1
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Zheng X, Li J, Ouyang Y, Wu G, He X, Wang D, Zhang XX. Ecological linkages between top-down designed benzothiazole-degrading consortia and selection strength: From performance to community structure and functional genes. WATER RESEARCH 2024; 267:122491. [PMID: 39353343 DOI: 10.1016/j.watres.2024.122491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Revised: 08/15/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024]
Abstract
The inefficient biodegradation and incomplete mineralization of nitrogenous heterocyclic compounds (NHCs) have emerged as a pressing environmental concern. The top-down design offers potential solutions to this issue by targeting improvements in community function, but the ecological linkages between selection strength and the structure and function of desired microbiomes remain elusive. Herein, the integration of metagenomics, culture-based approach, non-targeted metabolite screening and enzymatic verification experiments revealed the effect of enrichment concentration on the top-down designed benzothiazole (BTH, a typical NHC)-degrading consortia. Significant differences were observed for the degradation efficiency and community structure under varying BTH selections. Notably, the enriched consortia at high concentrations of BTH were dominated by genus Rhodococcus, possessing higher degradation rates. Moreover, the isolate Rhodococcus pyridinivorans Rho48 displayed excellent efficiencies in BTH removal (98 %) and mineralization (∼ 60 %) through the hydroxylation and cleavage of thiazole and benzene rings, where cytochrome P450 enzyme was firstly reported to participate in BTH conversion. The functional annotation of 460 recovered genomes from the enriched consortia revealed diverse interspecific cooperation patterns that accounted for the BTH mineralization, particularly Nakamurella and Micropruina under low selection strength, and Rhodococcus and Marmoricola under high selection strength. This study highlights the significance of selection strength in top-down design of synthetic microbiomes for degrading refractory organic pollutants, providing valuable guidance for designing functionally optimized microbiomes used in environmental engineering.
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Affiliation(s)
- Xiulin Zheng
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Jie Li
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Yixin Ouyang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Gang Wu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Xiwei He
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China; School of Environment, Jiangsu Engineering Lab of Water and Soil Eco-Remediation, Nanjing Normal University, Nanjing 210023, China
| | - Depeng Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
| | - Xu-Xiang Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
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2
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Wang S, Zhan Y, Jiang X, Lai Y. Engineering Microbial Consortia as Living Materials: Advances and Prospectives. ACS Synth Biol 2024; 13:2653-2666. [PMID: 39174016 PMCID: PMC11421429 DOI: 10.1021/acssynbio.4c00313] [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] [Indexed: 08/24/2024]
Abstract
The field of Engineered Living Materials (ELMs) integrates engineered living organisms into natural biomaterials to achieve diverse objectives. Multiorganism consortia, prevalent in both naturally occurring and synthetic microbial cultures, exhibit complex functionalities and interrelationships, extending the scope of what can be achieved with individual engineered bacterial strains. However, the ELMs comprising microbial consortia are still in the developmental stage. In this Review, we introduce two strategies for designing ELMs constituted of microbial consortia: a top-down strategy, which involves characterizing microbial interactions and mimicking and reconstructing natural ecosystems, and a bottom-up strategy, which entails the rational design of synthetic consortia and their assembly with material substrates to achieve user-defined functions. Next, we summarize technologies from synthetic biology that facilitate the efficient engineering of microbial consortia for performing tasks more complex than those that can be done with single bacterial strains. Finally, we discuss essential challenges and future perspectives for microbial consortia-based ELMs.
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Affiliation(s)
- Shuchen Wang
- Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
| | - Yuewei Zhan
- Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
| | - Xue Jiang
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Yong Lai
- Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
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3
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Chen X, Wang M, Luo L, Liu X, An L, Nie Y, Wu XL. The evolution of autonomy from two cooperative specialists in fluctuating environments. Proc Natl Acad Sci U S A 2024; 121:e2317182121. [PMID: 39172793 PMCID: PMC11363282 DOI: 10.1073/pnas.2317182121] [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: 10/04/2023] [Accepted: 07/24/2024] [Indexed: 08/24/2024] Open
Abstract
From microbes to humans, organisms perform numerous tasks for their survival, including food acquisition, migration, and reproduction. A complex biological task can be performed by either an autonomous organism or by cooperation among several specialized organisms. However, it remains unclear how autonomy and cooperation evolutionarily switch. Specifically, it remains unclear whether and how cooperative specialists can repair deleted genes through direct genetic exchange, thereby regaining metabolic autonomy. Here, we address this question by experimentally evolving a mutualistic microbial consortium composed of two specialists that cooperatively degrade naphthalene. We observed that autonomous genotypes capable of performing the entire naphthalene degradation pathway evolved from two cooperative specialists and dominated the community. This evolutionary transition was driven by the horizontal gene transfer (HGT) between the two specialists. However, this evolution was exclusively observed in the fluctuating environment alternately supplied with naphthalene and pyruvate, where mutualism and competition between the two specialists alternated. The naphthalene-supplied environment exerted selective pressure that favors the expansion of autonomous genotypes. The pyruvate-supplied environment promoted the coexistence and cell density of the cooperative specialists, thereby increasing the likelihood of HGT. Using a mathematical model, we quantitatively demonstrate that environmental fluctuations facilitate the evolution of autonomy through HGT when the relative growth rate and carrying capacity of the cooperative specialists allow enhanced coexistence and higher cell density in the competitive environment. Together, our results demonstrate that cooperative specialists can repair deleted genes through a direct genetic exchange under specific conditions, thereby regaining metabolic autonomy.
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Affiliation(s)
- Xiaoli Chen
- College of Engineering, Peking University, Beijing100871, China
- Institute of Ocean Research, Peking University, Beijing100871, China
| | - Miaoxiao Wang
- Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
- Department of Environmental Microbiology, Eawag, Dübendorf, Switzerland
| | - Laipeng Luo
- College of Engineering, Peking University, Beijing100871, China
| | - Xiaonan Liu
- College of Engineering, Peking University, Beijing100871, China
| | - Liyun An
- College of Architecture and Environment, Sichuan University, Chengdu610000, China
| | - Yong Nie
- College of Engineering, Peking University, Beijing100871, China
| | - Xiao-Lei Wu
- College of Engineering, Peking University, Beijing100871, China
- Institute of Ocean Research, Peking University, Beijing100871, China
- Institute of Ecology, Peking University, Beijing100871, China
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4
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Wang Z, Fu X, Kuramae EE. Insight into farming native microbiome by bioinoculant in soil-plant system. Microbiol Res 2024; 285:127776. [PMID: 38820701 DOI: 10.1016/j.micres.2024.127776] [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: 02/12/2024] [Revised: 05/16/2024] [Accepted: 05/17/2024] [Indexed: 06/02/2024]
Abstract
Applying beneficial microorganisms (BM) as bioinoculants presents a promising soil-amendment strategy while impacting the native microbiome, which jointly alters soil-plant performance. Leveraging the untapped potential of native microbiomes alongside bioinoculants may enable farmers to sustainably regulate soil-plant systems via natural bioresources. This review synthesizes literature on native microbiome responses to BMs and their interactive effects on soil and plant performance. We highlight that native microbiomes harbor both microbial "helpers" that can improve soil fertility and plant productivity, as well as "inhibitors" that hinder these benefits. To harness the full potential of resident microbiome, it is crucial to elucidate their intricate synergistic and antagonistic interplays with introduced BMs and clarify the conditions that facilitate durable BM-microbiome synergies. Hence, we indicate current challenges in predicting these complex microbial interactions and propose corresponding strategies for microbiome breeding via BM bioinoculant. Overall, fully realizing the potential of BMs requires clarifying their interactions with native soil microbiomes and judiciously engineering microbiome to harness helpful microbes already present within agroecosystems.
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Affiliation(s)
- Zhikang Wang
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China; Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China; Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen 6708 PB, the Netherlands
| | - Xiangxiang Fu
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China.
| | - Eiko E Kuramae
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen 6708 PB, the Netherlands; Ecology and biodiversity, Institute of Environmental Biology, Utrecht University, 3584 CH Utrecht, the Netherlands.
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5
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Vass M, Székely AJ, Carlsson-Graner U, Wikner J, Andersson A. Microeukaryote community coalescence strengthens community stability and elevates diversity. FEMS Microbiol Ecol 2024; 100:fiae100. [PMID: 39003240 PMCID: PMC11287207 DOI: 10.1093/femsec/fiae100] [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: 02/21/2024] [Revised: 06/19/2024] [Accepted: 07/12/2024] [Indexed: 07/15/2024] Open
Abstract
Mixing of entire microbial communities represents a frequent, yet understudied phenomenon. Here, we mimicked estuarine condition in a microcosm experiment by mixing a freshwater river community with a brackish sea community and assessed the effects of both environmental and community coalescences induced by varying mixing processes on microeukaryotic communities. Signs of shifted community composition of coalesced communities towards the sea parent community suggest asymmetrical community coalescence outcome, which, in addition, was generally less impacted by environmental coalescence. Community stability, inferred from community cohesion, differed among river and sea parent communities, and increased following coalescence treatments. Generally, community coalescence increased alpha diversity and promoted competition from the introduction (or emergence) of additional (or rare) species. These competitive interactions in turn had community stabilizing effect as evidenced by the increased proportion of negative cohesion. The fate of microeukaryotes was influenced by mixing ratios and frequencies (i.e. one-time versus repeated coalescence). Namely, diatoms were negatively impacted by coalescence, while fungi, ciliates, and cercozoans were promoted to varying extents, depending on the mixing ratios of the parent communities. Our study suggests that the predictability of coalescence outcomes was greater when the sea parent community dominated the final community, and this predictability was further enhanced when communities collided repeatedly.
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Affiliation(s)
- Máté Vass
- Department of Ecology and Environmental Science, Umeå University, SE-90187 Umeå, Sweden
- Division of Systems and Synthetic Biology, Department of Life Sciences, Science for Life Laboratory, Chalmers University of Technology, SE-41296 Gothenburg, Sweden
| | - Anna J Székely
- Division of Microbial Ecology, Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden
| | - Ulla Carlsson-Graner
- Department of Ecology and Environmental Science, Umeå University, SE-90187 Umeå, Sweden
| | - Johan Wikner
- Department of Ecology and Environmental Science, Umeå University, SE-90187 Umeå, Sweden
- Umeå Marine Sciences Centre, Umeå University, SE-90571 Hörnefors, Sweden
| | - Agneta Andersson
- Department of Ecology and Environmental Science, Umeå University, SE-90187 Umeå, Sweden
- Umeå Marine Sciences Centre, Umeå University, SE-90571 Hörnefors, Sweden
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6
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Ruan Z, Chen K, Cao W, Meng L, Yang B, Xu M, Xing Y, Li P, Freilich S, Chen C, Gao Y, Jiang J, Xu X. Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling. Nat Commun 2024; 15:4694. [PMID: 38824157 PMCID: PMC11144243 DOI: 10.1038/s41467-024-49098-z] [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: 03/26/2022] [Accepted: 05/21/2024] [Indexed: 06/03/2024] Open
Abstract
Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.
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Affiliation(s)
- Zhepu Ruan
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Agricultural & Rural Pollution Abatement and Environmental Safety, College of Natural Resources and Environment, South China Agricultural University, Guangzhou, 510642, China
| | - Kai Chen
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Weimiao Cao
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Lei Meng
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Bingang Yang
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Mengjun Xu
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Youwen Xing
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Pengfa Li
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Shiri Freilich
- Newe Ya'ar Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay, 30095, Israel
| | - Chen Chen
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China
| | - Yanzheng Gao
- College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095, China.
| | - Jiandong Jiang
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China.
| | - Xihui Xu
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural University, Key Laboratory of Agricultural and Environmental Microbiology, Ministry of Agriculture and Rural Affairs, Nanjing, 210095, China.
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7
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Jiménez DJ, Sanchez A, Dini-Andreote F. Engineering microbiomes to transform plastics. Trends Biotechnol 2024; 42:265-268. [PMID: 37845169 DOI: 10.1016/j.tibtech.2023.09.011] [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: 08/04/2023] [Revised: 09/24/2023] [Accepted: 09/25/2023] [Indexed: 10/18/2023]
Abstract
The design and study of active microbial consortia able to degrade plastics represent an exciting area of research toward the development of bio-based alternatives to efficiently transform plastic waste. This forum article discusses concepts and mechanisms to inform emerging strategies for engineering microbiomes to transform plastics under controlled settings.
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Affiliation(s)
- Diego Javier Jiménez
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
| | - Alvaro Sanchez
- Department of Microbial Biotechnology, Centro Nacional de Biotecnología - CSIC, Campus de Cantoblanco, Madrid, Spain
| | - Francisco Dini-Andreote
- Department of Plant Science and Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA; The One Health Microbiome Center, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
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8
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Faller L, Leite MFA, Kuramae EE. Enhancing phosphate-solubilising microbial communities through artificial selection. Nat Commun 2024; 15:1649. [PMID: 38388537 PMCID: PMC10884399 DOI: 10.1038/s41467-024-46060-x] [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: 08/24/2023] [Accepted: 02/13/2024] [Indexed: 02/24/2024] Open
Abstract
Microbial communities, acting as key drivers of ecosystem processes, harbour immense potential for sustainable agriculture practices. Phosphate-solubilising microorganisms, for example, can partially replace conventional phosphate fertilisers, which rely on finite resources. However, understanding the mechanisms and engineering efficient communities poses a significant challenge. In this study, we employ two artificial selection methods, environmental perturbation, and propagation, to construct phosphate-solubilising microbial communities. To assess trait transferability, we investigate the community performance in different media and a hydroponic system with Chrysanthemum indicum. Our findings reveal a distinct subset of phosphate-solubilising bacteria primarily dominated by Klebsiella and Enterobacterales. The propagated communities consistently demonstrate elevated levels of phosphate solubilisation, surpassing the starting soil community by 24.2% in activity. The increased activity of propagated communities remains consistent upon introduction into the hydroponic system. This study shows the efficacy of community-level artificial selection, particularly through propagation, as a tool for successfully modifying microbial communities to enhance phosphate solubilisation.
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Affiliation(s)
- Lena Faller
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB, Wageningen, The Netherlands
- Utrecht University, Institute of Environmental Biology, Ecology and Biodiversity, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Marcio F A Leite
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB, Wageningen, The Netherlands
- Utrecht University, Institute of Environmental Biology, Ecology and Biodiversity, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Eiko E Kuramae
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB, Wageningen, The Netherlands.
- Utrecht University, Institute of Environmental Biology, Ecology and Biodiversity, Padualaan 8, 3584 CH, Utrecht, The Netherlands.
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9
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Dijamentiuk A, Mangavel C, Gapp C, Elfassy A, Revol-Junelles AM, Borges F. Serial cultures in invert emulsion and monophase systems for microbial community shaping and propagation. Microb Cell Fact 2024; 23:50. [PMID: 38355580 PMCID: PMC10865683 DOI: 10.1186/s12934-024-02322-3] [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: 12/14/2023] [Accepted: 01/29/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Microbial communities harbor important biotechnological potential in diverse domains, however, the engineering and propagation of such communities still face both knowledge and know-how gaps. More specifically, culturing tools are needed to propagate and shape microbial communities, to obtain desired properties, and to exploit them. Previous work suggested that micro-confinement and segregation of microorganisms using invert (water-in-oil, w/o) emulsion broth can shape communities during propagation, by alleviating biotic interactions and inducing physiological changes in cultured bacteria. The present work aimed at evaluating invert emulsion and simple broth monophasic cultures for the propagation and shaping of bacterial communities derived from raw milk in a serial propagation design. RESULTS The monophasic setup resulted in stable community structures during serial propagation, whereas the invert emulsion system resulted in only transiently stable structures. In addition, different communities with different taxonomic compositions could be obtained from a single inoculum. Furthermore, the implementation of invert emulsion systems has allowed for the enrichment of less abundant microorganisms and consequently facilitated their isolation on culture agar plates. CONCLUSIONS The monophasic system enables communities to be propagated in a stable manner, whereas the invert emulsion system allowed for the isolation of less abundant microorganisms and the generation of diverse taxonomic compositions from a single inoculum.
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Affiliation(s)
- Alexis Dijamentiuk
- Laboratoire d'Ingénierie des Biomolécules (LIBio), Université de Lorraine, Nancy, France
| | - Cécile Mangavel
- Laboratoire d'Ingénierie des Biomolécules (LIBio), Université de Lorraine, Nancy, France
| | - Chloé Gapp
- Laboratoire d'Ingénierie des Biomolécules (LIBio), Université de Lorraine, Nancy, France
| | - Annelore Elfassy
- Laboratoire d'Ingénierie des Biomolécules (LIBio), Université de Lorraine, Nancy, France
| | | | - Frédéric Borges
- Laboratoire d'Ingénierie des Biomolécules (LIBio), Université de Lorraine, Nancy, France.
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10
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Thomas JL, Rowland-Chandler J, Shou W. Artificial selection of microbial communities: what have we learnt and how can we improve? Curr Opin Microbiol 2024; 77:102400. [PMID: 38091857 DOI: 10.1016/j.mib.2023.102400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/06/2023] [Accepted: 10/19/2023] [Indexed: 02/12/2024]
Abstract
Microbial communities are capable of performing diverse functions with important bioindustrial and medical applications. One approach to improving community function is to breed new communities by artificially selecting for those displaying high community function ('community selection'). Importantly, community selection can improve the function of interest without needing to understand how the function arises, just like in classical artificial selection of individuals. However, experimental studies of community selection have had varied and largely limited success. Here, we review a conceptual framework to help foster an understanding of community selection and its associated challenges, and provide broad insights for designing effective selection strategies.
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Affiliation(s)
- Joshua L Thomas
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, United Kingdom
| | - Jamila Rowland-Chandler
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, United Kingdom
| | - Wenying Shou
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, United Kingdom.
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11
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Deng J, Taylor W, Levin SA, Saavedra S. On the limits to invasion prediction using coexistence outcomes. J Theor Biol 2024; 577:111674. [PMID: 38008157 DOI: 10.1016/j.jtbi.2023.111674] [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: 04/20/2023] [Revised: 11/01/2023] [Accepted: 11/14/2023] [Indexed: 11/28/2023]
Abstract
The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while individual survival probability in coexistence dynamics can be fairly closely translated into invader colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.
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Affiliation(s)
- Jie Deng
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Washington Taylor
- Center for Theoretical Physics, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, USA
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12
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Lyu X, Nuhu M, Candry P, Wolfanger J, Betenbaugh M, Saldivar A, Zuniga C, Wang Y, Shrestha S. Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass. J Ind Microbiol Biotechnol 2024; 51:kuae025. [PMID: 39003244 PMCID: PMC11287213 DOI: 10.1093/jimb/kuae025] [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: 04/11/2024] [Accepted: 07/12/2024] [Indexed: 07/15/2024]
Abstract
Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach. The top-down approach is a classical method that uses environmental variables to selectively steer an existing microbial consortium to achieve a target function. While high-throughput sequencing has enabled microbial community characterization, the major challenge is to disentangle complex microbial interactions and manipulate the structure and function accordingly. The bottom-up approach uses prior knowledge of the metabolic pathway and possible interactions among consortium partners to design and engineer synthetic microbial consortia. This strategy offers some control over the composition and function of the consortium for targeted bioprocesses, but challenges remain in optimal assembly methods and long-term stability. In this review, we present the recent advancements, challenges, and opportunities for further improvement using top-down and bottom-up approaches for microbiome engineering. As the bottom-up approach is relatively a new concept for waste valorization, this review explores the assembly and design of synthetic microbial consortia, ecological engineering principles to optimize microbial consortia, and metabolic engineering approaches for efficient conversion. Integration of top-down and bottom-up approaches along with developments in metabolic modeling to predict and optimize consortia function are also highlighted. ONE-SENTENCE SUMMARY This review highlights the microbial consortia-driven waste valorization for biomanufacturing through top-down and bottom-up design approaches and describes strategies, tools, and unexplored opportunities to optimize the design and stability of such consortia.
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Affiliation(s)
- Xuejiao Lyu
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mujaheed Nuhu
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Pieter Candry
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE Wageningen, The Netherlands
| | - Jenna Wolfanger
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michael Betenbaugh
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Alexis Saldivar
- Department of Biology, San Diego State University, San Diego, CA 92182-4614, USA
| | - Cristal Zuniga
- Department of Biology, San Diego State University, San Diego, CA 92182-4614, USA
| | - Ying Wang
- Department of Soil and Crop Sciences, Texas A&M University, TX 77843, USA
| | - Shilva Shrestha
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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13
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Jing J, Garbeva P, Raaijmakers JM, Medema MH. Strategies for tailoring functional microbial synthetic communities. THE ISME JOURNAL 2024; 18:wrae049. [PMID: 38537571 PMCID: PMC11008692 DOI: 10.1093/ismejo/wrae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 02/26/2024] [Indexed: 04/12/2024]
Abstract
Natural ecosystems harbor a huge reservoir of taxonomically diverse microbes that are important for plant growth and health. The vast diversity of soil microorganisms and their complex interactions make it challenging to pinpoint the main players important for the life support functions microbes can provide to plants, including enhanced tolerance to (a)biotic stress factors. Designing simplified microbial synthetic communities (SynComs) helps reduce this complexity to unravel the molecular and chemical basis and interplay of specific microbiome functions. While SynComs have been successfully employed to dissect microbial interactions or reproduce microbiome-associated phenotypes, the assembly and reconstitution of these communities have often been based on generic abundance patterns or taxonomic identities and co-occurrences but have only rarely been informed by functional traits. Here, we review recent studies on designing functional SynComs to reveal common principles and discuss multidimensional approaches for community design. We propose a strategy for tailoring the design of functional SynComs based on integration of high-throughput experimental assays with microbial strains and computational genomic analyses of their functional capabilities.
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Affiliation(s)
- Jiayi Jing
- Bioinformatics Group, Department of Plant Science, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands
| | - Paolina Garbeva
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands
| | - Jos M Raaijmakers
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands
| | - Marnix H Medema
- Bioinformatics Group, Department of Plant Science, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
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14
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Petrushin IS, Filinova NV, Gutnik DI. Potato Microbiome: Relationship with Environmental Factors and Approaches for Microbiome Modulation. Int J Mol Sci 2024; 25:750. [PMID: 38255824 PMCID: PMC10815375 DOI: 10.3390/ijms25020750] [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: 10/20/2023] [Revised: 12/12/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
Every land plant exists in a close relationship with microbial communities of several niches: rhizosphere, endosphere, phyllosphere, etc. The growth and yield of potato-a critical food crop worldwide-highly depend on the diversity and structure of the bacterial and fungal communities with which the potato plant coexists. The potato plant has a specific part, tubers, and the soil near the tubers as a sub-compartment is usually called the "geocaulosphere", which is associated with the storage process and tare soil microbiome. Specific microbes can help the plant to adapt to particular environmental conditions and resist pathogens. There are a number of approaches to modulate the microbiome that provide organisms with desired features during inoculation. The mechanisms of plant-bacterial communication remain understudied, and for further engineering of microbiomes with particular features, the knowledge on the potato microbiome should be summarized. The most recent approaches to microbiome engineering include the construction of a synthetic microbial community or management of the plant microbiome using genome engineering. In this review, the various factors that determine the microbiome of potato and approaches that allow us to mitigate the negative impact of drought and pathogens are surveyed.
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Affiliation(s)
- Ivan S. Petrushin
- Siberian Institute of Plant Physiology and Biochemistry, Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia; (N.V.F.); (D.I.G.)
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15
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Meyer KM, Muscettola IE, Vasconcelos ALS, Sherman JK, Metcalf CJE, Lindow SE, Koskella B. Conspecific versus heterospecific transmission shapes host specialization of the phyllosphere microbiome. Cell Host Microbe 2023; 31:2067-2079.e5. [PMID: 38029741 DOI: 10.1016/j.chom.2023.11.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 09/09/2023] [Accepted: 11/01/2023] [Indexed: 12/01/2023]
Abstract
In disease ecology, pathogen transmission among conspecific versus heterospecific hosts is known to shape pathogen specialization and virulence, but we do not yet know if similar effects occur at the microbiome level. We tested this idea by experimentally passaging leaf-associated microbiomes either within conspecific or across heterospecific plant hosts. Although conspecific transmission results in persistent host-filtering effects and more within-microbiome network connections, heterospecific transmission results in weaker host-filtering effects but higher levels of interconnectivity. When transplanted onto novel plants, heterospecific lines are less differentiated by host species than conspecific lines, suggesting a shift toward microbiome generalism. Finally, conspecific lines from tomato exhibit a competitive advantage on tomato hosts against those passaged on bean or pepper, suggesting microbiome-level host specialization. Overall, we find that transmission mode and previous host history shape microbiome diversity, with repeated conspecific transmission driving microbiome specialization and repeated heterospecific transmission promoting microbiome generalism.
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Affiliation(s)
- Kyle M Meyer
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94720, USA.
| | - Isabella E Muscettola
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Ana Luisa S Vasconcelos
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Soil Science, College of Agriculture "Luiz de Queiroz", Universidade de São Paulo, Piracicaba 13418-900, Brazil
| | - Julia K Sherman
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Steven E Lindow
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94720, USA
| | - Britt Koskella
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA 94158, USA
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16
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Arya S, George AB, O’Dwyer JP. Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes. Proc Natl Acad Sci U S A 2023; 120:e2307313120. [PMID: 37991947 PMCID: PMC10691334 DOI: 10.1073/pnas.2307313120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 10/16/2023] [Indexed: 11/24/2023] Open
Abstract
Microbiome engineering offers the potential to leverage microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and function. But a brute force approach to cataloging community function is hindered by the combinatorial explosion in the number of ways we can combine microbial species. An alternative is to parameterize microbial community outcomes using simplified, mechanistic models, and then extrapolate these models beyond where we have sampled. But these approaches remain data-hungry, as well as requiring an a priori specification of what kinds of mechanisms are included and which are omitted. Here, we resolve both issues by introducing a mechanism-agnostic approach to predicting microbial community compositions and functions using limited data. The critical step is the identification of a sparse representation of the community landscape. We then leverage this sparsity to predict community compositions and functions, drawing from techniques in compressive sensing. We validate this approach on in silico community data, generated from a theoretical model. By sampling just [Formula: see text]1% of all possible communities, we accurately predict community compositions out of sample. We then demonstrate the real-world application of our approach by applying it to four experimental datasets and showing that we can recover interpretable, accurate predictions on composition and community function from highly limited data.
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Affiliation(s)
- Shreya Arya
- Department of Physics, University of Illinois, Urbana-Champaign, Urbana, IL61801
| | - Ashish B. George
- Center for Artificial Intelligence and Modeling, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL61801
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA0214
- Department of Plant Biology, University of Illinois, Urbana-Champaign, Urbana, IL61801
| | - James P. O’Dwyer
- Center for Artificial Intelligence and Modeling, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL61801
- Department of Plant Biology, University of Illinois, Urbana-Champaign, Urbana, IL61801
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17
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. ARXIV 2023:arXiv:2304.10694v3. [PMID: 37131883 PMCID: PMC10153352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R * and species coexistence cones. Here, we extend these arguments by constructing a novel geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically-stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, Massachusetts 02215, USA
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18
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. Phys Rev E 2023; 108:044409. [PMID: 37978666 DOI: 10.1103/physreve.108.044409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/29/2023] [Indexed: 11/19/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R^{*} and species coexistence cones. Here, we extend these arguments by constructing a geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, Massachusetts 02215, USA
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19
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Yu SR, Zhang YY, Zhang QG. The effectiveness of artificial microbial community selection: a conceptual framework and a meta-analysis. Front Microbiol 2023; 14:1257935. [PMID: 37840740 PMCID: PMC10570731 DOI: 10.3389/fmicb.2023.1257935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023] Open
Abstract
The potential for artificial selection at the community level to improve ecosystem functions has received much attention in applied microbiology. However, we do not yet understand what conditions in general allow for successful artificial community selection. Here we propose six hypotheses about factors that determine the effectiveness of artificial microbial community selection, based on previous studies in this field and those on multilevel selection. In particular, we emphasize selection strategies that increase the variance among communities. We then report a meta-analysis of published artificial microbial community selection experiments. The reported responses to community selection were highly variable among experiments; and the overall effect size was not significantly different from zero. The effectiveness of artificial community selection was greater when there was no migration among communities, and when the number of replicated communities subjected to selection was larger. The meta-analysis also suggests that the success of artificial community selection may be contingent on multiple necessary conditions. We argue that artificial community selection can be a promising approach, and suggest some strategies for improving the performance of artificial community selection programs.
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Affiliation(s)
- Shi-Rui Yu
- State Key Laboratory of Earth Surface Processes and Resource Ecology and MOE Key Laboratory for Biodiversity Science and Ecological Engineering, Beijing Normal University, Beijing, China
| | - Yuan-Ye Zhang
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China
| | - Quan-Guo Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology and MOE Key Laboratory for Biodiversity Science and Ecological Engineering, Beijing Normal University, Beijing, China
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20
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Abstract
For thousands of years, humans have enjoyed the novel flavors, increased shelf-life, and nutritional benefits that microbes provide in fermented foods and beverages. Recent sequencing surveys of ferments have mapped patterns of microbial diversity across space, time, and production practices. But a mechanistic understanding of how fermented food microbiomes assemble has only recently begun to emerge. Using three foods as case studies (surface-ripened cheese, sourdough starters, and fermented vegetables), we use an ecological and evolutionary framework to identify how microbial communities assemble in ferments. By combining in situ sequencing surveys with in vitro models, we are beginning to understand how dispersal, selection, diversification, and drift generate the diversity of fermented food communities. Most food producers are unaware of the ecological processes occurring in their production environments, but the theory and models of ecology and evolution can provide new approaches for managing fermented food microbiomes, from farm to ferment.
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Affiliation(s)
- Nicolas L Louw
- Department of Biology, Tufts University, Medford, Massachusetts, USA; , , , ,
| | - Kasturi Lele
- Department of Biology, Tufts University, Medford, Massachusetts, USA; , , , ,
| | - Ruby Ye
- Department of Biology, Tufts University, Medford, Massachusetts, USA; , , , ,
| | - Collin B Edwards
- Department of Biology, Tufts University, Medford, Massachusetts, USA; , , , ,
- School of Biological Sciences, Washington State University, Vancouver, Washington, USA
| | - Benjamin E Wolfe
- Department of Biology, Tufts University, Medford, Massachusetts, USA; , , , ,
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21
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Zaccaria M, Sandlin N, Soen Y, Momeni B. Partner-assisted artificial selection of a secondary function for efficient bioremediation. iScience 2023; 26:107632. [PMID: 37694149 PMCID: PMC10484969 DOI: 10.1016/j.isci.2023.107632] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/17/2023] [Accepted: 08/11/2023] [Indexed: 09/12/2023] Open
Abstract
Microbial enzymes can address diverse challenges such as degradation of toxins. However, if the function of interest does not confer a sufficient fitness effect on the producer, the enzymatic function cannot be improved in the host cells by a conventional selection scheme. To overcome this limitation, we propose an alternative scheme, termed "partner-assisted artificial selection" (PAAS), wherein the population of enzyme producers is assisted by function-dependent feedback from an accessory population. Simulations investigating the efficiency of toxin degradation reveal that this strategy supports selection of improved degradation performance, which is robust to stochasticity in the model parameters. We observe that conventional considerations still apply in PAAS: more restrictive bottlenecks lead to stronger selection but add uncertainty. Overall, we offer a guideline for successful implementation of PAAS and highlight its potentials and limitations.
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Affiliation(s)
- Marco Zaccaria
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
| | - Natalie Sandlin
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
| | - Yoav Soen
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7670001, Israel
| | - Babak Momeni
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
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22
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Fraboul J, Biroli G, De Monte S. Artificial selection of communities drives the emergence of structured interactions. J Theor Biol 2023; 571:111557. [PMID: 37302465 DOI: 10.1016/j.jtbi.2023.111557] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 06/05/2023] [Indexed: 06/13/2023]
Abstract
Species-rich communities, such as the microbiota or microbial ecosystems, provide key functions for human health and climatic resilience. Increasing effort is being dedicated to design experimental protocols for selecting community-level functions of interest. These experiments typically involve selection acting on populations of communities, each of which is composed of multiple species. If numerical simulations started to explore the evolutionary dynamics of this complex, multi-scale system, a comprehensive theoretical understanding of the process of artificial selection of communities is still lacking. Here, we propose a general model for the evolutionary dynamics of communities composed of a large number of interacting species, described by disordered generalised Lotka-Volterra equations. Our analytical and numerical results reveal that selection for scalar community functions leads to the emergence, along an evolutionary trajectory, of a low-dimensional structure in an initially featureless interaction matrix. Such structure reflects the combination of the properties of the ancestral community and of the selective pressure. Our analysis determines how the speed of adaptation scales with the system parameters and the abundance distribution of the evolved communities. Artificial selection for larger total abundance is thus shown to drive increased levels of mutualism and interaction diversity. Inference of the interaction matrix is proposed as a method to assess the emergence of structured interactions from experimentally accessible measures.
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Affiliation(s)
- Jules Fraboul
- Laboratoire de Physique de l'École Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, F-75005, France.
| | - Giulio Biroli
- Laboratoire de Physique de l'École Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, F-75005, France
| | - Silvia De Monte
- Institut de Biologie de l'ENS (IBENS), Département de Biologie, Ecole normale supérieure, CNRS, INSERM, Université PSL, Paris, 75005, France; Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany
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23
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Petrushin IS, Vasilev IA, Markova YA. Drought Tolerance of Legumes: Physiology and the Role of the Microbiome. Curr Issues Mol Biol 2023; 45:6311-6324. [PMID: 37623217 PMCID: PMC10453936 DOI: 10.3390/cimb45080398] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/17/2023] [Accepted: 07/24/2023] [Indexed: 08/26/2023] Open
Abstract
Water scarcity and global warming make drought-tolerant plant species more in-demand than ever. The most drastic damage exerted by drought occurs during the critical growth stages of seed development and reproduction. In the course of their evolution, plants form a variety of drought-tolerance mechanisms, including recruiting beneficial microorganisms. Legumes (one of the three largest groups of higher plants) have unique features and the potential to adapt to abiotic stress. The available literature discusses the genetic (breeding) and physiological aspects of drought tolerance in legumes, neglecting the role of the microbiome. Our review aims to fill this gap: starting with the physiological mechanisms of legume drought adaptation, we describe the symbiotic relationship of the plant host with the microbial community and its role in facing drought. We consider two types of studies related to microbiomes in low-water conditions: comparisons and microbiome engineering (modulation). The first type of research includes diversity shifts and the isolation of microorganisms from the various plant niches to which they belong. The second type focuses on manipulating the plant holobiont through microbiome engineering-a promising biotech strategy to improve the yield and stress-resistance of legumes.
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Affiliation(s)
- Ivan S. Petrushin
- Siberian Institute of Plant Physiology and Biochemistry, Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia; (I.A.V.); (Y.A.M.)
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24
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Henry LP, Bergelson J. Evolutionary implications of host genetic control for engineering beneficial microbiomes. CURRENT OPINION IN SYSTEMS BIOLOGY 2023; 34:None. [PMID: 37287906 PMCID: PMC10242548 DOI: 10.1016/j.coisb.2023.100455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Engineering new functions in the microbiome requires understanding how host genetic control and microbe-microbe interactions shape the microbiome. One key genetic mechanism underlying host control is the immune system. The immune system can promote stability in the composition of the microbiome by reshaping the ecological dynamics of its members, but the degree of stability will depend on the interplay between ecological context, immune system development, and higher-order microbe-microbe interactions. The eco-evolutionary interplay affecting composition and stability should inform the strategies used to engineer new functions in the microbiome. We conclude with recent methodological developments that provide an important path forward for both engineering new functionality in the microbiome and broadly understanding how ecological interactions shape evolutionary processes in complex biological systems.
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25
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Blumenthal E, Mehta P. Geometry of ecological coexistence and niche differentiation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.21.537832. [PMID: 37131730 PMCID: PMC10153274 DOI: 10.1101/2023.04.21.537832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze Consumer Resource Models (CRMs) using geometric arguments. This has led to broadly applicable principles such as Tilman's R* and species coexistence cones. Here, we extend these arguments by constructing a novel geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species coexistence and enumerate ecologically-stable steady states and transitions between them. Collectively, these results constitute a qualitatively new way of understanding the role of species traits in shaping ecosystems within niche theory.
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Affiliation(s)
- Emmy Blumenthal
- Department of Physics, Boston University, Boston, MA 02215, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, Boston, MA 02215, USA
- Biological Design Center, Boston University, Boston, MA 02215, USA
- Faculty of Computing and Data Sciences, Boston University, Boston, MA 02215, USA
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26
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Sanchez A, Bajic D, Diaz-Colunga J, Skwara A, Vila JCC, Kuehn S. The community-function landscape of microbial consortia. Cell Syst 2023; 14:122-134. [PMID: 36796331 DOI: 10.1016/j.cels.2022.12.011] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/17/2022] [Accepted: 12/21/2022] [Indexed: 02/17/2023]
Abstract
Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.
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Affiliation(s)
- Alvaro Sanchez
- Department of Ecology & Evolutionary Biology & Microbial Sciences Institute, Yale University, New Haven, CT, USA; Department of Microbial Biotechnology, CNB-CSIC, Campus de Cantoblanco, Madrid, Spain.
| | - Djordje Bajic
- Department of Ecology & Evolutionary Biology & Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Juan Diaz-Colunga
- Department of Ecology & Evolutionary Biology & Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Abigail Skwara
- Department of Ecology & Evolutionary Biology & Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Jean C C Vila
- Department of Ecology & Evolutionary Biology & Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Seppe Kuehn
- Center for the Physics of Evolving Systems, The Unviersity of Chicago, Chicago, IL, USA; Department of Ecology and Evolution, The University of Chicago, Chicago, IL, USA
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27
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Gabrielli N, Maga-Nteve C, Kafkia E, Rettel M, Loeffler J, Kamrad S, Typas A, Patil KR. Unravelling metabolic cross-feeding in a yeast-bacteria community using 13 C-based proteomics. Mol Syst Biol 2023; 19:e11501. [PMID: 36779294 PMCID: PMC10090948 DOI: 10.15252/msb.202211501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/24/2023] [Accepted: 01/25/2023] [Indexed: 02/14/2023] Open
Abstract
Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13 C isotope tracing in peptides to elucidate cross-fed metabolites in co-cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13 C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of 13 C-based proteomics for uncovering microbial interactions.
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Affiliation(s)
| | | | - Eleni Kafkia
- European Molecular Biology Laboratory, Heidelberg, Germany.,Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Mandy Rettel
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jakob Loeffler
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Stephan Kamrad
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
| | | | - Kiran Raosaheb Patil
- European Molecular Biology Laboratory, Heidelberg, Germany.,Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
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28
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George AB, Korolev KS. Ecological landscapes guide the assembly of optimal microbial communities. PLoS Comput Biol 2023; 19:e1010570. [PMID: 36626403 PMCID: PMC9831326 DOI: 10.1371/journal.pcbi.1010570] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 09/13/2022] [Indexed: 01/11/2023] Open
Abstract
Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.
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Affiliation(s)
- Ashish B. George
- Department of Physics and Biological Design Center, Boston University, Boston, Massachusetts, United States of America
- Carl R. Woese Institute for Genomic Biology and Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Kirill S. Korolev
- Department of Physics and Biological Design Center, Boston University, Boston, Massachusetts, United States of America
- Graduate Program in Bioinformatics, Boston University, Boston, Massachusetts, United States of America
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29
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Hu H, Wang M, Huang Y, Xu Z, Xu P, Nie Y, Tang H. Guided by the principles of microbiome engineering: Accomplishments and perspectives for environmental use. MLIFE 2022; 1:382-398. [PMID: 38818482 PMCID: PMC10989833 DOI: 10.1002/mlf2.12043] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/19/2022] [Accepted: 09/02/2022] [Indexed: 06/01/2024]
Abstract
Although the accomplishments of microbiome engineering highlight its significance for the targeted manipulation of microbial communities, knowledge and technical gaps still limit the applications of microbiome engineering in biotechnology, especially for environmental use. Addressing the environmental challenges of refractory pollutants and fluctuating environmental conditions requires an adequate understanding of the theoretical achievements and practical applications of microbiome engineering. Here, we review recent cutting-edge studies on microbiome engineering strategies and their classical applications in bioremediation. Moreover, a framework is summarized for combining both top-down and bottom-up approaches in microbiome engineering toward improved applications. A strategy to engineer microbiomes for environmental use, which avoids the build-up of toxic intermediates that pose a risk to human health, is suggested. We anticipate that the highlighted framework and strategy will be beneficial for engineering microbiomes to address difficult environmental challenges such as degrading multiple refractory pollutants and sustain the performance of engineered microbiomes in situ with indigenous microorganisms under fluctuating conditions.
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Affiliation(s)
- Haiyang Hu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Miaoxiao Wang
- Department of Environmental Systems ScienceETH ZürichZürichSwitzerland
- Department of Environmental MicrobiologyETH ZürichEawagSwitzerland
| | - Yiqun Huang
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Zhaoyong Xu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Ping Xu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Yong Nie
- College of EngineeringPeking UniversityBeijingChina
| | - Hongzhi Tang
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
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30
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Taylor M, Janasky L, Vega N. Convergent structure with divergent adaptations in combinatorial microbiome communities. FEMS Microbiol Ecol 2022; 98:6726631. [PMID: 36170949 DOI: 10.1093/femsec/fiac115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/13/2022] [Accepted: 09/26/2022] [Indexed: 01/21/2023] Open
Abstract
Adaptation of replicate microbial communities frequently produces shared trajectories of community composition and structure. However, divergent adaptation of individual community members can occur and is associated with community-level divergence. The extent to which community-based adaptation of microbes should be convergent when community members are similar but not identical is, therefore, not well-understood. In these experiments, adaptation of combinatorial minimal communities of bacteria with the model host Caenorhabditis elegans produces structurally similar communities over time, but with divergent adaptation of member taxa and differences in community-level resistance to invasion. These results indicate that community-based adaptation from taxonomically similar starting points can produce compositionally similar communities that differ in traits of member taxa and in ecological properties.
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Affiliation(s)
- Megan Taylor
- Biology Department, Emory University, Atlanta, GA, 30322, United States
| | - Lili Janasky
- Biology Department, Emory University, Atlanta, GA, 30322, United States
| | - Nic Vega
- Biology Department, Emory University, Atlanta, GA, 30322, United States.,Physics Department, Emory University, Atlanta, GA, 30322, United States
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31
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Lalejini A, Dolson E, Vostinar AE, Zaman L. Artificial selection methods from evolutionary computing show promise for directed evolution of microbes. eLife 2022; 11:e79665. [PMID: 35916365 PMCID: PMC9444240 DOI: 10.7554/elife.79665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, which harnesses the principles of Darwinian evolution as a general-purpose search engine for solutions to challenging computational problems. Despite their overlapping approaches, artificial selection methods from evolutionary computing are not commonly applied to living systems in the laboratory. In this work, we ask whether parent selection algorithms-procedures for choosing promising progenitors-from evolutionary computation might be useful for directing the evolution of microbial populations when selecting for multiple functional traits. To do so, we introduce an agent-based model of directed microbial evolution, which we used to evaluate how well three selection algorithms from evolutionary computing (tournament selection, lexicase selection, and non-dominated elite selection) performed relative to methods commonly used in the laboratory (elite and top 10% selection). We found that multiobjective selection techniques from evolutionary computing (lexicase and non-dominated elite) generally outperformed the commonly used directed evolution approaches when selecting for multiple traits of interest. Our results motivate ongoing work transferring these multiobjective selection procedures into the laboratory and a continued evaluation of more sophisticated artificial selection methods.
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Affiliation(s)
- Alexander Lalejini
- Department of Ecology and Evolutionary Biology, University of MichiganAnn ArborUnited States
- Center for the Study of Complex Systems, University of MichiganAnn ArborUnited States
| | - Emily Dolson
- Department of Computer Science and Engineering, Michigan State UniversityEast LansingUnited States
- Program in Ecology, Evolution, and Behavior, Michigan State UniversityEast LansingUnited States
| | - Anya E Vostinar
- Computer Science Department, Carleton CollegeNorthfieldUnited States
| | - Luis Zaman
- Department of Ecology and Evolutionary Biology, University of MichiganAnn ArborUnited States
- Center for the Study of Complex Systems, University of MichiganAnn ArborUnited States
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32
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San León D, Nogales J. Toward merging bottom-up and top-down model-based designing of synthetic microbial communities. Curr Opin Microbiol 2022; 69:102169. [PMID: 35763963 DOI: 10.1016/j.mib.2022.102169] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/25/2022] [Accepted: 05/11/2022] [Indexed: 11/16/2022]
Abstract
The increasing interest of microbial communities as promising biocatalyst is leading an intense effort into the development of computational frameworks assisting the analysis and rational engineering of such complex ecosystems. Here, we critically review the recent computational and model-guided advances in the system-level engineering of microbiome, including both the rational bottom-up and the evolutionary top-down approaches. Furthermore, we highlight modeling and computational methods supporting both engineering paradigms. Finally, we discuss the advantages of combining both strategies into a hybrid top-down/bottom-up (middle-out) strategy to engineer synthetic microbial communities with improved performance and scope.
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Affiliation(s)
- David San León
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain; Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain.
| | - Juan Nogales
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain; Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain.
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33
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Izabel-Shen D, Li S, Luo T, Wang J, Li Y, Sun Q, Yu CP, Hu A. Repeated introduction of micropollutants enhances microbial succession despite stable degradation patterns. ISME COMMUNICATIONS 2022; 2:48. [PMID: 37938643 PMCID: PMC9723708 DOI: 10.1038/s43705-022-00129-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/04/2022] [Accepted: 05/09/2022] [Indexed: 05/28/2023]
Abstract
The increasing-volume release of micropollutants into natural surface waters has raised great concern due to their environmental accumulation. Persisting micropollutants can impact multiple generations of organisms, but their microbially-mediated degradation and their influence on community assembly remain understudied. Here, freshwater microbes were treated with several common micropollutants, alone or in combination, and then transferred every 5 days to fresh medium containing the same micropollutants to mimic the repeated exposure of microbes. Metabarcoding of 16S rRNA gene makers was chosen to study the succession of bacterial assemblages following micropollutant exposure. The removal rates of micropollutants were then measured to assess degradation capacity of the associated communities. The degradation of micropollutants did not accelerate over time but altered the microbial community composition. Community assembly was dominated by stochastic processes during early exposure, via random community changes and emergence of seedbanks, and deterministic processes later in the exposure, via advanced community succession. Early exposure stages were characterized by the presence of sensitive microorganisms such as Actinobacteria and Planctomycetes, which were then replaced by more tolerant bacteria such as Bacteroidetes and Gammaproteobacteria. Our findings have important implication for ecological feedback between microbe-micropollutants under anthropogenic climate change scenarios.
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Affiliation(s)
- Dandan Izabel-Shen
- Department of Ecology, Environment and Plant Sciences, Stockholm University, 106 91, Stockholm, Sweden
| | - Shuang Li
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Department of Environmental Microbiology, UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Tingwei Luo
- Institute of Marine Microbes and Ecospheres, State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Jianjun Wang
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Yan Li
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qian Sun
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chang-Ping Yu
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, 106, Taiwan
| | - Anyi Hu
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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34
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Mueller UG, Linksvayer TA. Microbiome breeding: conceptual and practical issues. Trends Microbiol 2022; 30:997-1011. [PMID: 35595643 DOI: 10.1016/j.tim.2022.04.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/30/2022] [Accepted: 04/11/2022] [Indexed: 10/18/2022]
Abstract
Microbiome breeding is a new artificial selection technique that seeks to change the genetic composition of microbiomes in order to benefit plant or animal hosts. Recent experimental and theoretical analyses have shown that microbiome breeding is possible whenever microbiome-encoded genetic factors affect host traits (e.g., health) and microbiomes are transmissible between hosts with sufficient fidelity, such as during natural microbiome transmission between individuals of social animals, or during experimental microbiome transplanting between plants. To address misunderstandings that stymie microbiome-breeding programs, we (i) clarify and visualize the corresponding elements of microbiome selection and standard selection; (ii) elucidate the eco-evolutionary processes underlying microbiome selection within a quantitative genetic framework to summarize practical guidelines that optimize microbiome breeding; and (iii) characterize the kinds of host species most amenable to microbiome breeding.
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Affiliation(s)
- Ulrich G Mueller
- Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA.
| | - Timothy A Linksvayer
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA.
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35
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Reyes-González D, De Luna-Valenciano H, Utrilla J, Sieber M, Peña-Miller R, Fuentes-Hernández A. Dynamic proteome allocation regulates the profile of interaction of auxotrophic bacterial consortia. ROYAL SOCIETY OPEN SCIENCE 2022; 9:212008. [PMID: 35592760 PMCID: PMC9066302 DOI: 10.1098/rsos.212008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/25/2022] [Indexed: 05/03/2023]
Abstract
Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding and occurs when the metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic inter-dependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function and stability of microbial communities. To evaluate how ppGpp-mediated resource allocation drives the population-level profile of interaction, here we postulate a multi-scale mathematical model that incorporates dynamics of proteome partition into a population dynamics model. We compare our computational results with experimental data obtained from co-cultures of auxotrophic Escherichia coli K12 strains under a range of amino acid concentrations and population structures. We conclude by arguing that the stringent response promotes cooperation by inhibiting the growth of fast-growing strains and promoting the synthesis of metabolites essential for other community members.
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Affiliation(s)
- D. Reyes-González
- Synthetic Biology Program, Center for Genomic Sciences, Universidad Autónoma de México, 62220 Cuernavaca, Mexico
| | - H. De Luna-Valenciano
- Synthetic Biology Program, Center for Genomic Sciences, Universidad Autónoma de México, 62220 Cuernavaca, Mexico
- Systems Biology Program, Center for Genomic Sciences, Universidad Nacional Autónoma de México, 62210 Cuernavaca, Mexico
| | - J. Utrilla
- Synthetic Biology Program, Center for Genomic Sciences, Universidad Autónoma de México, 62220 Cuernavaca, Mexico
| | - M. Sieber
- Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany
| | - R. Peña-Miller
- Systems Biology Program, Center for Genomic Sciences, Universidad Nacional Autónoma de México, 62210 Cuernavaca, Mexico
| | - A. Fuentes-Hernández
- Synthetic Biology Program, Center for Genomic Sciences, Universidad Autónoma de México, 62220 Cuernavaca, Mexico
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36
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Li S, Abdulkadir N, Schattenberg F, Nunes da Rocha U, Grimm V, Müller S, Liu Z. Stabilizing microbial communities by looped mass transfer. Proc Natl Acad Sci U S A 2022; 119:e2117814119. [PMID: 35446625 PMCID: PMC9169928 DOI: 10.1073/pnas.2117814119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 03/11/2022] [Indexed: 01/18/2023] Open
Abstract
Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates μ′. Subsets of cells that did not show net growth μ′SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.
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Affiliation(s)
- Shuang Li
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
| | - Nafi'u Abdulkadir
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
| | - Florian Schattenberg
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
| | - Ulisses Nunes da Rocha
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
| | - Volker Grimm
- Department of Ecological Modelling, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
- Plant Ecology and Nature Conservation, University of Potsdam, 14476 Potsdam, Germany
| | - Susann Müller
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany
| | - Zishu Liu
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
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37
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Celis AI, Aranda-Díaz A, Culver R, Xue K, Relman D, Shi H, Huang KC. Optimization of the 16S rRNA sequencing analysis pipeline for studying in vitro communities of gut commensals. iScience 2022; 25:103907. [PMID: 35340431 PMCID: PMC8941205 DOI: 10.1016/j.isci.2022.103907] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/24/2021] [Accepted: 02/08/2022] [Indexed: 01/04/2023] Open
Abstract
While microbial communities inhabit a wide variety of complex natural environments, in vitro culturing enables highly controlled conditions and high-throughput interrogation for generating mechanistic insights. In vitro assemblies of gut commensals have recently been introduced as models for the intestinal microbiota, which plays fundamental roles in host health. However, a protocol for 16S rRNA sequencing and analysis of in vitro samples that optimizes financial cost, time/effort, and accuracy/reproducibility has yet to be established. Here, we systematically identify protocol elements that have significant impact, introduce bias, and/or can be simplified. Our results indicate that community diversity and composition are generally unaffected by substantial protocol streamlining. Additionally, we demonstrate that a strictly aerobic halophile is an effective spike-in for estimating absolute abundances in communities of anaerobic gut commensals. This time- and money-saving protocol should accelerate discovery by increasing 16S rRNA data reliability and comparability and through the incorporation of absolute abundance estimates.
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Affiliation(s)
- Arianna I. Celis
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Andrés Aranda-Díaz
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Rebecca Culver
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Katherine Xue
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - David Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Handuo Shi
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kerwyn Casey Huang
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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38
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Zachar I, Boza G. The Evolution of Microbial Facilitation: Sociogenesis, Symbiogenesis, and Transition in Individuality. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.798045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Metabolic cooperation is widespread, and it seems to be a ubiquitous and easily evolvable interaction in the microbial domain. Mutual metabolic cooperation, like syntrophy, is thought to have a crucial role in stabilizing interactions and communities, for example biofilms. Furthermore, cooperation is expected to feed back positively to the community under higher-level selection. In certain cases, cooperation can lead to a transition in individuality, when freely reproducing, unrelated entities (genes, microbes, etc.) irreversibly integrate to form a new evolutionary unit. The textbook example is endosymbiosis, prevalent among eukaryotes but virtually lacking among prokaryotes. Concerning the ubiquity of syntrophic microbial communities, it is intriguing why evolution has not lead to more transitions in individuality in the microbial domain. We set out to distinguish syntrophy-specific aspects of major transitions, to investigate why a transition in individuality within a syntrophic pair or community is so rare. We review the field of metabolic communities to identify potential evolutionary trajectories that may lead to a transition. Community properties, like joint metabolic capacity, functional profile, guild composition, assembly and interaction patterns are important concepts that may not only persist stably but according to thought-provoking theories, may provide the heritable information at a higher level of selection. We explore these ideas, relating to concepts of multilevel selection and of informational replication, to assess their relevance in the debate whether microbial communities may inherit community-level information or not.
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39
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Liang Y, Ma A, Zhuang G. Construction of Environmental Synthetic Microbial Consortia: Based on Engineering and Ecological Principles. Front Microbiol 2022; 13:829717. [PMID: 35283862 PMCID: PMC8905317 DOI: 10.3389/fmicb.2022.829717] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 01/31/2022] [Indexed: 01/30/2023] Open
Abstract
In synthetic biology, engineering principles are applied to system design. The development of synthetic microbial consortia represents the intersection of synthetic biology and microbiology. Synthetic community systems are constructed by co-cultivating two or more microorganisms under certain environmental conditions, with broad applications in many fields including ecological restoration and ecological theory. Synthetic microbial consortia tend to have high biological processing efficiencies, because the division of labor reduces the metabolic burden of individual members. In this review, we focus on the environmental applications of synthetic microbial consortia. Although there are many strategies for the construction of synthetic microbial consortia, we mainly introduce the most widely used construction principles based on cross-feeding. Additionally, we propose methods for constructing synthetic microbial consortia based on traits and spatial structure from the perspective of ecology to provide a basis for future work.
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Affiliation(s)
- Yu Liang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
- College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Anzhou Ma
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
- College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Guoqiang Zhuang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
- College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, China
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40
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Top-down and bottom-up cohesiveness in microbial community coalescence. Proc Natl Acad Sci U S A 2022; 119:2111261119. [PMID: 35105804 PMCID: PMC8832967 DOI: 10.1073/pnas.2111261119] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/29/2021] [Indexed: 12/13/2022] Open
Abstract
In the microbial world, it is common for previously isolated communities to come in contact with one another. This phenomenon is known as community coalescence. Despite it being a key process in the assembly of microbial communities, little is known about the mechanisms that determine its outcomes. Here we present an experimental system that allowed us to study over 100 coalescence events between previously segregated microbiomes. Our results, predicted by a mathematical model, provide direct evidence of ecological coselection: the situation where members of a community recruit one another during coalescence. Our combined experimental and theoretical framework represents a powerful tool to predict the outcomes and interrogate the mechanisms of community coalescence. Microbial communities frequently invade one another as a whole, a phenomenon known as community coalescence. Despite its potential importance for the assembly, dynamics, and stability of microbial consortia, as well as its prospective utility for microbiome engineering, our understanding of the processes that govern it is still very limited. Theory has suggested that microbial communities may exhibit cohesiveness in the face of invasions emerging from collective metabolic interactions across microbes and their environment. This cohesiveness may lead to correlated invasional outcomes, where the fate of a given taxon is determined by that of other members of its community—a hypothesis known as ecological coselection. Here, we have performed over 100 invasion and coalescence experiments with microbial communities of various origins assembled in two different synthetic environments. We show that the dominant members of the primary communities can recruit their rarer partners during coalescence (top-down coselection) and also be recruited by them (bottom-up coselection). With the aid of a consumer-resource model, we found that the emergence of top-down or bottom-up cohesiveness is modulated by the structure of the underlying cross-feeding networks that sustain the coalesced communities. The model also predicts that these two forms of ecological coselection cannot co-occur under our conditions, and we have experimentally confirmed that one can be strong only when the other is weak. Our results provide direct evidence that collective invasions can be expected to produce ecological coselection as a result of cross-feeding interactions at the community level.
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41
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Korkmazhan E, Dunn AR. High-order correlations in species interactions lead to complex diversity-stability relationships for ecosystems. Phys Rev E 2022; 105:014406. [PMID: 35193273 DOI: 10.1103/physreve.105.014406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/22/2021] [Indexed: 11/07/2022]
Abstract
How ecosystems maintain stability is an active area of research. Inspired by applications of random matrix theory in nuclear physics, May showed decades ago that in an ecosystem model with many randomly interacting species, increasing species diversity decreases the stability of the ecosystem. There have since been many additions to May's efforts, one being an improved understanding the effect of mutualistic, competitive, or predator-prey-like correlations between pairs of species. Here we extend a random matrix technique developed in the context of spin-glass theory to study the effect of high-order correlations among species interactions. The resulting analytically solvable models include next-to-nearest-neighbor correlations in the species interaction network, such as the enemy of my enemy is my friend, as well as higher-order correlations. We find qualitative differences from May and others' models, including nonmonotonic diversity-stability relationships. Furthermore, inclusion of particular next-to-nearest-neighbor correlations in predator-prey as opposed to mutualist-competitive networks causes the former to transition to being more stable at higher species diversity. We discuss potential applicability of our results to microbiota engineering and to the ecology of interpredator interactions, such as cub predation between lions and hyenas as well as companionship between humans and dogs.
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Affiliation(s)
- Elgin Korkmazhan
- Biophysics Program, Stanford University, Stanford, California 94305, USA and Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
| | - Alexander R Dunn
- Biophysics Program, Stanford University, Stanford, California 94305, USA and Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
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Abstract
The microorganisms associated with an organism, the microbiome, have a strong and wide impact in their host biology. In particular, the microbiome modulates both the host defense responses and immunity, thus influencing the fate of infections by pathogens. Indeed, this immune modulation and/or interaction with pathogenic viruses can be essential to define the outcome of viral infections. Understanding the interplay between the microbiome and pathogenic viruses opens future venues to fight viral infections and enhance the efficacy of antiviral therapies. An increasing number of researchers are focusing on microbiome-virus interactions, studying diverse combinations of microbial communities, hosts, and pathogenic viruses. Here, we aim to review these studies, providing an integrative overview of the microbiome impact on viral infection across different pathosystems.
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Affiliation(s)
- Rubén González
- Instituto de Biología Integrativa de Sistemas, Consejo Superior de Investigaciones Científicas-Universitat de València, Paterna, Valencia, Spain
| | - Santiago F. Elena
- Instituto de Biología Integrativa de Sistemas, Consejo Superior de Investigaciones Científicas-Universitat de València, Paterna, Valencia, Spain
- The Santa Fe Institute, Santa Fe, New Mexico, USA
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Abstract
We develop a method to artificially select for rhizosphere microbiomes that confer salt tolerance to the model grass Brachypodium distachyon grown under sodium salt stress or aluminum salt stress. In a controlled greenhouse environment, we differentially propagated rhizosphere microbiomes between plants of a nonevolving, highly inbred plant population; therefore, only microbiomes evolved in our experiment, but the plants did not evolve in parallel. To maximize microbiome perpetuation when transplanting microbiomes between plants and, thus, maximize response to microbiome selection, we improved earlier methods by (i) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (ii) fractionating microbiomes before transfer between plants to harvest, perpetuate, and select on only bacterial and viral microbiome components; (iii) ramping of salt stress gradually from minor to extreme salt stress with each selection cycle to minimize the chance of overstressing plants; (iv) using two nonselection control treatments (e.g., nonselection microbial enrichment and null inoculation) that permit comparison to the improving fitness benefits that selected microbiomes impart on plants. Unlike previous methods, our selection protocol generated microbiomes that enhance plant fitness after only 1 to 3 rounds of microbiome selection. After nine rounds of microbiome selection, the effect of microbiomes selected to confer tolerance to aluminum salt stress was nonspecific (these artificially selected microbiomes equally ameliorate sodium and aluminum salt stresses), but the effect of microbiomes selected to confer tolerance to sodium salt stress was specific (these artificially selected microbiomes do not confer tolerance to aluminum salt stress). Plants with artificially selected microbiomes had 55 to 205% greater seed production than plants with unselected control microbiomes. IMPORTANCE We developed an experimental protocol that improves earlier methods of artificial selection on microbiomes and then tested the efficacy of our protocol to breed root-associated bacterial microbiomes that confer salt tolerance to a plant. Salt stress limits growth and seed production of crop plants, and artificially selected microbiomes conferring salt tolerance may ultimately help improve agricultural productivity. Unlike previous experiments of microbiome selection, our selection protocol generated microbiomes that enhance plant productivity after only 1 to 3 rounds of artificial selection on root-associated microbiomes, increasing seed production under extreme salt stress by 55 to 205% after nine rounds of microbiome selection. Although we artificially selected microbiomes under controlled greenhouse conditions that differ from outdoor conditions, increasing seed production by 55 to 205% under extreme salt stress is a remarkable enhancement of plant productivity compared to traditional plant breeding. We describe a series of additional experimental protocols that will advance insights into key parameters that determine efficacy and response to microbiome selection.
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Xie L, Shou W. Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities. Nat Commun 2021; 12:6799. [PMID: 34815384 PMCID: PMC8611069 DOI: 10.1038/s41467-021-26647-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 09/30/2021] [Indexed: 11/23/2022] Open
Abstract
Microbial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and "reproduce" the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a "community function landscape", we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j ; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/ .
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Affiliation(s)
- Li Xie
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
| | - Wenying Shou
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.
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Rocca JD, Muscarella ME, Peralta AL, Izabel-Shen D, Simonin M. Guided by Microbes: Applying Community Coalescence Principles for Predictive Microbiome Engineering. mSystems 2021; 6:e0053821. [PMID: 34402638 PMCID: PMC8407356 DOI: 10.1128/msystems.00538-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Every seed germinating in soils, wastewater treatment, and stream confluence exemplify microbial community coalescence-the blending of previously isolated communities. Here, we present theoretical and experimental knowledge on how separated microbial communities mix, with particular focus on managed ecosystems. We adopt the community coalescence framework, which integrates metacommunity theory and meta-ecosystem dynamics, and highlight the prevalence of these coalescence events within microbial systems. Specifically, we (i) describe fundamental types of community coalescences using naturally occurring and managed examples, (ii) offer ways forward to leverage community coalescence in managed systems, and (iii) emphasize the importance of microbial ecological theory to achieving desired coalescence outcomes. Further, considering the massive dispersal events of microbiomes and their coalescences is pivotal to better predict microbial community dynamics and responses to disturbances. We conclude our piece by highlighting some challenges and unanswered question yet to be tackled.
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Affiliation(s)
- Jennifer D. Rocca
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Mario E. Muscarella
- Institute of Arctic Biology, Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, Alaska, USA
| | - Ariane L. Peralta
- Department of Biology, East Carolina University, Greenville, North Carolina, USA
| | - Dandan Izabel-Shen
- Department of Ecology, Environment, and Plant Sciences, Stockholm University, Stockholm, Sweden
| | - Marie Simonin
- University of Angers, Institut Agro, INRAE, IRHS, SFR QUASAV, Angers, France
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Pacheco AR, Segrè D. An evolutionary algorithm for designing microbial communities via environmental modification. J R Soc Interface 2021; 18:20210348. [PMID: 34157894 PMCID: PMC8220269 DOI: 10.1098/rsif.2021.0348] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.
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Affiliation(s)
- Alan R Pacheco
- Graduate Program in Bioinformatics and Biological Design Center, Boston University, Boston, MA 02215, USA
| | - Daniel Segrè
- Graduate Program in Bioinformatics and Biological Design Center, Boston University, Boston, MA 02215, USA.,Department of Biology, Boston University, Boston, MA 02215, USA.,Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Department of Physics, Boston University, Boston, MA 02215, USA
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Bergelson J, Kreitman M, Petrov DA, Sanchez A, Tikhonov M. Functional biology in its natural context: A search for emergent simplicity. eLife 2021; 10:e67646. [PMID: 34096867 PMCID: PMC8184206 DOI: 10.7554/elife.67646] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/28/2021] [Indexed: 01/03/2023] Open
Abstract
The immeasurable complexity at every level of biological organization creates a daunting task for understanding biological function. Here, we highlight the risks of stripping it away at the outset and discuss a possible path toward arriving at emergent simplicity of understanding while still embracing the ever-changing complexity of biotic interactions that we see in nature.
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Affiliation(s)
- Joy Bergelson
- Department of Ecology & Evolution, University of ChicagoChicagoUnited States
| | - Martin Kreitman
- Department of Ecology & Evolution, University of ChicagoChicagoUnited States
| | - Dmitri A Petrov
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Alvaro Sanchez
- Department of Ecology & Evolutionary Biology, Yale UniversityNew HavenUnited States
| | - Mikhail Tikhonov
- Department of Physics, Washington University in St LouisSt. LouisUnited States
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48
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Affiliation(s)
- Silvia De Monte
- Institut de Biologie de l'École Normale Supérieure, École Normale Supérieure, CNRS, INSERM, PSL Research University, Paris, France. .,Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plőn, Germany.
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