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Atasoy M, Scott WT, Regueira A, Mauricio-Iglesias M, Schaap PJ, Smidt H. Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches. Biotechnol Adv 2024; 73:108363. [PMID: 38657743 DOI: 10.1016/j.biotechadv.2024.108363] [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: 12/07/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 04/26/2024]
Abstract
In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.
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Affiliation(s)
- Merve Atasoy
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Department of Environmental Technology, Wageningen University & Research, Wageningen, the Netherlands; Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands.
| | - William T Scott
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
| | - Alberte Regueira
- CRETUS, Department of Chemical Engineering, Universidade de Santiago de Compostela, Santiago de Compostela, Spain; Center for Microbial Ecology and Technology (CMET), Ghent University, Ghent, Belgium; Center for Advanced Process Technology for Urban Resource Recovery (CAPTURE), Frieda Saeysstraat 1, Ghent, Belgium.
| | - Miguel Mauricio-Iglesias
- CRETUS, Department of Chemical Engineering, Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
| | - Peter J Schaap
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
| | - Hauke Smidt
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands.
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2
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Jin R, Song J, Liu C, Lin R, Liang D, Aweya JJ, Weng W, Zhu L, Shang J, Yang S. Synthetic microbial communities: Novel strategies to enhance the quality of traditional fermented foods. Compr Rev Food Sci Food Saf 2024; 23:e13388. [PMID: 38865218 DOI: 10.1111/1541-4337.13388] [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: 04/27/2024] [Accepted: 05/19/2024] [Indexed: 06/14/2024]
Abstract
Consumers are attracted to traditional fermented foods due to their unique flavor and nutritional value. However, the traditional fermentation technique can no longer accommodate the requirements of the food industry. Traditional fermented foods produce hazardous compounds, off-odor, and anti-nutritional factors, reducing product stability. The microbial system complexity of traditional fermented foods resulting from the open fermentation process has made it challenging to regulate these problems by modifying microbial behaviors. Synthetic microbial communities (SynComs) have been shown to simplify complex microbial communities and allow for the targeted design of microbial communities, which has been applied in processing traditional fermented foods. Herein, we describe the theoretical information of SynComs, particularly microbial physiological processes and their interactions. This paper discusses current approaches to creating SynComs, including designing, building, testing, and learning, with typical applications and fundamental techniques. Based on various traditional fermented food innovation demands, the potential and application of SynComs in enhancing the quality of traditional fermented foods are highlighted. SynComs showed superior performance in regulating the quality of traditional fermented foods using the interaction of core microorganisms to reduce the hazardous compounds of traditional fermented foods and improve flavor. Additionally, we presented the current status and future perspectives of SynComs for improving the quality of traditional fermented foods.
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Affiliation(s)
- Ritian Jin
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Jing Song
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Chang Liu
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Rong Lin
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Duo Liang
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Jude Juventus Aweya
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
| | - Wuyin Weng
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
| | - Longji Zhu
- Institute of Urban Environment, Chinese Academy of Science, Xiamen, China
| | - Jiaqi Shang
- Key Laboratory of Bionic Engineering, College of Biological and Agricultural Engineering, Jilin University, Changchun, China
| | - Shen Yang
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, China
- Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Jimei University, Xiamen, China
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3
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Pawlowska TE. Symbioses between fungi and bacteria: from mechanisms to impacts on biodiversity. Curr Opin Microbiol 2024; 80:102496. [PMID: 38875733 DOI: 10.1016/j.mib.2024.102496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 05/20/2024] [Accepted: 05/31/2024] [Indexed: 06/16/2024]
Abstract
Symbiotic interactions between fungi and bacteria range from positive to negative. They are ubiquitous in free-living as well as host-associated microbial communities worldwide. Yet, the impact of fungal-bacterial symbioses on the organization and dynamics of microbial communities is uncertain. There are two reasons for this uncertainty: (1) knowledge gaps in the understanding of the genetic mechanisms underpinning fungal-bacterial symbioses and (2) prevailing interpretations of ecological theory that favor antagonistic interactions as drivers stabilizing biological communities despite the existence of models emphasizing contributions of positive interactions. This review synthesizes information on fungal-bacterial symbioses common in the free-living microbial communities of the soil as well as in host-associated polymicrobial biofilms. The interdomain partnerships are considered in the context of the relevant community ecology models, which are discussed critically.
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Affiliation(s)
- Teresa E Pawlowska
- School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA.
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Vimal SR, Singh JS, Kumar A, Prasad SM. The plant endomicrobiome: Structure and strategies to produce stress resilient future crop. CURRENT RESEARCH IN MICROBIAL SCIENCES 2024; 6:100236. [PMID: 38756233 PMCID: PMC11097330 DOI: 10.1016/j.crmicr.2024.100236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024] Open
Abstract
Plants have a microbiome, a diverse community of microorganisms, including bacteria, fungi, and viruses, living inside and on their tissues. Versatile endophytic microorganisms inhabited in every plant part without causing disease and develop endophytic microbiome or endo-microbiome. Plant endo-microbiome are drawn by the nutrient rich micro-environment, and in turn some microbes mutualistically endorse and protect plant from adverse environmental stresses. Plant endo-microbiome interact within well-designed host equilibrium containing xylem, phloem, nutrients, phytohormones, metabolites and shift according to environmental and nutritional change. Plant endo-microbiome regulate and respond to environmental variations, pathogens, herbivores by producing stress regulators, organic acids, secondary metabolites, stress hormones as well as unknown substances and signalling molecules. Endomicrobiome efficiently synthesizes multiple bioactive compounds, stress phytohormones with high competence. The technological innovation as next generation genomics biology and high-throughput multiomics techniques stepping stones on the illumination of critical endo-microbiome communities and functional characterization that aid in improving plant physiology, biochemistry and immunity interplay for best crop productivity. This review article contains deeper insight in endomicrobiome related research work in last years, recruitment, niche development, nutrient dynamics, stress removal mechanisms, bioactive services in plant health development, community architecture and communication, and immunity interplay in producing stress resilient future crop.
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Affiliation(s)
- Shobhit Raj Vimal
- Ranjan Plant Physiology & Biochemistry Laboratory, Department of Botany, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India
| | - Jay Shankar Singh
- Department of Environmental Microbiology, School for Earth and Environmental Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, Uttar Pradesh, India
| | - Ashwani Kumar
- Metagenomics and Secretomics Research Laboratory, Department of Botany, University of Allahabad (A Central University), Prayagraj 211002, Uttar Pradesh, India
| | - Sheo Mohan Prasad
- Ranjan Plant Physiology & Biochemistry Laboratory, Department of Botany, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India
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Sulaiman JE, Thompson J, Qian Y, Vivas EI, Diener C, Gibbons SM, Safdar N, Venturelli OS. Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.13.589383. [PMID: 38659900 PMCID: PMC11042340 DOI: 10.1101/2024.04.13.589383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
The human gut pathogen Clostridioides difficile displays extreme genetic variability and confronts a changeable nutrient landscape in the gut. We mapped gut microbiota inter-species interactions impacting the growth and toxin production of diverse C. difficile strains in different nutrient environments. Although negative interactions impacting C. difficile are prevalent in environments promoting resource competition, they are sparse in an environment containing C. difficile-preferred carbohydrates. C. difficile strains display differences in interactions with Clostridium scindens and the ability to compete for proline. C. difficile toxin production displays substantial community-context dependent variation and does not trend with growth-mediated inter-species interactions. C. difficile shows substantial differences in transcriptional profiles in the presence of the closely related species C. hiranonis or C. scindens. In co-culture with C. hiranonis, C. difficile exhibits massive alterations in metabolism and other cellular processes, consistent with their high metabolic overlap. Further, Clostridium hiranonis inhibits the growth and toxin production of diverse C. difficile strains across different nutrient environments and ameliorates the disease severity of a C. difficile challenge in a murine model. In sum, strain-level variability and nutrient environments are major variables shaping gut microbiota interactions with C. difficile.
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Affiliation(s)
- Jordy Evan Sulaiman
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Jaron Thompson
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Yili Qian
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Eugenio I. Vivas
- Gnotobiotic Animal Core Facility, University of Wisconsin-Madison, Madison, WI, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Sean M. Gibbons
- Institute for Systems Biology, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- eScience Institute, University of Washington, Seattle, WA, USA
| | - Nasia Safdar
- Division of Infectious Disease, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medicine, William S. Middleton Veterans Hospital Madison, Madison, WI, USA
| | - Ophelia S. Venturelli
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
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6
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Liu Y, Cheng YY, Thompson J, Zhou Z, Vivas EI, Warren MF, Rey FE, Anantharaman K, Venturelli OS. Shaping human gut community assembly and butyrate production by controlling the arginine dihydrolase pathway. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.10.523442. [PMID: 37986770 PMCID: PMC10659395 DOI: 10.1101/2023.01.10.523442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The arginine dihydrolase pathway (arc operon) present in a subset of diverse human gut species enables arginine catabolism. This specialized metabolic pathway can alter environmental pH and nitrogen availability, which in turn could shape gut microbiota inter-species interactions. By exploiting synthetic control of gene expression, we investigated the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and health-relevant metabolite profiles in vitro and in the murine gut. By stabilizing environmental pH, the arc operon reduced variability in community composition across different initial pH perturbations. The abundance of butyrate producing bacteria were altered in response to arc operon activity and butyrate production was enhanced in a physiologically relevant pH range. While the presence of the arc operon altered community dynamics, it did not impact production of short chain fatty acids. Dynamic computational modeling of pH-mediated interactions reveals the quantitative contribution of this mechanism to community assembly. In sum, our framework to quantify the contribution of molecular pathways and mechanism modalities on microbial community dynamics and functions could be applied more broadly.
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Affiliation(s)
- Yiyi Liu
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison WI 53706
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706
| | - Yu-Yu Cheng
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706
| | - Jaron Thompson
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison WI 53706
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706
| | - Zhichao Zhou
- Department of Bacteriology, University of Wisconsin-Madison, WI 53706
| | - Eugenio I. Vivas
- Department of Bacteriology, University of Wisconsin-Madison, WI 53706
- Gnotobiotic Animal Core Facility, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Matthew F. Warren
- Department of Bacteriology, University of Wisconsin-Madison, WI 53706
| | - Federico E. Rey
- Department of Bacteriology, University of Wisconsin-Madison, WI 53706
| | | | - Ophelia S. Venturelli
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison WI 53706
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706
- Department of Bacteriology, University of Wisconsin-Madison, WI 53706
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7
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Srinivasan S, Jnana A, Murali TS. Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions. MICROBIAL ECOLOGY 2024; 87:56. [PMID: 38587642 PMCID: PMC11001700 DOI: 10.1007/s00248-024-02370-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 03/28/2024] [Indexed: 04/09/2024]
Abstract
Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.
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Affiliation(s)
- Shanchana Srinivasan
- Department of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India
| | - Apoorva Jnana
- Department of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India
| | - Thokur Sreepathy Murali
- Department of Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, India.
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8
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Geesink P, ter Horst J, Ettema TJG. More than the sum of its parts: uncovering emerging effects of microbial interactions in complex communities. FEMS Microbiol Ecol 2024; 100:fiae029. [PMID: 38444203 PMCID: PMC10950044 DOI: 10.1093/femsec/fiae029] [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: 11/15/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 03/07/2024] Open
Abstract
Microbial communities are not only shaped by the diversity of microorganisms and their individual metabolic potential, but also by the vast amount of intra- and interspecies interactions that can occur pairwise interactions among microorganisms, we suggest that more attention should be drawn towards the effects on the entire microbiome that emerge from individual interactions between community members. The production of certain metabolites that can be tied to a specific microbe-microbe interaction might subsequently influence the physicochemical parameters of the habitat, stimulate a change in the trophic network of the community or create new micro-habitats through the formation of biofilms, similar to the production of antimicrobial substances which might negatively affect only one microorganism but cause a ripple effect on the abundance of other community members. Here, we argue that combining established as well as innovative laboratory and computational methods is needed to predict novel interactions and assess their secondary effects. Such efforts will enable future microbiome studies to expand our knowledge on the dynamics of complex microbial communities.
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Affiliation(s)
- Patricia Geesink
- Laboratory of Microbiology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - Jolanda ter Horst
- Laboratory of Microbiology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - Thijs J G Ettema
- Laboratory of Microbiology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
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9
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Ponciano JM, Gómez JP, Ravel J, Forney LJ. Inferring stability and persistence in the vaginal microbiome: A stochastic model of ecological dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.02.581600. [PMID: 38464272 PMCID: PMC10925280 DOI: 10.1101/2024.03.02.581600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The interplay of stochastic and ecological processes that govern the establishment and persistence of host-associated microbial communities is not well understood. Here we illustrate the conceptual and practical advantages of fitting stochastic population dynamics models to multi-species bacterial time series data. We show how the stability properties, fluctuation regimes and persistence probabilities of human vaginal microbial communities can be better understood by explicitly accommodating three sources of variability in ecological stochastic models of multi-species abundances: 1) stochastic biotic and abiotic forces, 2) ecological feedback and 3) sampling error. Rooting our modeling tool in stochastic population dynamics modeling theory was key to apply standardized measures of a community's reaction to environmental variation that ultimately depends on the nature and intensity of the intra-specific and inter-specific interaction strengths. Using estimates of model parameters, we developed a Risk Prediction Monitoring (RPM) tool that estimates temporal changes in persistence probabilities for any bacterial group of interest. This method mirrors approaches that are often used in conservation biology in which a measure of extinction risks is periodically updated with any change in a population or community. Additionally, we show how to use estimates of interaction strengths and persistence probabilities to formulate hypotheses regarding the molecular mechanisms and genetic composition that underpin different types of interactions. Instead of seeking a definition of "dysbiosis" we propose to translate concepts of theoretical ecology and conservation biology methods into practical approaches for the management of human-associated bacterial communities.
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Affiliation(s)
| | - Juan P. Gómez
- Departamento de Química y Biología, Universidad del Norte, Barranquilla, Colombia
| | - Jacques Ravel
- Institute for Genome Sciences and Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD
| | - Larry J. Forney
- Institute for Interdisciplinary Data Science and Department of Biological Sciences, University of Idaho, Moscow, ID
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10
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Law SR, Mathes F, Paten AM, Alexandre PA, Regmi R, Reid C, Safarchi A, Shaktivesh S, Wang Y, Wilson A, Rice SA, Gupta VVSR. Life at the borderlands: microbiomes of interfaces critical to One Health. FEMS Microbiol Rev 2024; 48:fuae008. [PMID: 38425054 PMCID: PMC10977922 DOI: 10.1093/femsre/fuae008] [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: 07/26/2023] [Revised: 02/12/2024] [Accepted: 02/27/2024] [Indexed: 03/02/2024] Open
Abstract
Microbiomes are foundational components of the environment that provide essential services relating to food security, carbon sequestration, human health, and the overall well-being of ecosystems. Microbiota exert their effects primarily through complex interactions at interfaces with their plant, animal, and human hosts, as well as within the soil environment. This review aims to explore the ecological, evolutionary, and molecular processes governing the establishment and function of microbiome-host relationships, specifically at interfaces critical to One Health-a transdisciplinary framework that recognizes that the health outcomes of people, animals, plants, and the environment are tightly interconnected. Within the context of One Health, the core principles underpinning microbiome assembly will be discussed in detail, including biofilm formation, microbial recruitment strategies, mechanisms of microbial attachment, community succession, and the effect these processes have on host function and health. Finally, this review will catalogue recent advances in microbiology and microbial ecology methods that can be used to profile microbial interfaces, with particular attention to multi-omic, advanced imaging, and modelling approaches. These technologies are essential for delineating the general and specific principles governing microbiome assembly and functions, mapping microbial interconnectivity across varying spatial and temporal scales, and for the establishment of predictive frameworks that will guide the development of targeted microbiome-interventions to deliver One Health outcomes.
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Affiliation(s)
- Simon R Law
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Canberra, ACT 2601, Australia
| | - Falko Mathes
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Floreat, WA 6014, Australia
| | - Amy M Paten
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Canberra, ACT 2601, Australia
| | - Pamela A Alexandre
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, St Lucia, Qld 4072, Australia
| | - Roshan Regmi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
| | - Cameron Reid
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Urrbrae, SA 5064, Australia
| | - Azadeh Safarchi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Westmead, NSW 2145, Australia
| | - Shaktivesh Shaktivesh
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Data 61, Clayton, Vic 3168, Australia
| | - Yanan Wang
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Adelaide SA 5000, Australia
| | - Annaleise Wilson
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Geelong, Vic 3220, Australia
| | - Scott A Rice
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture, and Food, Westmead, NSW 2145, Australia
| | - Vadakattu V S R Gupta
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
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11
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Jin Y, Chen W, Hu J, Wang J, Ren H. Constructions of quorum sensing signaling network for activated sludge microbial community. ISME COMMUNICATIONS 2024; 4:ycae018. [PMID: 38500706 PMCID: PMC10945367 DOI: 10.1093/ismeco/ycae018] [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: 11/03/2023] [Revised: 01/04/2024] [Accepted: 01/22/2024] [Indexed: 03/20/2024]
Abstract
In wastewater treatment systems, the interactions among various microbes based on chemical signals, namely quorum sensing (QS), play critical roles in influencing microbial structure and function. However, it is challenging to understand the QS-controlled behaviors and the underlying mechanisms in complex microbial communities. In this study, we constructed a QS signaling network, providing insights into the intra- and interspecies interactions of activated sludge microbial communities based on diverse QS signal molecules. Our research underscores the role of diffusible signal factors in both intra- and interspecies communication among activated sludge microorganisms, and signal molecules commonly considered to mediate intraspecies communication may also participate in interspecies communication. QS signaling molecules play an important role as communal resources among the entire microbial group. The communication network within the microbial community is highly redundant, significantly contributing to the stability of natural microbial systems. This work contributes to the establishment of QS signaling network for activated sludge microbial communities, which may complement metabolic exchanges in explaining activated sludge microbial community structure and may help with a variety of future applications, such as making the dynamics and resilience of highly complex ecosystems more predictable.
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Affiliation(s)
- Ying Jin
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wenkang Chen
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jie Hu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jinfeng Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Hongqiang Ren
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
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12
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Baig Y, Ma HR, Xu H, You L. Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics. Nat Commun 2023; 14:7937. [PMID: 38049401 PMCID: PMC10696002 DOI: 10.1038/s41467-023-43455-0] [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: 01/30/2023] [Accepted: 11/09/2023] [Indexed: 12/06/2023] Open
Abstract
The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitative analysis and engineering. By using autoencoder neural networks, we show that microbial growth dynamics can be compressed into low-dimensional representations and reconstructed with high fidelity. These low-dimensional embeddings are just as effective, if not better, than raw data for tasks such as identifying bacterial strains, predicting traits like antibiotic resistance, and predicting community dynamics. Additionally, we demonstrate that essential dynamical information of these systems can be captured using far fewer variables than traditional mechanistic models. Our work suggests that machine learning can enable the creation of concise representations of high-dimensional microbiome dynamics to facilitate data analysis and gain new biological insights.
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Affiliation(s)
- Yasa Baig
- Department of Physics, Duke University, Durham, NC, USA
- Department of Computer Science, Duke University, Durham, NC, USA
| | - Helena R Ma
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Quantitative Biodesign, Duke University, Durham, NC, USA
| | - Helen Xu
- Department of Computer Science, Duke University, Durham, NC, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Center for Quantitative Biodesign, Duke University, Durham, NC, USA.
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA.
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13
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Picot A, Shibasaki S, Meacock OJ, Mitri S. Microbial interactions in theory and practice: when are measurements compatible with models? Curr Opin Microbiol 2023; 75:102354. [PMID: 37421708 DOI: 10.1016/j.mib.2023.102354] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/01/2023] [Accepted: 06/07/2023] [Indexed: 07/10/2023]
Abstract
Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.
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Affiliation(s)
- Aurore Picot
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France; Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Shota Shibasaki
- Department of Biology, University of North Carolina at Greensboro, Greensboro, NC, USA; Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Oliver J Meacock
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
| | - Sara Mitri
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
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14
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Boruta T. Computation-aided studies related to the induction of specialized metabolite biosynthesis in microbial co-cultures: An introductory overview. Comput Struct Biotechnol J 2023; 21:4021-4029. [PMID: 37649711 PMCID: PMC10462793 DOI: 10.1016/j.csbj.2023.08.011] [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: 05/14/2023] [Revised: 08/14/2023] [Accepted: 08/14/2023] [Indexed: 09/01/2023] Open
Abstract
Co-cultivation is an effective method of inducing the production of specialized metabolites (SMs) in microbial strains. By mimicking the ecological interactions that take place in natural environment, this approach enables to trigger the biosynthesis of molecules which are not formed under monoculture conditions. Importantly, microbial co-cultivation may lead to the discovery of novel chemical entities of pharmaceutical interest. The experimental efforts aimed at the induction of SMs are greatly facilitated by computational techniques. The aim of this overview is to highlight the relevance of computational methods for the investigation of SM induction via microbial co-cultivation. The concepts related to the induction of SMs in microbial co-cultures are briefly introduced by addressing four areas associated with the SM induction workflows, namely the detection of SMs formed exclusively under co-culture conditions, the annotation of induced SMs, the identification of SM producer strains, and the optimization of fermentation conditions. The computational infrastructure associated with these areas, including the tools of multivariate data analysis, molecular networking, genome mining and mathematical optimization, is discussed in relation to the experimental results described in recent literature. The perspective on the future developments in the field, mainly in relation to the microbiome-related research, is also provided.
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Affiliation(s)
- Tomasz Boruta
- Lodz University of Technology, Faculty of Process and Environmental Engineering, Department of Bioprocess Engineering, ul. Wólczańska 213, 93-005 Łódź, Poland
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15
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Hessler T, Huddy RJ, Sachdeva R, Lei S, Harrison STL, Diamond S, Banfield JF. Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms. Nat Commun 2023; 14:4768. [PMID: 37553333 PMCID: PMC10409787 DOI: 10.1038/s41467-023-40360-4] [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: 02/15/2023] [Accepted: 07/20/2023] [Indexed: 08/10/2023] Open
Abstract
Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax, supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities.
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Affiliation(s)
- Tomas Hessler
- The Innovative Genomics Institute at the University of California, Berkeley, CA, USA
- The Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Robert J Huddy
- Reasearch Office, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Rohan Sachdeva
- The Innovative Genomics Institute at the University of California, Berkeley, CA, USA
- The Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
| | - Shufei Lei
- The Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
| | - Susan T L Harrison
- The Center for Bioprocess Engineering Research, University of Cape Town, Cape Town, South Africa
- The Future Water Institute, University of Cape Town, Cape Town, South Africa
- Department of Chemical Engineering, University of Cape Town, Cape Town, South Africa
| | - Spencer Diamond
- The Innovative Genomics Institute at the University of California, Berkeley, CA, USA
- The Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
| | - Jillian F Banfield
- The Innovative Genomics Institute at the University of California, Berkeley, CA, USA.
- The Department of Earth and Planetary Science, University of California, Berkeley, CA, USA.
- The Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA.
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16
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Lan F, Saba J, Qian Y, Ross T, Landick R, Venturelli OS. Single-cell analysis of multiple invertible promoters reveals differential inversion rates as a strong determinant of bacterial population heterogeneity. SCIENCE ADVANCES 2023; 9:eadg5476. [PMID: 37540747 PMCID: PMC10403206 DOI: 10.1126/sciadv.adg5476] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 07/05/2023] [Indexed: 08/06/2023]
Abstract
Population heterogeneity can promote bacterial fitness in response to unpredictable environmental conditions. A major mechanism of phenotypic variability in the human gut symbiont Bacteroides spp. involves the inversion of promoters that drive the expression of capsular polysaccharides, which determine the architecture of the cell surface. High-throughput single-cell sequencing reveals substantial population heterogeneity generated through combinatorial promoter inversion regulated by a broadly conserved serine recombinase. Exploiting control over population diversification, we show that populations with different initial compositions converge to a similar composition over time. Combining our data with stochastic computational modeling, we demonstrate that the differential rates of promoter inversion are a major mechanism shaping population dynamics. More broadly, our approach could be used to interrogate single-cell combinatorial phase variable states of diverse microbes including bacterial pathogens.
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Affiliation(s)
- Freeman Lan
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Jason Saba
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Bacteriology, University of Wisconsin-Madison, WI 53726, USA
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Yili Qian
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Tyler Ross
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Robert Landick
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Bacteriology, University of Wisconsin-Madison, WI 53726, USA
| | - Ophelia S. Venturelli
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Bacteriology, University of Wisconsin-Madison, WI 53726, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison 53706, WI, USA
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17
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Martin AJ, Serebrinsky-Duek K, Riquelme E, Saa PA, Garrido D. Microbial interactions and the homeostasis of the gut microbiome: the role of Bifidobacterium. MICROBIOME RESEARCH REPORTS 2023; 2:17. [PMID: 38046822 PMCID: PMC10688804 DOI: 10.20517/mrr.2023.10] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/17/2023] [Accepted: 04/24/2023] [Indexed: 12/05/2023]
Abstract
The human gut is home to trillions of microorganisms that influence several aspects of our health. This dense microbial community targets almost all dietary polysaccharides and releases multiple metabolites, some of which have physiological effects on the host. A healthy equilibrium between members of the gut microbiota, its microbial diversity, and their metabolites is required for intestinal health, promoting regulatory or anti-inflammatory immune responses. In contrast, the loss of this equilibrium due to antibiotics, low fiber intake, or other conditions results in alterations in gut microbiota composition, a term known as gut dysbiosis. This dysbiosis can be characterized by a reduction in health-associated microorganisms, such as butyrate-producing bacteria, enrichment of a small number of opportunistic pathogens, or a reduction in microbial diversity. Bifidobacterium species are key species in the gut microbiome, serving as primary degraders and contributing to a balanced gut environment in various ways. Colonization resistance is a fundamental property of gut microbiota for the prevention and control of infections. This community competes strongly with foreign microorganisms, such as gastrointestinal pathogens, antibiotic-resistant bacteria, or even probiotics. Resistance to colonization is based on microbial interactions such as metabolic cross-feeding, competition for nutrients, or antimicrobial-based inhibition. These interactions are mediated by metabolites and metabolic pathways, representing the inner workings of the gut microbiota, and play a protective role through colonization resistance. This review presents a rationale for how microbial interactions provide resistance to colonization and gut dysbiosis, highlighting the protective role of Bifidobacterium species.
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Affiliation(s)
- Alberto J.M. Martin
- Laboratorio de Redes Biológicas, Centro Científico y Tecnológico de Excelencia Ciencia & Vida, Fundación Ciencia & Vida, Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago 8580702, Chile
| | - Kineret Serebrinsky-Duek
- Department of Chemical and Bioprocess Engineering, Pontificia Universidad Católica de Chile, Santiago 833115, Chile
| | - Erick Riquelme
- Department of Respiratory Diseases, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Pedro A. Saa
- Department of Chemical and Bioprocess Engineering, Pontificia Universidad Católica de Chile, Santiago 833115, Chile
- Institute for Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Daniel Garrido
- Department of Chemical and Bioprocess Engineering, Pontificia Universidad Católica de Chile, Santiago 833115, Chile
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18
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Oliveira RA, Pamer EG. Assembling symbiotic bacterial species into live therapeutic consortia that reconstitute microbiome functions. Cell Host Microbe 2023; 31:472-484. [PMID: 37054670 DOI: 10.1016/j.chom.2023.03.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
Increasing experimental evidence suggests that administering live commensal bacterial species can optimize microbiome composition and lead to reduced disease severity and enhanced health. Our understanding of the intestinal microbiome and its functions has increased over the past two decades largely due to deep sequence analyses of fecal nucleic acids, metabolomic and proteomic assays to measure nutrient use and metabolite production, and extensive studies on the metabolism and ecological interactions of a wide range of commensal bacterial species inhabiting the intestine. Herein, we review new and important findings that have emerged from this work and provide thoughts and considerations on approaches to re-establish and optimize microbiome functions by assembling and administering commensal bacterial consortia.
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Affiliation(s)
- Rita A Oliveira
- Duchossois Family Institute, University of Chicago, Chicago, IL, USA; Department of Medicine, Section of Infectious Diseases & Global Health, University of Chicago Medicine, Chicago, IL, USA.
| | - Eric G Pamer
- Duchossois Family Institute, University of Chicago, Chicago, IL, USA; Department of Medicine, Section of Infectious Diseases & Global Health, University of Chicago Medicine, Chicago, IL, USA; Department of Microbiology, University of Chicago Medicine, Chicago, IL, USA; Department of Pathology, University of Chicago Medicine, Chicago, IL, USA
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19
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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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20
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Xu N, Zhang Z, Shen Y, Zhang Q, Liu Z, Yu Y, Wang Y, Lei C, Ke M, Qiu D, Lu T, Chen Y, Xiong J, Qian H. Compare the performance of multiple binary classification models in microbial high-throughput sequencing datasets. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 837:155807. [PMID: 35537509 DOI: 10.1016/j.scitotenv.2022.155807] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 06/14/2023]
Abstract
The development of machine learning and deep learning provided solutions for predicting microbiota response on environmental change based on microbial high-throughput sequencing. However, there were few studies specifically clarifying the performance and practical of two types of binary classification models to find a better algorithm for the microbiota data analysis. Here, for the first time, we evaluated the performance, accuracy and running time of the binary classification models built by three machine learning methods - random forest (RF), support vector machine (SVM), logistic regression (LR), and one deep learning method - back propagation neural network (BPNN). The built models were based on the microbiota datasets that removed low-quality variables and solved the class imbalance problem. Additionally, we optimized the models by tuning. Our study demonstrated that dataset pre-processing was a necessary process for model construction. Among these 4 binary classification models, BPNN and RF were the most suitable methods for constructing microbiota binary classification models. Using these 4 models to predict multiple microbial datasets, BPNN showed the highest accuracy and the most robust performance, while the RF method was ranked second. We also constructed the optimal models by adjusting the epochs of BPNN and the n_estimators of RF for six times. The evaluation related to performances of models provided a road map for the application of artificial intelligence to assess microbial ecology.
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Affiliation(s)
- Nuohan Xu
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Zhenyan Zhang
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Yechao Shen
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Qi Zhang
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Zhen Liu
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, PR China
| | - Yitian Yu
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Yan Wang
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Chaotang Lei
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Mingjing Ke
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Danyan Qiu
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Tao Lu
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China
| | - Yiling Chen
- Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Juntao Xiong
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, PR China
| | - Haifeng Qian
- College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, PR China.
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21
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Ecological dynamics of the gut microbiome in response to dietary fiber. THE ISME JOURNAL 2022; 16:2040-2055. [PMID: 35597888 PMCID: PMC9296629 DOI: 10.1038/s41396-022-01253-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 05/05/2022] [Accepted: 05/11/2022] [Indexed: 12/19/2022]
Abstract
Dietary fibers are generally thought to benefit intestinal health. Their impacts on the composition and metabolic function of the gut microbiome, however, vary greatly across individuals. Previous research showed that each individual's response to fibers depends on their baseline gut microbiome, but the ecology driving microbiota remodeling during fiber intake remained unclear. Here, we studied the long-term dynamics of the gut microbiome and short-chain fatty acids (SCFAs) in isogenic mice with distinct microbiota baselines fed with the fermentable fiber inulin and resistant starch compared to the non-fermentable fiber cellulose. We found that inulin produced a generally rapid response followed by gradual stabilization to new equilibria, and those dynamics were baseline-dependent. We parameterized an ecology model from the time-series data, which revealed a group of bacteria whose growth significantly increased in response to inulin and whose baseline abundance and interspecies competition explained the baseline dependence of microbiome density and community composition dynamics. Fecal levels of SCFAs, such as propionate, were associated with the abundance of inulin responders, yet inter-individual variation of gut microbiome impeded the prediction of SCFAs by machine learning models. We showed that our methods and major findings were generalizable to dietary resistant starch. Finally, we analyzed time-series data of synthetic and natural human gut microbiome in response to dietary fiber and validated the inferred interspecies interactions in vitro. This study emphasizes the importance of ecological modeling to understand microbiome responses to dietary changes and the need for personalized interventions.
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22
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Liu Y, Xu P. Quantitative and analytical tools to analyze the spatiotemporal population dynamics of microbial consortia. Curr Opin Biotechnol 2022; 76:102754. [PMID: 35809433 DOI: 10.1016/j.copbio.2022.102754] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/30/2022] [Accepted: 06/06/2022] [Indexed: 12/27/2022]
Abstract
Microorganisms occupy almost every niche on earth. They play critical roles in maintaining ecological balance, atmospheric C/N cycle, and human health. Microbes live in consortia with metabolite exchange or signal communication. Quantitative and analytical tools are becoming increasingly important to study microbial consortia dynamics. We argue that a combined reductionist and holistic approach will be important to understanding the assembly rules and spatiotemporal population dynamics of the microbial community (MICOM). Reductionism allows us to reconstruct complex MICOM from isolated or simple synthetic consortia. Holism allows us to understand microbes as a community with cooperation and competition. Here we review the recent development of quantitative and analytical tools to uncover the underlying principles in microbial communities that govern their spatiotemporal change and interaction dynamics. Mathematical models and analytical tools will continue to provide essential knowledge and expand our capability to manipulate and control microbial consortia.
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Affiliation(s)
- Yugeng Liu
- Department of Chemical Engineering, Guangdong Technion-Israel Institute of Technology, Shantou, Guangdong 515063, China
| | - Peng Xu
- Department of Chemical Engineering, Guangdong Technion-Israel Institute of Technology, Shantou, Guangdong 515063, China; Guangdong Provincial Key Laboratory of Materials and Technologies for Energy Conversion, Guangdong Technion-Israel Institute of Technology, Shantou, Guangdong 515063, China.
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23
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A Study and Modeling of Bifidobacterium and Bacillus Coculture Continuous Fermentation under Distal Intestine Simulated Conditions. Microorganisms 2022; 10:microorganisms10050929. [PMID: 35630373 PMCID: PMC9147766 DOI: 10.3390/microorganisms10050929] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/21/2022] [Accepted: 04/25/2022] [Indexed: 12/10/2022] Open
Abstract
The diversity and the stability of the microbial community are associated with microecological interactions between its members. Antagonism is one type of interaction, which particularly determines the benefits that probiotics bring to host health by suppressing opportunistic pathogens and microbial contaminants in food. Mathematical models allow for quantitatively predicting intrapopulation relationships. The aim of this study was to create predictive models for bacterial contamination outcomes depending on the probiotic antagonism and prebiotic concentration. This should allow an improvement in the screening of synbiotic composition for preventing gut microbial infections. The functional model (fermentation) was based on a three-stage continuous system, and the distal colon section (N2, pH 6.8, flow rate 0.04 h–1) was simulated. The strains Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 were chosen as the model probiotic and pathogen. Oligofructose Orafti P95 (OF) was used as the prebiotic at concentrations of 2, 5, 7, 10, 12, and 15 g/L of the medium. In the first stage, the system was inoculated with Bifidobacterium, and a dynamic equilibrium (Bifidobacterium count, lactic, and acetic acids) was achieved. Then, the system was contaminated with a 3-day Bacillus suspension (spores). The microbial count, as well as the concentration of acids and residual carbohydrates, was measured. A Bacillus monoculture was studied as a control. The stationary count of Bacillus in monoculture was markedly higher. An increase (up to 8 h) in the lag phase was observed for higher prebiotic concentrations. The specific growth rate in the exponential phase varied at different OF concentrations. Thus, the OF concentration influenced two key events of bacterial infection, which together determine when the maximal pathogen count will be reached. The mathematical models were developed, and their accuracies were acceptable for Bifidobacterium (relative errors ranging from 1.00% to 2.58%) and Bacillus (relative errors ranging from 0.74% to 2.78%) count prediction.
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24
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Jenior ML, Papin JA. Computational approaches to understanding Clostridioides difficile metabolism and virulence. Curr Opin Microbiol 2022; 65:108-115. [PMID: 34839237 PMCID: PMC8792252 DOI: 10.1016/j.mib.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/06/2021] [Accepted: 11/08/2021] [Indexed: 02/03/2023]
Abstract
The progress of infection by Clostridioides difficile is strongly influenced by metabolic cues it encounters as it colonizes the gastrointestinal tract. Both colonization and regulation of virulence have a multi-factorial interaction between host, microbiome, and gene expression cascades. While these connections with metabolism have been understood for some time, many mechanisms of control have remained difficult to directly assay due to high metabolic variability among C. difficile isolates and difficult genetic systems. Computational systems offer a means to interrogate structure of complex or noisy datasets and generate useful, tractable hypotheses to be tested in the laboratory. Recently, in silico techniques have provided powerful insights into metabolic elements of C. difficile infection ranging from virulence regulation to interactions with the gut microbiota. In this review, we introduce and provide context to the methods of computational modeling that have been applied to C. difficile metabolism and virulence thus far. The techniques discussed here have laid the foundation for future multi-scale efforts aimed at understanding the complex interplay of metabolic activity between pathogen, host, and surrounding microbial community in the regulation of C. difficile pathogenesis.
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Affiliation(s)
- Matthew L Jenior
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA,denotes co-corresponding author
| | - Jason A Papin
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA, Department of Medicine, Division of Infectious Diseases & International Health, University of Virginia, Charlottesville, VA, USA, Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, VA, USA,denotes co-corresponding author
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Saa P, Urrutia A, Silva-Andrade C, Martín AJ, Garrido D. Modeling approaches for probing cross-feeding interactions in the human gut microbiome. Comput Struct Biotechnol J 2021; 20:79-89. [PMID: 34976313 PMCID: PMC8685919 DOI: 10.1016/j.csbj.2021.12.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/03/2021] [Accepted: 12/04/2021] [Indexed: 12/16/2022] Open
Abstract
Microbial communities perform emergent activities that are essentially different from those carried by their individual members. The gut microbiome and its metabolites have a significant impact on the host, contributing to homeostasis or disease. Food molecules shape this community, being fermented through cross-feeding interactions of metabolites such as lactate, acetate, and amino acids, or products derived from macromolecule degradation. Mathematical and experimental approaches have been applied to understand and predict the interactions between microorganisms in complex communities such as the gut microbiota. Rational and mechanistic understanding of microbial interactions is essential to exploit their metabolic activities and identify keystone taxa and metabolites. The latter could be used in turn to modulate or replicate the metabolic behavior of the community in different contexts. This review aims to highlight recent experimental and modeling approaches for studying cross-feeding interactions within the gut microbiome. We focus on short-chain fatty acid production and fiber fermentation, which are fundamental processes in human health and disease. Special attention is paid to modeling approaches, particularly kinetic and genome-scale stoichiometric models of metabolism, to integrate experimental data under different diet and health conditions. Finally, we discuss limitations and challenges for the broad application of these modeling approaches and their experimental verification for improving our understanding of the mechanisms of microbial interactions.
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Affiliation(s)
- Pedro Saa
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna, 4860 Santiago, Chile
| | - Arles Urrutia
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Silva-Andrade
- Laboratorio de Biología de Redes, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, Chile
| | - Alberto J. Martín
- Laboratorio de Biología de Redes, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, Chile
| | - Daniel Garrido
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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Ji B, Herrgård MJ, Nielsen J. Microbial community dynamics revisited. NATURE COMPUTATIONAL SCIENCE 2021; 1:640-641. [PMID: 38217193 DOI: 10.1038/s43588-021-00144-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Affiliation(s)
- Boyang Ji
- BioInnovation Institute, Copenhagen, Denmark.
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