated flavonoid pathway is analyzed in order to address the issues of biosensor tuning of the regulated pathway under industrial biomanufacturing operating constraints.This work is partially supported by grant MINECO/AEI and EU DPI2017-82896-C2-1-R. P.C. acknowledges support from the Universitat Politecnica de Valencia Talento Programme.Boada-Acosta, YF.; Vignoni, A.; Picó, J.; Carbonell, P. (2020). Extended metabolic biosensor design for dynamic pathway regulation of cell factories. iScience. 23(7):1-25. https://doi.org/10.1016/j.isci.2020.101305S125237Agrawal, D. K., Dolan, E. M., Hernandez, N. E., Blacklock, K. M., Khare, S. D., & Sontag, E. D. (2020). Mathematical Models of Protease-Based Enzymatic Biosensors. ACS Synthetic Biology, 9(2), 198-208. doi:10.1021/acssynbio.9b00279Arnold, F. H. (2017). Directed Evolution: Bringing New Chemistry to Life. Angewandte Chemie International Edition, 57(16), 4143-4148. doi:10.1002/anie.201708408Boada, Y., Vignoni, A., & Picó, J. (2017). Engineered Control of Genetic Variability Reveals Interplay among Quorum Sensing, Feedback Regulation, and Biochemical Noise. ACS Synthetic Biology, 6(10), 1903-1912. doi:10.1021/acssynbio.7b00087Boada, Y., Vignoni, A., & Picó, J. (2017). Multi-objective optimization for gene expression noise reduction in a synthetic gene circuit * *This work is partially supported by Spanish government and European Union (FEDER-CICYT DPI2014-55276-C5-1). Y.B. thanks grant FPI/2013-3242 of Universitat Politècnica de València, and also thanks the support from the Ayudas para movilidad dentro del Programa para la Formación de Personal Investigador (FPI) de la UPV para estancias 2016. A.V. thanks the Max Planck Society, the CSBD and the MPI-CBG. The authors are grateful to Prof. Dr. Ivo F. Sbalzarini for hosting Y.B in the MOSAIC Group for a research stay, also to Pietro Incadorna from the MOSAIC Group at CSBD for his help in the parallel algorithm implementation, and to Dr. Gilberto Reynoso-Meza from the PPGEPS at Pontifícia Universidade Católica do Paraná for his always helpful comments regarding the MOOD. IFAC-PapersOnLine, 50(1), 4472-4477. doi:10.1016/j.ifacol.2017.08.376Boada, Y., Vignoni, A., & Pico, J. (2020). Multiobjective Identification of a Feedback Synthetic Gene Circuit. IEEE Transactions on Control Systems Technology, 28(1), 208-223. doi:10.1109/tcst.2018.2885694Briat, C., Gupta, A., & Khammash, M. (2016). Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks. Cell Systems, 2(1), 15-26. doi:10.1016/j.cels.2016.01.004Briat, C., & Khammash, M. (2018). Perfect Adaptation and Optimal Equilibrium Productivity in a Simple Microbial Biofuel Metabolic Pathway Using Dynamic Integral Control. 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ACS Synthetic Biology, 9(3), 590-597. doi:10.1021/acssynbio.9b00451Doong, S. J., Gupta, A., & Prather, K. L. J. (2018). Layered dynamic regulation for improving metabolic pathway productivity inEscherichia coli. Proceedings of the National Academy of Sciences, 115(12), 2964-2969. doi:10.1073/pnas.1716920115Evans, C. R., Kempes, C. P., Price-Whelan, A., & Dietrich, L. E. P. (2020). Metabolic Heterogeneity and Cross-Feeding in Bacterial Multicellular Systems. Trends in Microbiology, 28(9), 732-743. doi:10.1016/j.tim.2020.03.008Gao, C., Xu, P., Ye, C., Chen, X., & Liu, L. (2019). Genetic Circuit-Assisted Smart Microbial Engineering. Trends in Microbiology, 27(12), 1011-1024. doi:10.1016/j.tim.2019.07.005Goldberg, A. P., Szigeti, B., Chew, Y. H., Sekar, J. A., Roth, Y. D., & Karr, J. R. (2018). Emerging whole-cell modeling principles and methods. Current Opinion in Biotechnology, 51, 97-102. doi:10.1016/j.copbio.2017.12.013Hsiao, V., Swaminathan, A., & Murray, R. M. (2018). Control Theory for Synthetic Biology: Recent Advances in System Characterization, Control Design, and Controller Implementation for Synthetic Biology. IEEE Control Systems, 38(3), 32-62. doi:10.1109/mcs.2018.2810459Huyett, L. M., Dassau, E., Zisser, H. C., & Doyle, F. J. (2018). Glucose Sensor Dynamics and the Artificial Pancreas: The Impact of Lag on Sensor Measurement and Controller Performance. IEEE Control Systems, 38(1), 30-46. doi:10.1109/mcs.2017.2766322Johnson, A. O., Gonzalez-Villanueva, M., Wong, L., Steinbüchel, A., Tee, K. L., Xu, P., & Wong, T. S. (2017). Design and application of genetically-encoded malonyl-CoA biosensors for metabolic engineering of microbial cell factories. Metabolic Engineering, 44, 253-264. doi:10.1016/j.ymben.2017.10.011Juminaga, D., Baidoo, E. E. K., Redding-Johanson, A. M., Batth, T. S., Burd, H., Mukhopadhyay, A., … Keasling, J. D. (2011). Modular Engineering of l-Tyrosine Production in Escherichia coli. Applied and Environmental Microbiology, 78(1), 89-98. doi:10.1128/aem.06017-11Koch, M., Pandi, A., Delépine, B., & Faulon, J.-L. (2018). A dataset of small molecules triggering transcriptional and translational cellular responses. Data in Brief, 17, 1374-1378. doi:10.1016/j.dib.2018.02.061LEONARD, E., YAN, Y., & KOFFAS, M. (2006). Functional expression of a P450 flavonoid hydroxylase for the biosynthesis of plant-specific hydroxylated flavonols in Escherichia coli. Metabolic Engineering, 8(2), 172-181. doi:10.1016/j.ymben.2005.11.001Lin, J.-L., Wagner, J. M., & Alper, H. S. (2017). Enabling tools for high-throughput detection of metabolites: Metabolic engineering and directed evolution applications. Biotechnology Advances, 35(8), 950-970. doi:10.1016/j.biotechadv.2017.07.005Liu, D., Mannan, A. A., Han, Y., Oyarzún, D. A., & Zhang, F. (2018). Dynamic metabolic control: towards precision engineering of metabolism. 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A quantitative study of the relationships between morphology, physiology and geldanamycin synthesis in submerged cultures of Streptomyces hygroscopicus var. geldanus

Microbially produced secondary metabolites such as antibiotics have tremendous economic importance. However, most are produced by filamentous organisms which exhibit diverse growth patterns presenting challenges for industrial fermentation. There are many factors affecting secondary metabolite production which concomitantly impact on morphology, thus it is difficult to distinguish the key driver for productivity. Streptomyces spp. is a genus of filamentous organisms that together synthesise over 4000 bioactive compounds. Streptomyces hygroscopicus var. geldanus produces the secondary metabolite geldanamycin, a novel chemotherapeutic compound, in submerged fermentation. This organism represents an ideal system for experimentation in order to elucidate the relationships between morphology, physiology and secondary metabolite production. The effects of a variety of microbiological (inoculum size), physical (glass beads) and chemical (surfactants, calcium ions, magnesium ions) factors on morphological development were examined as part of this study. Inclusion of the divalent cations magnesium or calcium was demonstrated to alter the cell surface hydrophobicity of the organism, provoking dispersion or aggregation of cells respectively, and stimulating great disparity in geldanamycin yields. Indeed, in all instances, morphology was found to impact considerably on secondary metabolite formation, with smaller pellet sizes optimal for geldanamycin synthesis. Investigation of the respiration rate of Streptomyces hygroscopicus var. geldanus revealed that a linear relationship existed between this parameter and geldanamycin production. Submerged cultures consisting primarily of small pellets, less than 0.5mm in diameter, were more metabolically active and concomitantly produced more geldanamycin. Nonetheless, it was also demonstrated that other explicit factors exist which do not affect morphology or respiration but regulate geldanamycin synthesis through feedback inhibition of the direct metabolic pathway. This study has demonstrated that, in Streptomyces hygroscopicus var. geldanus, the bulk of factors that affect morphology impact significantly on respiration, and it is this parameter that is the key driver of secondary metabolite production. This case study provides new insights into the regulation of geldanamycin production in Streptomyces hygroscopicus var. geldanus and provides a basis for elucidation of the relationships between morphology, physiology and secondary metabolism in other filamentous micro-organisms

Towards bacterial strains overproducing L-tryptophan and other aromatics by metabolic engineering

The original publication is available at www.springerlink.com.ArticleApplied Microbiology and Biotechnology. 69(6): 615-626 (2006)journal articl

(Im) Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

Background: Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results: This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions: A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering