51
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Stump SM, Klausmeier CA. Competition and coexistence between a syntrophic consortium and a metabolic generalist, and its effect on productivity. J Theor Biol 2016; 404:348-360. [DOI: 10.1016/j.jtbi.2016.06.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 05/24/2016] [Accepted: 06/15/2016] [Indexed: 11/24/2022]
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52
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Solé R. Synthetic transitions: towards a new synthesis. Philos Trans R Soc Lond B Biol Sci 2016; 371:20150438. [PMID: 27431516 PMCID: PMC4958932 DOI: 10.1098/rstb.2015.0438] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2016] [Indexed: 12/17/2022] Open
Abstract
The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general framework to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics.This article is part of the themed issue 'The major synthetic evolutionary transitions'.
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Affiliation(s)
- Ricard Solé
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 88, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Pg Maritim de la Barceloneta 37, 08003 Barcelona, Spain Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
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53
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Affiliation(s)
- Eric Higgs
- School of Environmental Studies; University of Victoria; Victoria British Columbia V8P 5C2 Canada
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54
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Kosina SM, Danielewicz MA, Mohammed M, Ray J, Suh Y, Yilmaz S, Singh AK, Arkin AP, Deutschbauer AM, Northen TR. Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism. ACS Synth Biol 2016; 5:569-76. [PMID: 26885935 DOI: 10.1021/acssynbio.5b00236] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.
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Affiliation(s)
- Suzanne M. Kosina
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Megan A. Danielewicz
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Mujahid Mohammed
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Jayashree Ray
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Yumi Suh
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Suzan Yilmaz
- Sandia National Laboratory, Livermore, California 94550, United States
| | - Anup K. Singh
- Sandia National Laboratory, Livermore, California 94550, United States
| | - Adam P. Arkin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- University of California Berkeley, Berkeley, California 94720, United States
| | - Adam M. Deutschbauer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Trent R. Northen
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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55
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Cordero OX, Datta MS. Microbial interactions and community assembly at microscales. Curr Opin Microbiol 2016; 31:227-234. [PMID: 27232202 DOI: 10.1016/j.mib.2016.03.015] [Citation(s) in RCA: 191] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/28/2016] [Accepted: 03/30/2016] [Indexed: 11/16/2022]
Abstract
In most environments, microbial interactions take place within microscale cell aggregates. At the scale of these aggregates (∼100μm), interactions are likely to be the dominant driver of population structure and dynamics. In particular, organisms that exploit interspecific interactions to increase ecological performance often co-aggregate. Conversely, organisms that antagonize each other will tend to spatially segregate, creating distinct micro-communities and increased diversity at larger length scales. We argue that, in order to understand the role that biological interactions play in microbial community function, it is necessary to study microscale spatial organization with enough throughput to measure statistical associations between taxa and possible alternative community states. We conclude by proposing strategies to tackle this challenge.
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Affiliation(s)
- Otto X Cordero
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Manoshi S Datta
- Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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56
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Shin JE, Lin C, Lim HN. Horizontal transfer of DNA methylation patterns into bacterial chromosomes. Nucleic Acids Res 2016; 44:4460-71. [PMID: 27084942 PMCID: PMC4872104 DOI: 10.1093/nar/gkw230] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2016] [Accepted: 03/29/2016] [Indexed: 12/21/2022] Open
Abstract
Horizontal gene transfer (HGT) is the non-inherited acquisition of novel DNA sequences. HGT is common and important in bacteria because it enables the rapid generation of new phenotypes such as antibiotic resistance. Here we show that in vivo and in vitro DNA methylation patterns can be horizontally transferred into bacterial chromosomes to program cell phenotypes. The experiments were performed using a synthetic system in Escherichia coli where different DNA methylation patterns within the cis-regulatory sequence of the agn43 gene turn on or off a fluorescent reporter (CFP). With this system we demonstrated that DNA methylation patterns not only accompany the horizontal transfer of genes into the bacterial cytoplasm but can be transferred into chromosomes by: (i) bacteriophage P1 transduction; and (ii) transformation of extracellular synthetic DNA. We also modified the experimental system by replacing CFP with the SgrS small RNA, which regulates glucose and methyl α-D-glucoside uptake, and showed that horizontally acquired DNA methylation patterns can increase or decrease cell fitness. That is, horizontally acquired DNA methylation patterns can result in the selection for and against cells that have HGT. Findings from these proof-of-concept experiments have applications in synthetic biology and potentially broad implications for bacterial adaptation and evolution.
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Affiliation(s)
- Jung-Eun Shin
- Department of Integrative Biology, University of California Berkeley, CA 94720-3140, USA
| | - Chris Lin
- Department of Integrative Biology, University of California Berkeley, CA 94720-3140, USA
| | - Han N Lim
- Department of Integrative Biology, University of California Berkeley, CA 94720-3140, USA
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57
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Johns NI, Blazejewski T, Gomes AL, Wang HH. Principles for designing synthetic microbial communities. Curr Opin Microbiol 2016; 31:146-153. [PMID: 27084981 DOI: 10.1016/j.mib.2016.03.010] [Citation(s) in RCA: 159] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 03/19/2016] [Accepted: 03/21/2016] [Indexed: 01/21/2023]
Abstract
Advances in synthetic biology to build microbes with defined and controllable properties are enabling new approaches to design and program multispecies communities. This emerging field of synthetic ecology will be important for many areas of biotechnology, bioenergy and bioremediation. This endeavor draws upon knowledge from synthetic biology, systems biology, microbial ecology and evolution. Fully realizing the potential of this discipline requires the development of new strategies to control the intercellular interactions, spatiotemporal coordination, robustness, stability and biocontainment of synthetic microbial communities. Here, we review recent experimental, analytical and computational advances to study and build multi-species microbial communities with defined functions and behavior for various applications. We also highlight outstanding challenges and future directions to advance this field.
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Affiliation(s)
- Nathan I Johns
- Department of Systems Biology, Columbia University Medical Center, New York, USA; Integrated Program in Cellular, Molecular and Biomedical Studies, Columbia University Medical Center, New York, USA
| | - Tomasz Blazejewski
- Department of Systems Biology, Columbia University Medical Center, New York, USA; Integrated Program in Cellular, Molecular and Biomedical Studies, Columbia University Medical Center, New York, USA
| | - Antonio Lc Gomes
- Department of Systems Biology, Columbia University Medical Center, New York, USA
| | - Harris H Wang
- Department of Systems Biology, Columbia University Medical Center, New York, USA; Department of Pathology and Cell Biology, Columbia University Medical Center, New York, USA.
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58
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Widder S, Allen RJ, Pfeiffer T, Curtis TP, Wiuf C, Sloan WT, Cordero OX, Brown SP, Momeni B, Shou W, Kettle H, Flint HJ, Haas AF, Laroche B, Kreft JU, Rainey PB, Freilich S, Schuster S, Milferstedt K, van der Meer JR, Groβkopf T, Huisman J, Free A, Picioreanu C, Quince C, Klapper I, Labarthe S, Smets BF, Wang H, Soyer OS. Challenges in microbial ecology: building predictive understanding of community function and dynamics. ISME JOURNAL 2016; 10:2557-2568. [PMID: 27022995 PMCID: PMC5113837 DOI: 10.1038/ismej.2016.45] [Citation(s) in RCA: 377] [Impact Index Per Article: 47.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Revised: 02/12/2016] [Accepted: 02/22/2016] [Indexed: 12/21/2022]
Abstract
The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
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Affiliation(s)
- Stefanie Widder
- CUBE, Department of Microbiology and Ecosystem Science, University of Vienna, Vienna, Austria
| | - Rosalind J Allen
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, UK
| | - Thomas Pfeiffer
- New Zealand Institute for Advanced Study, Massey University, Auckland, New Zealand
| | - Thomas P Curtis
- School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, UK
| | - Carsten Wiuf
- Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - William T Sloan
- Infrastructure and Environment Research Division, School of Engineering, University of Glasgow, Glasgow, UK
| | - Otto X Cordero
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sam P Brown
- Centre for Immunity, Infection and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Babak Momeni
- Department of Biology, Boston College, Chestnut Hill, MA, USA.,Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wenying Shou
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Helen Kettle
- Biomathematics and Statistics Scotland, Edinburgh, UK
| | - Harry J Flint
- Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK
| | - Andreas F Haas
- Biology Department, San Diego State University, San Diego, CA, USA
| | - Béatrice Laroche
- Département de Mathématiques Informatiques Appliquées, INRA, Jouy-en-Josas, France
| | | | - Paul B Rainey
- New Zealand Institute for Advanced Study, Massey University, Auckland, New Zealand
| | - Shiri Freilich
- Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Stefan Schuster
- Department of Bioinformatics, Friedrich-Schiller-University Jena, Jena, Germany
| | - Kim Milferstedt
- INRA, UR0050, Laboratoire de Biotechnologie de l'Environnement, Narbonne, France
| | - Jan R van der Meer
- Department of Fundamental Microbiology, Université de Lausanne, Lausanne, Switzerland
| | - Tobias Groβkopf
- School of Life Sciences, The University of Warwick, Coventry, UK
| | - Jef Huisman
- Department of Aquatic Microbiology, University of Amsterdam, Amsterdam, The Netherlands
| | - Andrew Free
- Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Science, University of Edinburgh, Edinburgh, UK
| | - Cristian Picioreanu
- Department of Biotechnology, Delft University of Technology, Delft, The Netherlands
| | | | - Isaac Klapper
- Department of Mathematics, Temple University, Philadelphia, PA, USA
| | - Simon Labarthe
- Département de Mathématiques Informatiques Appliquées, INRA, Jouy-en-Josas, France
| | - Barth F Smets
- Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Harris Wang
- Department of Systems Biology, Columbia University, New York, NY, USA
| | | | - Orkun S Soyer
- School of Life Sciences, The University of Warwick, Coventry, UK
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59
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Johnson WM, Kido Soule MC, Kujawinski EB. Evidence for quorum sensing and differential metabolite production by a marine bacterium in response to DMSP. ISME JOURNAL 2016; 10:2304-16. [PMID: 26882264 PMCID: PMC4989321 DOI: 10.1038/ismej.2016.6] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 12/17/2015] [Accepted: 12/24/2015] [Indexed: 11/09/2022]
Abstract
Microbes, the foundation of the marine foodweb, do not function in isolation, but rather rely on molecular level interactions among species to thrive. Although certain types of interactions between autotrophic and heterotrophic microorganisms have been well documented, the role of specific organic molecules in regulating inter-species relationships and supporting growth are only beginning to be understood. Here, we examine one such interaction by characterizing the metabolic response of a heterotrophic marine bacterium, Ruegeria pomeroyi DSS-3, to growth on dimethylsulfoniopropionate (DMSP), an abundant organosulfur metabolite produced by phytoplankton. When cultivated on DMSP, R. pomeroyi synthesized a quorum-sensing molecule, N-(3-oxotetradecanoyl)-l-homoserine lactone, at significantly higher levels than during growth on propionate. Concomitant with the production of a quorum-sensing molecule, we observed differential production of intra- and extracellular metabolites including glutamine, vitamin B2 and biosynthetic intermediates of cyclic amino acids. Our metabolomics data indicate that R. pomeroyi changes regulation of its biochemical pathways in a manner that is adaptive for a cooperative lifestyle in the presence of DMSP, in anticipation of phytoplankton-derived nutrients and higher microbial density. This behavior is likely to occur on sinking marine particles, indicating that this response may impact the fate of organic matter.
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Affiliation(s)
- Winifred M Johnson
- MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering, Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Melissa C Kido Soule
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Elizabeth B Kujawinski
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
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60
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Hosoda K, Tsuda S, Kadowaki K, Nakamura Y, Nakano T, Ishii K. Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems. Biosystems 2015; 140:28-34. [PMID: 26747638 DOI: 10.1016/j.biosystems.2015.12.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Revised: 12/10/2015] [Accepted: 12/11/2015] [Indexed: 11/15/2022]
Abstract
Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms.
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Affiliation(s)
- Kazufumi Hosoda
- Institute for Academic Initiatives, Osaka University, Suita, Osaka, Japan.
| | - Soichiro Tsuda
- WestCHEM, School of Chemistry, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Kohmei Kadowaki
- Graduate School of Human and Environmental Studies, Kyoto University, Kyoto, Japan
| | - Yutaka Nakamura
- Institute for Academic Initiatives, Osaka University, Suita, Osaka, Japan
| | - Tadashi Nakano
- Institute for Academic Initiatives, Osaka University, Suita, Osaka, Japan
| | - Kojiro Ishii
- Institute for Academic Initiatives, Osaka University, Suita, Osaka, Japan
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61
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Dorado-Morales P, Vilanova C, P Garay C, Martí JM, Porcar M. Unveiling Bacterial Interactions through Multidimensional Scaling and Dynamics Modeling. Sci Rep 2015; 5:18396. [PMID: 26671778 PMCID: PMC4680887 DOI: 10.1038/srep18396] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 11/17/2015] [Indexed: 01/29/2023] Open
Abstract
We propose a new strategy to identify and visualize bacterial consortia by conducting replicated culturing of environmental samples coupled with high-throughput sequencing and multidimensional scaling analysis, followed by identification of bacteria-bacteria correlations and interactions. We conducted a proof of concept assay with pine-tree resin-based media in ten replicates, which allowed detecting and visualizing dynamical bacterial associations in the form of statistically significant and yet biologically relevant bacterial consortia.
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Affiliation(s)
- Pedro Dorado-Morales
- Cavanilles Institute of Biodiversity and Evolutionary Biology (Universitat de València), 46020 Valencia, Spain
| | - Cristina Vilanova
- Cavanilles Institute of Biodiversity and Evolutionary Biology (Universitat de València), 46020 Valencia, Spain
| | - Carlos P Garay
- Instituto de Física Corpuscular, CSIC-UVEG, 46071, Valencia, Spain
| | | | - Manuel Porcar
- Cavanilles Institute of Biodiversity and Evolutionary Biology (Universitat de València), 46020 Valencia, Spain.,Fundació General de la Universitat de València, Spain
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62
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Better together: engineering and application of microbial symbioses. Curr Opin Biotechnol 2015; 36:40-9. [DOI: 10.1016/j.copbio.2015.08.008] [Citation(s) in RCA: 187] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 07/28/2015] [Accepted: 08/09/2015] [Indexed: 12/26/2022]
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63
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Artificial cell-cell communication as an emerging tool in synthetic biology applications. J Biol Eng 2015; 9:13. [PMID: 26265937 PMCID: PMC4531478 DOI: 10.1186/s13036-015-0011-2] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Accepted: 07/25/2015] [Indexed: 01/14/2023] Open
Abstract
Cell-cell communication is a widespread phenomenon in nature, ranging from bacterial quorum sensing and fungal pheromone communication to cellular crosstalk in multicellular eukaryotes. These communication modes offer the possibility to control the behavior of an entire community by modifying the performance of individual cells in specific ways. Synthetic biology, i.e., the implementation of artificial functions within biological systems, is a promising approach towards the engineering of sophisticated, autonomous devices based on specifically functionalized cells. With the growing complexity of the functions performed by such systems, both the risk of circuit crosstalk and the metabolic burden resulting from the expression of numerous foreign genes are increasing. Therefore, systems based on a single type of cells are no longer feasible. Synthetic biology approaches with multiple subpopulations of specifically functionalized cells, wired by artificial cell-cell communication systems, provide an attractive and powerful alternative. Here we review recent applications of synthetic cell-cell communication systems with a specific focus on recent advances with fungal hosts.
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64
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In situ hydrogen, acetone, butanol, ethanol and microdiesel production by Clostridium acetobutylicum ATCC 824 from oleaginous fungal biomass. Anaerobe 2015; 34:125-31. [DOI: 10.1016/j.anaerobe.2015.05.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2015] [Revised: 05/20/2015] [Accepted: 05/21/2015] [Indexed: 12/13/2022]
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65
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Abstract
A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET) from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.
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Affiliation(s)
- Joshua Tasoff
- Department of Economics, Claremont Graduate University, Claremont, California, United States of America
- * E-mail: (JT); (HHW)
| | - Michael T. Mee
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Harris H. Wang
- Department of Systems Biology, Columbia University, New York, New York, United States of America
- * E-mail: (JT); (HHW)
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66
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Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells. Sci Rep 2015; 5:11988. [PMID: 26178309 PMCID: PMC4648426 DOI: 10.1038/srep11988] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 05/29/2015] [Indexed: 12/26/2022] Open
Abstract
The microbiome's underlying dynamics play an important role in regulating the behavior and health of its host. In order to explore the details of these interactions, we created an in silico model of a living microbiome, engineered with synthetic biology, that interfaces with a biomimetic, robotic host. By analytically modeling and computationally simulating engineered gene networks in these commensal communities, we reproduced complex behaviors in the host. We observed that robot movements depended upon programmed biochemical network dynamics within the microbiome. These results illustrate the model's potential utility as a tool for exploring inter-kingdom ecological relationships. These systems could impact fields ranging from synthetic biology and ecology to biophysics and medicine.
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67
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Ji B, Nielsen J. From next-generation sequencing to systematic modeling of the gut microbiome. Front Genet 2015; 6:219. [PMID: 26157455 PMCID: PMC4477173 DOI: 10.3389/fgene.2015.00219] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 06/03/2015] [Indexed: 12/31/2022] Open
Abstract
Changes in the human gut microbiome are associated with altered human metabolism and health, yet the mechanisms of interactions between microbial species and human metabolism have not been clearly elucidated. Next-generation sequencing has revolutionized the human gut microbiome research, but most current applications concentrate on studying the microbial diversity of communities and have at best provided associations between specific gut bacteria and human health. However, little is known about the inner metabolic mechanisms in the gut ecosystem. Here we review recent progress in modeling the metabolic interactions of gut microbiome, with special focus on the utilization of metabolic modeling to infer host–microbe interactions and microbial species interactions. The systematic modeling of metabolic interactions could provide a predictive understanding of gut microbiome, and pave the way to synthetic microbiota design and personalized-microbiome medicine and healthcare. Finally, we discuss the integration of metabolic modeling and gut microbiome engineering, which offer a new way to explore metabolic interactions across members of the gut microbiota.
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Affiliation(s)
- Boyang Ji
- Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology , Göteborg, Sweden
| | - Jens Nielsen
- Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology , Göteborg, Sweden
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68
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Goers L, Freemont P, Polizzi KM. Co-culture systems and technologies: taking synthetic biology to the next level. J R Soc Interface 2014; 11:rsif.2014.0065. [PMID: 24829281 DOI: 10.1098/rsif.2014.0065] [Citation(s) in RCA: 343] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Co-culture techniques find myriad applications in biology for studying natural or synthetic interactions between cell populations. Such techniques are of great importance in synthetic biology, as multi-species cell consortia and other natural or synthetic ecology systems are widely seen to hold enormous potential for foundational research as well as novel industrial, medical and environmental applications with many proof-of-principle studies in recent years. What is needed for co-cultures to fulfil their potential? Cell-cell interactions in co-cultures are strongly influenced by the extracellular environment, which is determined by the experimental set-up, which therefore needs to be given careful consideration. An overview of existing experimental and theoretical co-culture set-ups in synthetic biology and adjacent fields is given here, and challenges and opportunities involved in such experiments are discussed. Greater focus on foundational technology developments for co-cultures is needed for many synthetic biology systems to realize their potential in both applications and answering biological questions.
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Affiliation(s)
- Lisa Goers
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK Centre for Synthetic Biology and Innovation, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Paul Freemont
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK Centre for Synthetic Biology and Innovation, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Karen M Polizzi
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK Centre for Synthetic Biology and Innovation, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
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69
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Mathematical Modeling of Microbial Community Dynamics: A Methodological Review. Processes (Basel) 2014. [DOI: 10.3390/pr2040711] [Citation(s) in RCA: 91] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
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70
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Song H, Ding MZ, Jia XQ, Ma Q, Yuan YJ. Synthetic microbial consortia: from systematic analysis to construction and applications. Chem Soc Rev 2014; 43:6954-81. [PMID: 25017039 DOI: 10.1039/c4cs00114a] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Synthetic biology is an emerging research field that focuses on using rational engineering strategies to program biological systems, conferring on them new functions and behaviours. By developing genetic parts and devices based on transcriptional, translational, post-translational modules, many genetic circuits and metabolic pathways had been programmed in single cells. Extending engineering capabilities from single-cell behaviours to multicellular microbial consortia represents a new frontier of synthetic biology. Herein, we first reviewed binary interaction modes of microorganisms in microbial consortia and their underlying molecular mechanisms, which lay the foundation of programming cell-cell interactions in synthetic microbial consortia. Systems biology studies on cellular systems enable systematic understanding of diverse physiological processes of cells and their interactions, which in turn offer insights into the optimal design of synthetic consortia. Based on such fundamental understanding, a comprehensive array of synthetic microbial consortia constructed in the last decade were reviewed, including isogenic microbial communities programmed by quorum sensing-based cell-cell communications, sender-receiver microbial communities with one-way communications, and microbial ecosystems wired by two-way (bi-directional) communications. Furthermore, many applications including using synthetic microbial consortia for distributed bio-computations, chemicals and bioenergy production, medicine and human health, and environments were reviewed. Synergistic development of systems and synthetic biology will provide both a thorough understanding of naturally occurring microbial consortia and rational engineering of these complicated consortia for novel applications.
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Affiliation(s)
- Hao Song
- Key Laboratory of Systems Bioengineering, Ministry of Education, School of Chemical Engineering and Technology, and Collaborative Innovation Centre of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, P. R. China.
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71
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Abstract
Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology.
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72
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Grosskopf T, Soyer OS. Synthetic microbial communities. Curr Opin Microbiol 2014; 18:72-7. [PMID: 24632350 PMCID: PMC4005913 DOI: 10.1016/j.mib.2014.02.002] [Citation(s) in RCA: 234] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2013] [Revised: 02/06/2014] [Accepted: 02/13/2014] [Indexed: 01/22/2023]
Abstract
Microbial interactions and system function are two ways to study communities. Natural microbial communities are difficult to define and to study. Synthetic microbial communities are comprehensible systems of reduced complexity. Synthetic communities keep key features of natural ones and are amenable to modelling. Synthetic microbial communities are gaining importance in biotechnology.
While natural microbial communities are composed of a mix of microbes with often unknown functions, the construction of synthetic microbial communities allows for the generation of defined systems with reduced complexity. Used in a top-down approach, synthetic communities serve as model systems to ask questions about the performance and stability of microbial communities. In a second, bottom-up approach, synthetic microbial communities are used to study which conditions are necessary to generate interaction patterns like symbiosis or competition, and how higher order community structure can emerge from these. Besides their obvious value as model systems to understand the structure, function and evolution of microbial communities as complex dynamical systems, synthetic communities can also open up new avenues for biotechnological applications.
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Affiliation(s)
| | - Orkun S Soyer
- School of Life Sciences, University of Warwick, United Kingdom.
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73
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Synthetic microbial ecosystems for biotechnology. Biotechnol Lett 2014; 36:1141-51. [PMID: 24563311 DOI: 10.1007/s10529-014-1480-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2013] [Accepted: 01/31/2014] [Indexed: 12/11/2022]
Abstract
Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.
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74
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Transcriptome analysis of a microbial coculture in which the cell populations are separated by a membrane. Methods Mol Biol 2014; 1151:151-64. [PMID: 24838885 DOI: 10.1007/978-1-4939-0554-6_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The microbial coculture of multiple cell populations is used to study community evolution and for bioengineering applications. The cells in coculture undergo dynamic changes because of cell-cell and cell-environment interactions. Transcriptome analysis allows us to study the molecular basis of these changes in cell physiology. For transcriptome analysis, it is essential that the cell populations in the coculture are harvested separately. Here, we describe a method for transcriptome analysis of a microbial coculture in which two different cell populations are separated by a porous membrane.
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75
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Abstract
Recent progress in molecular biology and genetics opens up the possibility of engineering a variety of biological systems, from single-cellular to multicellular organisms. The consortia of microbes that reside on the human body, the human-associated microbiota, are particularly interesting as targets for forward engineering and manipulation due to their relevance in health and disease. New technologies in analysis and perturbation of the human microbiota will lead to better diagnostic and therapeutic strategies against diseases of microbial origin or pathogenesis. Here, we discuss recent advances that are bringing us closer to realizing the true potential of an engineered human-associated microbial community.
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Affiliation(s)
- Stephanie J Yaung
- Program in Medical Engineering Medical Physics, Harvard-MIT Health Sciences and Technology, Cambridge, MA, USA
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76
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Review of Microalgae Harvesting via Co-Pelletization with Filamentous Fungus. ENERGIES 2013. [DOI: 10.3390/en6115921] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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77
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Genome-scale engineering for systems and synthetic biology. Mol Syst Biol 2013; 9:641. [PMID: 23340847 PMCID: PMC3564264 DOI: 10.1038/msb.2012.66] [Citation(s) in RCA: 209] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2012] [Accepted: 12/16/2012] [Indexed: 12/15/2022] Open
Abstract
This review provides an overview of methodologies and technologies enabling genome-scale engineering, focusing on the design, construction, and testing of modified genomes in a variety of organisms. Future applications for systems and synthetic biology are discussed. Genome-modification technologies enable the rational engineering and perturbation of biological systems. Historically, these methods have been limited to gene insertions or mutations at random or at a few pre-defined locations across the genome. The handful of methods capable of targetedgene editing suffered from low efficiencies, significant labor costs, or both. Recent advances have dramatically expanded our ability to engineer cells in a directed and combinatorial manner. Here, we review current technologies and methodologies for genome-scale engineering, discuss the prospects for extending efficient genome modification to new hosts, and explore the implications of continued advances toward the development of flexibly programmable chasses, novel biochemistries, and safer organismal and ecological engineering.
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78
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Design and characterization of synthetic fungal-bacterial consortia for direct production of isobutanol from cellulosic biomass. Proc Natl Acad Sci U S A 2013; 110:14592-7. [PMID: 23959872 DOI: 10.1073/pnas.1218447110] [Citation(s) in RCA: 264] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Synergistic microbial communities are ubiquitous in nature and exhibit appealing features, such as sophisticated metabolic capabilities and robustness. This has inspired fast-growing interest in engineering synthetic microbial consortia for biotechnology development. However, there are relatively few reports of their use in real-world applications, and achieving population stability and regulation has proven to be challenging. In this work, we bridge ecology theory with engineering principles to develop robust synthetic fungal-bacterial consortia for efficient biosynthesis of valuable products from lignocellulosic feedstocks. The required biological functions are divided between two specialists: the fungus Trichoderma reesei, which secretes cellulase enzymes to hydrolyze lignocellulosic biomass into soluble saccharides, and the bacterium Escherichia coli, which metabolizes soluble saccharides into desired products. We developed and experimentally validated a comprehensive mathematical model for T. reesei/E. coli consortia, providing insights on key determinants of the system's performance. To illustrate the bioprocessing potential of this consortium, we demonstrate direct conversion of microcrystalline cellulose and pretreated corn stover to isobutanol. Without costly nutrient supplementation, we achieved titers up to 1.88 g/L and yields up to 62% of theoretical maximum. In addition, we show that cooperator-cheater dynamics within T. reesei/E. coli consortia lead to stable population equilibria and provide a mechanism for tuning composition. Although we offer isobutanol production as a proof-of-concept application, our modular system could be readily adapted for production of many other valuable biochemicals.
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79
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Kubo I, Hosoda K, Suzuki S, Yamamoto K, Kihara K, Mori K, Yomo T. Construction of bacteria-eukaryote synthetic mutualism. Biosystems 2013; 113:66-71. [PMID: 23711432 DOI: 10.1016/j.biosystems.2013.05.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2013] [Revised: 05/14/2013] [Accepted: 05/16/2013] [Indexed: 01/07/2023]
Abstract
Mutualism is ubiquitous in nature but is known to be intrinsically vulnerable with regard to both population dynamics and evolution. Synthetic ecology has indicated that it is feasible for organisms to establish novel mutualism merely through encountering each other by showing that it is feasible to construct synthetic mutualism between organisms. However, bacteria-eukaryote mutualism, which is ecologically important, has not yet been constructed. In this study, we synthetically constructed mutualism between a bacterium and a eukaryote by using two model organisms. We mixed a bacterium, Escherichia coli (a genetically engineered glutamine auxotroph), and an amoeba, Dictyostelium discoideum, in 14 sets of conditions in which each species could not grow in monoculture but potentially could grow in coculture. Under a single condition in which the bacterium and amoeba mutually compensated for the lack of required nutrients (lipoic acid and glutamine, respectively), both species grew continuously through several subcultures, essentially establishing mutualism. Our results shed light on the establishment of bacteria-eukaryote mutualism and indicate that a bacterium and eukaryote pair in nature also has a non-negligible possibility of establishing novel mutualism if the organisms are potentially mutualistic.
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Affiliation(s)
- Isao Kubo
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan
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80
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Lebeaux D, Chauhan A, Rendueles O, Beloin C. From in vitro to in vivo Models of Bacterial Biofilm-Related Infections. Pathogens 2013; 2:288-356. [PMID: 25437038 PMCID: PMC4235718 DOI: 10.3390/pathogens2020288] [Citation(s) in RCA: 300] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2013] [Revised: 05/01/2013] [Accepted: 05/08/2013] [Indexed: 12/13/2022] Open
Abstract
The influence of microorganisms growing as sessile communities in a large number of human infections has been extensively studied and recognized for 30–40 years, therefore warranting intense scientific and medical research. Nonetheless, mimicking the biofilm-life style of bacteria and biofilm-related infections has been an arduous task. Models used to study biofilms range from simple in vitro to complex in vivo models of tissues or device-related infections. These different models have progressively contributed to the current knowledge of biofilm physiology within the host context. While far from a complete understanding of the multiple elements controlling the dynamic interactions between the host and biofilms, we are nowadays witnessing the emergence of promising preventive or curative strategies to fight biofilm-related infections. This review undertakes a comprehensive analysis of the literature from a historic perspective commenting on the contribution of the different models and discussing future venues and new approaches that can be merged with more traditional techniques in order to model biofilm-infections and efficiently fight them.
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Affiliation(s)
- David Lebeaux
- Institut Pasteur, Unité de Génétique des Biofilms, 25 rue du Dr. Roux, 75724 Paris cedex 15, France.
| | - Ashwini Chauhan
- Institut Pasteur, Unité de Génétique des Biofilms, 25 rue du Dr. Roux, 75724 Paris cedex 15, France.
| | - Olaya Rendueles
- Institut Pasteur, Unité de Génétique des Biofilms, 25 rue du Dr. Roux, 75724 Paris cedex 15, France.
| | - Christophe Beloin
- Institut Pasteur, Unité de Génétique des Biofilms, 25 rue du Dr. Roux, 75724 Paris cedex 15, France.
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