1
|
Muñoz-Gómez SA. The energetic costs of cellular complexity in evolution. Trends Microbiol 2024; 32:746-755. [PMID: 38307786 DOI: 10.1016/j.tim.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 02/04/2024]
Abstract
The evolutionary history of cells has been marked by drastic increases in complexity. Some hypothesize that such cellular complexification requires a massive energy flux as the origin of new features is hypothetically more energetically costly than their evolutionary maintenance. However, it remains unclear how increases in cellular complexity demand more energy. I propose that the early evolution of new genes with weak functions imposes higher energetic costs by overexpression before their functions are evolutionarily refined. In the long term, the accumulation of new genes deviates resources away from growth and reproduction. Accrued cellular complexity further requires additional infrastructure for its maintenance. Altogether, this suggests that larger and more complex cells are defined by increased survival but lower reproductive capacity.
Collapse
|
2
|
Patel A, McGrosso D, Hefner Y, Campeau A, Sastry AV, Maurya S, Rychel K, Gonzalez DJ, Palsson BO. Proteome allocation is linked to transcriptional regulation through a modularized transcriptome. Nat Commun 2024; 15:5234. [PMID: 38898010 PMCID: PMC11187210 DOI: 10.1038/s41467-024-49231-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigate whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions can be modularized in the same way to reveal novel relationships between their compositions. We find that; (1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, (2) the modules in the proteome often represent combinations of modules from the transcriptome, (3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and (4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria.
Collapse
Affiliation(s)
- Arjun Patel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Dominic McGrosso
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Ying Hefner
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Anaamika Campeau
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Anand V Sastry
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Svetlana Maurya
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Kevin Rychel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - David J Gonzalez
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, 92093, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA.
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs, Lyngby, Denmark.
| |
Collapse
|
3
|
Lara AR, Utrilla J, Martínez LM, Krausch N, Kaspersetz L, Hidalgo D, Cruz-Bournazou N, Neubauer P, Sigala JC, Gosset G, Büchs J. Recombinant protein expression in proteome-reduced cells under aerobic and oxygen-limited regimes. Biotechnol Bioeng 2024; 121:1216-1230. [PMID: 38178599 DOI: 10.1002/bit.28645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 11/18/2023] [Accepted: 12/17/2023] [Indexed: 01/06/2024]
Abstract
Industrial cultures are hindered by the physiological complexity of the host and the limited mass transfer capacity of conventional bioreactors. In this study, a minimal cell approach was combined with genetic devices to overcome such issues. A flavin mononucleotide-based fluorescent protein (FbFP) was expressed in a proteome-reduced Escherichia coli (PR). When FbFP was expressed from a constitutive protein generator (CPG), the PR strain produced 47% and 35% more FbFP than its wild type (WT), in aerobic or oxygen-limited regimes, respectively. Metabolic and expression models predicted more efficient biomass formation at higher fluxes to FbFP, in agreement with these results. A microaerobic protein generator (MPG) and a microaerobic transcriptional cascade (MTC) were designed to induce FbFP expression upon oxygen depletion. The FbFP fluorescence using the MTC in the PR strain was 9% higher than that of the WT bearing the CPG under oxygen limitation. To further improve the PR strain, the pyruvate dehydrogenase complex regulator gene was deleted, and the Vitreoscilla hemoglobin was expressed. Compared to oxygen-limited cultures of the WT, the engineered strains increased the FbFP expression more than 50% using the MTC. Therefore, the designed expression systems can be a valuable alternative for industrial cultivations.
Collapse
Affiliation(s)
- Alvaro R Lara
- Department of Biological and Chemical Engineering, Aarhus University, Aarhus, Denmark
| | - Jose Utrilla
- Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | - Luz María Martínez
- Departamento de Ingeniería Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, México
| | - Niels Krausch
- Chair of Bioprocess Engineering, Technische Universität Berlin, Berlin, Germany
| | - Lucas Kaspersetz
- Chair of Bioprocess Engineering, Technische Universität Berlin, Berlin, Germany
| | - David Hidalgo
- Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | | | - Peter Neubauer
- Chair of Bioprocess Engineering, Technische Universität Berlin, Berlin, Germany
| | - Juan-Carlos Sigala
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana, Ciudad de México, México
| | - Guillermo Gosset
- Departamento de Ingeniería Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, México
| | - Jochen Büchs
- Chair of Biochemical Engineering (AVT.BioVT), RWTH Aachen University, Aachen, Germany
| |
Collapse
|
4
|
Heffernan JK, Mahamkali V, Valgepea K, Marcellin E, Nielsen LK. Analytical tools for unravelling the metabolism of gas-fermenting Clostridia. Curr Opin Biotechnol 2022; 75:102700. [PMID: 35240422 DOI: 10.1016/j.copbio.2022.102700] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/24/2022] [Accepted: 02/05/2022] [Indexed: 12/23/2022]
Abstract
Acetogens harness the Wood-Ljungdahl Pathway, a unique metabolic pathway for C1 capture close to the thermodynamic limit. Gas fermentation using acetogens is already used for CO-to-ethanol conversion at industrial-scale and has the potential to valorise a range of C1 and waste substrates to short-chain and medium-chain carboxylic acids and alcohols. Advances in analytical quantification and metabolic modelling have helped guide industrial gas fermentation designs. Further advances in the measurements of difficult to measure metabolites are required to improve kinetic modelling and understand the regulation of acetogen metabolism. This will help guide future synthetic biology designs needed to realise the full potential of gas fermentation in stimulating a circular bioeconomy.
Collapse
Affiliation(s)
- James K Heffernan
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Vishnu Mahamkali
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Kaspar Valgepea
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu 50411, Estonia
| | - Esteban Marcellin
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia; Queensland Node of Metabolomics Australia, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Lars K Nielsen
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia; Queensland Node of Metabolomics Australia, The University of Queensland, Brisbane, QLD 4072, Australia; The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby DK-2800, Denmark.
| |
Collapse
|
5
|
Intelligent host engineering for metabolic flux optimisation in biotechnology. Biochem J 2021; 478:3685-3721. [PMID: 34673920 PMCID: PMC8589332 DOI: 10.1042/bcj20210535] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 09/22/2021] [Accepted: 09/24/2021] [Indexed: 12/13/2022]
Abstract
Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.
Collapse
|
6
|
Ziegler M, Zieringer J, Döring CL, Paul L, Schaal C, Takors R. Engineering of a robust Escherichia coli chassis and exploitation for large-scale production processes. Metab Eng 2021; 67:75-87. [PMID: 34098100 DOI: 10.1016/j.ymben.2021.05.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 05/30/2021] [Accepted: 05/31/2021] [Indexed: 11/28/2022]
Abstract
In large-scale bioprocesses microbes are exposed to heterogeneous substrate availability reducing the overall process performance. A series of deletion strains was constructed from E. coli MG1655 aiming for a robust phenotype in heterogeneous fermentations with transient starvation. Deletion targets were hand-picked based on a list of genes derived from previous large-scale simulation runs. Each gene deletion was conducted on the premise of strict neutrality towards growth parameters in glucose minimal medium. The final strain of the series, named E. coli RM214, was cultivated continuously in an STR-PFR (stirred tank reactor - plug flow reactor) scale-down reactor. The scale-down reactor system simulated repeated passages through a glucose starvation zone. When exposed to nutrient gradients, E. coli RM214 had a significantly lower maintenance coefficient than E. coli MG1655 (Δms = 0.038 gGlucose/gCDW/h, p < 0.05). In an exemplary protein production scenario E. coli RM214 remained significantly more productive than E. coli MG1655 reaching 44% higher eGFP yield after 28 h of STR-PFR cultivation. This study developed E. coli RM214 as a robust chassis strain and demonstrated the feasibility of engineering microbial hosts for large-scale applications.
Collapse
Affiliation(s)
- Martin Ziegler
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| | - Julia Zieringer
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| | - Clarissa-Laura Döring
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| | - Liv Paul
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| | - Christoph Schaal
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| | - Ralf Takors
- University of Stuttgart - Institute of Biochemical Engineering, Allmandring 31, 70569, Stuttgart, Germany.
| |
Collapse
|
7
|
de la Cruz M, Ramírez EA, Sigala JC, Utrilla J, Lara AR. Plasmid DNA Production in Proteome-Reduced Escherichia coli. Microorganisms 2020; 8:microorganisms8091444. [PMID: 32967123 PMCID: PMC7563601 DOI: 10.3390/microorganisms8091444] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/05/2020] [Accepted: 09/11/2020] [Indexed: 11/16/2022] Open
Abstract
The design of optimal cell factories requires engineering resource allocation for maximizing product synthesis. A recently developed method to maximize the saving in cell resources released 0.5% of the proteome of Escherichia coli by deleting only three transcription factors. We assessed the capacity for plasmid DNA (pDNA) production in the proteome-reduced strain in a mineral medium, lysogeny, and terrific broths. In all three cases, the pDNA yield from biomass was between 33 and 53% higher in the proteome-reduced than in its wild type strain. When cultured in fed-batch mode in shake-flask, the proteome-reduced strain produced 74.8 mg L-1 pDNA, which was four times greater than its wild-type strain. Nevertheless, the pDNA supercoiled fraction was less than 60% in all cases. Deletion of recA increased the pDNA yields in the wild type, but not in the proteome-reduced strain. Furthermore, recA mutants produced a higher fraction of supercoiled pDNA, compared to their parents. These results show that the novel proteome reduction approach is a promising starting point for the design of improved pDNA production hosts.
Collapse
Affiliation(s)
- Mitzi de la Cruz
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana-Cuajimalpa, Mexico City 05348, Mexico; (M.d.l.C.); (E.A.R.); (J.-C.S.)
| | - Elisa A. Ramírez
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana-Cuajimalpa, Mexico City 05348, Mexico; (M.d.l.C.); (E.A.R.); (J.-C.S.)
| | - Juan-Carlos Sigala
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana-Cuajimalpa, Mexico City 05348, Mexico; (M.d.l.C.); (E.A.R.); (J.-C.S.)
| | - José Utrilla
- Systems and Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico;
| | - Alvaro R. Lara
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana-Cuajimalpa, Mexico City 05348, Mexico; (M.d.l.C.); (E.A.R.); (J.-C.S.)
- Correspondence:
| |
Collapse
|
8
|
Proteome reallocation from amino acid biosynthesis to ribosomes enables yeast to grow faster in rich media. Proc Natl Acad Sci U S A 2020; 117:21804-21812. [PMID: 32817546 PMCID: PMC7474676 DOI: 10.1073/pnas.1921890117] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
The yeast Saccharomyces cerevisiae is a well-studied organism, which is used as a model organism for studying eukaryal biology and as a cell factory for the production of fuels, chemicals, and pharmaceuticals. For both applications, the way that the cell utilizes its finite protein resource and how those inherent trade-offs manifest themselves is of interest, not least for their impact on cellular metabolism. Here we elucidate how alterations of protein-allocation allow for S. cerevisiae to increase its growth rate. Our results on cellular proteome-allocation may aid the engineering of more efficient strains in industrial biotechnology as well as improve our understanding toward phenotypes of cancer cells that grow faster than normal cells. Several recent studies have shown that the concept of proteome constraint, i.e., the need for the cell to balance allocation of its proteome between different cellular processes, is essential for ensuring proper cell function. However, there have been no attempts to elucidate how cells’ maximum capacity to grow depends on protein availability for different cellular processes. To experimentally address this, we cultivated Saccharomyces cerevisiae in bioreactors with or without amino acid supplementation and performed quantitative proteomics to analyze global changes in proteome allocation, during both anaerobic and aerobic growth on glucose. Analysis of the proteomic data implies that proteome mass is mainly reallocated from amino acid biosynthetic processes into translation, which enables an increased growth rate during supplementation. Similar findings were obtained from both aerobic and anaerobic cultivations. Our findings show that cells can increase their growth rate through increasing its proteome allocation toward the protein translational machinery.
Collapse
|
9
|
RNAi expression tuning, microfluidic screening, and genome recombineering for improved protein production in Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 2019; 116:9324-9332. [PMID: 31000602 DOI: 10.1073/pnas.1820561116] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
The cellular machinery that supports protein synthesis and secretion lies at the foundation of cell factory-centered protein production. Due to the complexity of such cellular machinery, the challenge in generating a superior cell factory is to fully exploit the production potential by finding beneficial targets for optimized strains, which ideally could be used for improved secretion of other proteins. We focused on an approach in the yeast Saccharomyces cerevisiae that allows for attenuation of gene expression, using RNAi combined with high-throughput microfluidic single-cell screening for cells with improved protein secretion. Using direct experimental validation or enrichment analysis-assisted characterization of systematically introduced RNAi perturbations, we could identify targets that improve protein secretion. We found that genes with functions in cellular metabolism (YDC1, AAD4, ADE8, and SDH1), protein modification and degradation (VPS73, KTR2, CNL1, and SSA1), and cell cycle (CDC39), can all impact recombinant protein production when expressed at differentially down-regulated levels. By establishing a workflow that incorporates Cas9-mediated recombineering, we demonstrated how we could tune the expression of the identified gene targets for further improved protein production for specific proteins. Our findings offer a high throughput and semirational platform design, which will improve not only the production of a desired protein but even more importantly, shed additional light on connections between protein production and other cellular processes.
Collapse
|
10
|
Noack S, Baumgart M. Communities of Niche-Optimized Strains: Small-Genome Organism Consortia in Bioproduction. Trends Biotechnol 2019; 37:126-139. [DOI: 10.1016/j.tibtech.2018.07.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 07/16/2018] [Accepted: 07/17/2018] [Indexed: 12/30/2022]
|
11
|
Stalidzans E, Seiman A, Peebo K, Komasilovs V, Pentjuss A. Model-based metabolism design: constraints for kinetic and stoichiometric models. Biochem Soc Trans 2018; 46:261-267. [PMID: 29472367 PMCID: PMC5906704 DOI: 10.1042/bst20170263] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 12/19/2017] [Accepted: 01/01/2018] [Indexed: 02/06/2023]
Abstract
The implementation of model-based designs in metabolic engineering and synthetic biology may fail. One of the reasons for this failure is that only a part of the real-world complexity is included in models. Still, some knowledge can be simplified and taken into account in the form of optimization constraints to improve the feasibility of model-based designs of metabolic pathways in organisms. Some constraints (mass balance, energy balance, and steady-state assumption) serve as a basis for many modelling approaches. There are others (total enzyme activity constraint and homeostatic constraint) proposed decades ago, but which are frequently ignored in design development. Several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance. Constraints for kinetic and stoichiometric models are grouped according to their applicability preconditions in (1) general constraints, (2) organism-level constraints, and (3) experiment-level constraints. General constraints are universal and are applicable for any system. Organism-level constraints are applicable for biological systems and usually are organism-specific, but these constraints can be applied without information about experimental conditions. To apply experimental-level constraints, peculiarities of the organism and the experimental set-up have to be taken into account to calculate the values of constraints. The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed.
Collapse
Affiliation(s)
- Egils Stalidzans
- Biosystems Group, Latvia University of Agriculture, Liela Iela 2, LV 3001 Jelgava, Latvia
| | - Andrus Seiman
- Center of Food and Fermentation Technologies, Akadeemia tee 15A, 12618 Tallinn, Estonia
| | - Karl Peebo
- Center of Food and Fermentation Technologies, Akadeemia tee 15A, 12618 Tallinn, Estonia
| | - Vitalijs Komasilovs
- Biosystems Group, Latvia University of Agriculture, Liela Iela 2, LV 3001 Jelgava, Latvia
| | - Agris Pentjuss
- Biosystems Group, Latvia University of Agriculture, Liela Iela 2, LV 3001 Jelgava, Latvia
| |
Collapse
|
12
|
Wortel MT, Noor E, Ferris M, Bruggeman FJ, Liebermeister W. Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield. PLoS Comput Biol 2018; 14:e1006010. [PMID: 29451895 PMCID: PMC5847312 DOI: 10.1371/journal.pcbi.1006010] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 03/12/2018] [Accepted: 01/30/2018] [Indexed: 11/25/2022] Open
Abstract
Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.
Collapse
Affiliation(s)
- Meike T. Wortel
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway
- Systems Bioinformatics Section, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit, Amsterdam, The Netherlands
| | - Elad Noor
- Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule, Zürich, Switzerland
| | - Michael Ferris
- Computer Sciences Department and Wisconsin Institute for Discovery, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Frank J. Bruggeman
- Systems Bioinformatics Section, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit, Amsterdam, The Netherlands
| | - Wolfram Liebermeister
- INRA, UR1404, MaIAGE, Université Paris-Saclay, Jouy-en-Josas, France
- Institute of Biochemistry, Charité – Universitätsmedizin Berlin, Berlin, Germany
| |
Collapse
|
13
|
Campbell K, Xia J, Nielsen J. The Impact of Systems Biology on Bioprocessing. Trends Biotechnol 2017; 35:1156-1168. [DOI: 10.1016/j.tibtech.2017.08.011] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 08/28/2017] [Accepted: 08/29/2017] [Indexed: 12/16/2022]
|
14
|
|
15
|
Martínez-García E, de Lorenzo V. The quest for the minimal bacterial genome. Curr Opin Biotechnol 2016; 42:216-224. [DOI: 10.1016/j.copbio.2016.09.001] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 09/01/2016] [Accepted: 09/02/2016] [Indexed: 01/09/2023]
|
16
|
Yang L, Ma D, Ebrahim A, Lloyd CJ, Saunders MA, Palsson BO. solveME: fast and reliable solution of nonlinear ME models. BMC Bioinformatics 2016; 17:391. [PMID: 27659412 PMCID: PMC5034503 DOI: 10.1186/s12859-016-1240-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 09/06/2016] [Indexed: 11/21/2022] Open
Abstract
Background Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Results Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints. Conclusions Just as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1240-1) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Laurence Yang
- Department of Bioengineering, University of California at San Diego, La Jolla, 92093, CA, USA
| | - Ding Ma
- Department of Management Science and Engineering, Stanford University, Stanford, 94305, CA, USA
| | - Ali Ebrahim
- Department of Bioengineering, University of California at San Diego, La Jolla, 92093, CA, USA
| | - Colton J Lloyd
- Department of Bioengineering, University of California at San Diego, La Jolla, 92093, CA, USA
| | - Michael A Saunders
- Department of Management Science and Engineering, Stanford University, Stanford, 94305, CA, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California at San Diego, La Jolla, 92093, CA, USA. .,Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, Kongens Lyngby, DK-2800, Denmark.
| |
Collapse
|
17
|
O’Brien EJ, Utrilla J, Palsson BO. Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments. PLoS Comput Biol 2016; 12:e1004998. [PMID: 27351952 PMCID: PMC4924638 DOI: 10.1371/journal.pcbi.1004998] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 05/25/2016] [Indexed: 12/14/2022] Open
Abstract
The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change. An overarching endeavor in systems biology is to characterize and understand the allocation of an organism’s proteome. Common approaches to characterize proteome allocation are based on annotations of protein functions or transcriptional regulatory targets. Here, we develop a novel approach based on model-predicted proteome utilization. This approach reveals that in many environments, a large fraction of the proteome is unused. Unused protein expression is known to incur costs on organismal fitness. We show that changes in the allocation of the proteome to used versus unused fractions can account for the variability in growth rates observed across environments and is a common mechanism to increase growth rates in laboratory evolution experiments. We compare our approach to classify the proteome based on model-predicted utilization to more traditional approaches to reveal biological functions and transcriptional regulators underlying the expression of unused protein. Expression of these functions may reflect ecological trade-offs between growth, nutrient-readiness, and stress resistance.
Collapse
Affiliation(s)
- Edward J. O’Brien
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
- Bioinformatics and Systems Biology program, University of California, San Diego, La Jolla, California, United States of America
| | - Jose Utrilla
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
- Centro de Ciencias Genómicas. Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
| | - Bernhard O. Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
- * E-mail:
| |
Collapse
|