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Calvert J, McTaggart A, Carvalhais LC, Rensink S, Dennis PG, Drenth A, Shivas R. Divergent rainforest tree microbiomes between phases of the monsoon cycle, host plants and tissues. PLANT BIOLOGY (STUTTGART, GERMANY) 2023; 25:860-870. [PMID: 37647418 DOI: 10.1111/plb.13569] [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: 01/09/2023] [Accepted: 07/26/2023] [Indexed: 09/01/2023]
Abstract
The Australian Monsoon Tropics (AMT) contain some of the most biodiverse forests on the continent. Little is known about the dynamics of rainforest plant microbiomes in general, and there have been no community-level studies on Australian rainforest endophytes, their seasonality, tissue and host specificity. We tested whether community composition of tropical tree endophytes (fungi and bacteria) differs: (i) at different points during a monsoon cycle, (ii) between leaf and stem tissues, (iii) between forest microclimates (gully/ridge), and between (iv) host plant species, and (v) host plant clade, using amplicon sequencing of the bacterial 16S and fungal ITS2 gene regions. Results indicated that the composition of rainforest plant microbiomes differs between wet and dry seasons, which may be explained by physiological shifts in host plants due to annual climate fluctuations from mesic to xeric. Endophyte microbiomes differed between leaves and stems. Distinct fungal communities were associated with host species and clades, with some trees enriched in a number of fungal taxa compared to host plants in other clades. Diversity of bacterial endophytes in plant stems increased in the dry season. We conclude that the microbiomes of tropical plants are responsive to monsoonal climate variation, are highly compartmentalised between plant tissues, and may be partly shaped by the relatedness of their host plants.
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Affiliation(s)
- J Calvert
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
| | - A McTaggart
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
| | - L C Carvalhais
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
| | - S Rensink
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
| | - P G Dennis
- School of Earth and Environmental Sciences, The University of Queensland, St Lucia, QLD, Australia
| | - A Drenth
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
| | - R Shivas
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Dutton Park, QLD, Australia
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2
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Bai X, Ren J, Sun F. MLR-OOD: A Markov Chain Based Likelihood Ratio Method for Out-Of-Distribution Detection of Genomic Sequences. J Mol Biol 2022; 434:167586. [PMID: 35427634 PMCID: PMC10433695 DOI: 10.1016/j.jmb.2022.167586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 04/05/2022] [Accepted: 04/05/2022] [Indexed: 12/23/2022]
Abstract
Machine learning or deep learning models have been widely used for taxonomic classification of metagenomic sequences and many studies reported high classification accuracy. Such models are usually trained based on sequences in several training classes in hope of accurately classifying unknown sequences into these classes. However, when deploying the classification models on real testing data sets, sequences that do not belong to any of the training classes may be present and are falsely assigned to one of the training classes with high confidence. Such sequences are referred to as out-of-distribution (OOD) sequences and are ubiquitous in metagenomic studies. To address this problem, we develop a deep generative model-based method, MLR-OOD, that measures the probability of a testing sequencing belonging to OOD by the likelihood ratio of the maximum of the in-distribution (ID) class conditional likelihoods and the Markov chain likelihood of the testing sequence measuring the sequence complexity. We compose three different microbial data sets consisting of bacterial, viral, and plasmid sequences for comprehensively benchmarking OOD detection methods. We show that MLR-OOD achieves the state-of-the-art performance demonstrating the generality of MLR-OOD to various types of microbial data sets. It is also shown that MLR-OOD is robust to the GC content, which is a major confounding effect for OOD detection of genomic sequences. In conclusion, MLR-OOD will greatly reduce false positives caused by OOD sequences in metagenomic sequence classification.
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Affiliation(s)
- Xin Bai
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Jie Ren
- Google Research, Brain Team, USA
| | - Fengzhu Sun
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.
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3
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Fields C, Levin M. Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments. ENTROPY 2022; 24:e24060819. [PMID: 35741540 PMCID: PMC9222757 DOI: 10.3390/e24060819] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/26/2022] [Accepted: 06/08/2022] [Indexed: 12/20/2022]
Abstract
One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.
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Affiliation(s)
- Chris Fields
- Allen Discovery Center at Tufts University, Science and Engineering Complex, 200 College Ave., Medford, MA 02155, USA;
| | - Michael Levin
- Allen Discovery Center at Tufts University, Science and Engineering Complex, 200 College Ave., Medford, MA 02155, USA;
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02115, USA
- Correspondence:
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4
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Fields C, Friston K, Glazebrook JF, Levin M. A free energy principle for generic quantum systems. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 173:36-59. [PMID: 35618044 DOI: 10.1016/j.pbiomolbio.2022.05.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/04/2022] [Accepted: 05/18/2022] [Indexed: 01/17/2023]
Abstract
The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on surprisal (a.k.a., self-information). This upper bound can be read as a Bayesian prediction error. Equivalently, its negative is a lower bound on Bayesian model evidence (a.k.a., marginal likelihood). In short, certain random dynamical systems evince a kind of self-evidencing. Here, we reformulate the FEP in the formal setting of spacetime-background free, scale-free quantum information theory. We show how generic quantum systems can be regarded as observers, which with the standard freedom of choice assumption become agents capable of assigning semantics to observational outcomes. We show how such agents minimize Bayesian prediction error in environments characterized by uncertainty, insufficient learning, and quantum contextuality. We show that in its quantum-theoretic formulation, the FEP is asymptotically equivalent to the Principle of Unitarity. Based on these results, we suggest that biological systems employ quantum coherence as a computational resource and - implicitly - as a communication resource. We summarize a number of problems for future research, particularly involving the resources required for classical communication and for detecting and responding to quantum context switches.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandières, 11160, Caunes Minervois, France.
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3AR, UK
| | - James F Glazebrook
- Department of Mathematics and Computer Science, Eastern Illinois University, Charleston, IL, 61920, USA; Adjunct Faculty, Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
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5
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Fields C, Glazebrook JF, Levin M. Minimal physicalism as a scale-free substrate for cognition and consciousness. Neurosci Conscious 2021; 2021:niab013. [PMID: 34345441 PMCID: PMC8327199 DOI: 10.1093/nc/niab013] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/04/2021] [Accepted: 04/05/2021] [Indexed: 12/14/2022] Open
Abstract
Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our "minimal physicalist" approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandières, 11160 Caunes Minervois, France
| | - James F Glazebrook
- Department of Mathematics and Computer Science, Eastern Illinois University, 600 Lincoln Ave, Charleston, IL 61920 USA
- Department of Mathematics, Adjunct Faculty, University of Illinois at Urbana–Champaign, 1409 W. Green Street, Urbana, IL 61801, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, 200 College Avenue, Medford, MA 02155, USA
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6
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Díaz M, Jarrín-V P, Simarro R, Castillejo P, Tenea GN, Molina CA. The Ecuadorian Microbiome Project: a plea to strengthen microbial genomic research. NEOTROPICAL BIODIVERSITY 2021. [DOI: 10.1080/23766808.2021.1938900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Magdalena Díaz
- Institute of Research on Zoonoses (CIZ), Central University of Ecuador, Quito, Ecuador
- Chemistry Engineering Faculty, Central University of Ecuador, Quito, Ecuador
| | - Pablo Jarrín-V
- Health and Environment Research Group, Universidad Regional Amazónica Ikiam, Tena, Ecuador
| | - Raquel Simarro
- Department of Biology, Geology, Physics and Inorganic Chemistry,ESCET, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain
| | - Pablo Castillejo
- Faculty of Environmental Sciences, SEK International University, Quito, Ecuador
- Applied Sciences and Engineering Faculty, Universidad De Las Américas, Quito, Ecuador
| | - Gabriela N. Tenea
- Biofood and Nutraceutics Research and Development Group, Faculty of Engineering in Agricultural and Environmental Sciences, Technical University of the North, Ibarra, Ecuador
| | - C. Alfonso Molina
- Institute of Research on Zoonoses (CIZ), Central University of Ecuador, Quito, Ecuador
- Faculty of Veterinary Medicine and Zootechnics, Central University of Ecuador, Quito, Ecuador
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7
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Metagenomic-based Approach for the Analysis of Yeast Diversity Associated with Amylase Production in Lai (Durio kutejensis). JOURNAL OF PURE AND APPLIED MICROBIOLOGY 2021. [DOI: 10.22207/jpam.15.1.02] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
This study reported the application of a next generation sequencing (NGS) analysis of yeast diversity in native Indonesian fruit, Durio kutejensis, collected from Borneo, Central Kalimantan. The analysis was designed to observe the microbial consortium associated with solid state fermentation (SSF) for amylase production. Together with the additional data from culture-dependent analysis, we observed the morphological features, molecular characteristics, and amylase concentration produced by each isolate. We performed Solid State Fermentation (SSF) for amylase production and the enzyme activity was then determined using UV-Vis spectrophotometer at 540 nm. Result obtained from metagenomic approach consist of 4 group that fungal species included in the Ascomycota identified as Botryosphaeria dothidea (1.35%), Lasiodiplodia crassispora (17.62%), Aureobasidium pullulans (55.02%), Paraphoma chrysanthemicola (11.38%), Preussia funiculate (1.90%), Sporormiella intermedia (0.82%), Myrothecium gramineum (1.35%), Fusarium oxysporum (6.24%), Fusarium proliferatum (3.25%) and Phialemoniopsis curvata (1.08%). The results of isolation using culturable medium in the form of YMA obtained 40 yeast isolates. A total of 40 representative isolates from durian fruit were screened, two positive amylase isolates based on clear zones formed were DU 4.2 (Candida sorboxylosa) and DU4.22 (Cyberlindnera fabianii) isolates with amylolytic index of DU 4.2 isolates at 0.24 and DU 4.22 at 0.72 with an incubation time of 48 h. The highest amylase enzyme activity was found in isolate DU 4.2 of 31.21 U / mL.
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Abstract
Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.
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9
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Fields C, Levin M. Scale-Free Biology: Integrating Evolutionary and Developmental Thinking. Bioessays 2020; 42:e1900228. [PMID: 32537770 DOI: 10.1002/bies.201900228] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 04/24/2020] [Indexed: 12/16/2022]
Abstract
When the history of life on earth is viewed as a history of cell division, all of life becomes a single cell lineage. The growth and differentiation of this lineage in reciprocal interaction with its environment can be viewed as a developmental process; hence the evolution of life on earth can also be seen as the development of life on earth. Here, in reviewing this field, some potentially fruitful research directions suggested by this change in perspective are highlighted. Variation and selection become, for example, bidirectional information flows between scales, while the notions of "cooperation" and "competition" become scale relative. The language of communication, inference, and information processing becomes more useful than the language of causation to describe the interactions of both homogeneous and heterogeneous living systems at any scale. Emerging scale-free theoretical frameworks such as predictive coding and active inference provide conceptual tools for reconceptualizing biology as the study of a unified, multiscale dynamical system.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandieres, 11160 Caunes Minervois, France
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
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10
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Pepin KM, Hopken MW, Shriner SA, Spackman E, Abdo Z, Parrish C, Riley S, Lloyd-Smith JO, Piaggio AJ. Improving risk assessment of the emergence of novel influenza A viruses by incorporating environmental surveillance. Philos Trans R Soc Lond B Biol Sci 2019; 374:20180346. [PMID: 31401963 PMCID: PMC6711309 DOI: 10.1098/rstb.2018.0346] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Reassortment is an evolutionary mechanism by which influenza A viruses (IAV) generate genetic novelty. Reassortment is an important driver of host jumps and is widespread according to retrospective surveillance studies. However, predicting the epidemiological risk of reassortant emergence in novel hosts from surveillance data remains challenging. IAV strains persist and co-occur in the environment, promoting co-infection during environmental transmission. These conditions offer opportunity to understand reassortant emergence in reservoir and spillover hosts. Specifically, environmental RNA could provide rich information for understanding the evolutionary ecology of segmented viruses, and transform our ability to quantify epidemiological risk to spillover hosts. However, significant challenges with recovering and interpreting genomic RNA from the environment have impeded progress towards predicting reassortant emergence from environmental surveillance data. We discuss how the fields of genomics, experimental ecology and epidemiological modelling are well positioned to address these challenges. Coupling quantitative disease models and natural transmission studies with new molecular technologies, such as deep-mutational scanning and single-virus sequencing of environmental samples, should dramatically improve our understanding of viral co-occurrence and reassortment. We define observable risk metrics for emerging molecular technologies and propose a conceptual research framework for improving accuracy and efficiency of risk prediction. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
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Affiliation(s)
- Kim M. Pepin
- National Wildlife Research Center, USDA-APHIS, Fort Collins, CO 80521, USA
- e-mail:
| | - Matthew W. Hopken
- National Wildlife Research Center, USDA-APHIS, Fort Collins, CO 80521, USA
- Colorado State University, Fort Collins, CO 80523, USA
| | - Susan A. Shriner
- National Wildlife Research Center, USDA-APHIS, Fort Collins, CO 80521, USA
| | - Erica Spackman
- Exotic and Emerging Avian Viral Diseases Research, USDA-ARS, Athens, GA 30605, USA
| | - Zaid Abdo
- Colorado State University, Fort Collins, CO 80523, USA
| | - Colin Parrish
- Baker Institute for Animal Health, Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14853, USA
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Imperial College, London, SW7 2AZ, UK
| | - James O. Lloyd-Smith
- UCLA, Los Angeles, CA 90095, USA
- Department of Ecology and Evolutionary Biology, Fogarty International Center, National Institutes of Health, Bethesda MD 20892, USA
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Fields C, Levin M. Somatic multicellularity as a satisficing solution to the prediction-error minimization problem. Commun Integr Biol 2019; 12:119-132. [PMID: 31413788 PMCID: PMC6682261 DOI: 10.1080/19420889.2019.1643666] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 07/04/2019] [Accepted: 07/07/2019] [Indexed: 11/26/2022] Open
Abstract
Adaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves - highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.
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Affiliation(s)
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA USA
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12
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Sergaki C, Lagunas B, Lidbury I, Gifford ML, Schäfer P. Challenges and Approaches in Microbiome Research: From Fundamental to Applied. FRONTIERS IN PLANT SCIENCE 2018; 9:1205. [PMID: 30174681 PMCID: PMC6107787 DOI: 10.3389/fpls.2018.01205] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 07/26/2018] [Indexed: 05/07/2023]
Abstract
We face major agricultural challenges that remain a threat for global food security. Soil microbes harbor enormous potentials to provide sustainable and economically favorable solutions that could introduce novel approaches to improve agricultural practices and, hence, crop productivity. In this review we give an overview regarding the current state-of-the-art of microbiome research by discussing new technologies and approaches. We also provide insights into fundamental microbiome research that aim to provide a deeper understanding of the dynamics within microbial communities, as well as their interactions with different plant hosts and the environment. We aim to connect all these approaches with potential applications and reflect how we can use microbial communities in modern agricultural systems to realize a more customized and sustainable use of valuable resources (e.g., soil).
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Affiliation(s)
- Chrysi Sergaki
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
- *Correspondence: Chrysi Sergaki,
| | - Beatriz Lagunas
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Ian Lidbury
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Miriam L. Gifford
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
- Warwick Integrative Synthetic Biology Centre, University of Warwick, Coventry, United Kingdom
| | - Patrick Schäfer
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
- Warwick Integrative Synthetic Biology Centre, University of Warwick, Coventry, United Kingdom
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13
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Fields C, Levin M. Multiscale memory and bioelectric error correction in the cytoplasm-cytoskeleton-membrane system. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2017; 10. [DOI: 10.1002/wsbm.1410] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 08/19/2017] [Accepted: 10/04/2017] [Indexed: 12/12/2022]
Affiliation(s)
- Chris Fields
- 21 Rue des Lavandiéres, 11160 Caunes Minervois; France
| | - Michael Levin
- Allen Discovery Center at Tufts University; Medford MA USA
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14
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Abstract
Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer.
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Affiliation(s)
| | - Luc Henry
- Hackuarium Association, Renens, Switzerland
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15
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Abstract
Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment, with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer.
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Affiliation(s)
| | - Luc Henry
- Hackuarium Association, Renens, Switzerland
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16
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Karkman A, Lehtimäki J, Ruokolainen L. The ecology of human microbiota: dynamics and diversity in health and disease. Ann N Y Acad Sci 2017; 1399:78-92. [DOI: 10.1111/nyas.13326] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 01/19/2017] [Accepted: 02/02/2017] [Indexed: 12/15/2022]
Affiliation(s)
- Antti Karkman
- Metapopulation Research Centre, Department of Biosciences; University of Helsinki; Helsinki Finland
| | - Jenni Lehtimäki
- Metapopulation Research Centre, Department of Biosciences; University of Helsinki; Helsinki Finland
| | - Lasse Ruokolainen
- Metapopulation Research Centre, Department of Biosciences; University of Helsinki; Helsinki Finland
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