Using automated reasoning to explore the metabolism of unconventional organisms: a first step to explore host–microbial interactions

Systems modelled in the context of molecular and cellular biology are difficult to represent with a single calibrated numerical model. Flux optimisation hypotheses have shown tremendous promise to accurately predict bacterial metabolism but they require a precise understanding of metabolic reactions occurring in the considered species. Unfortunately, this information may not be available for more complex organisms or non-cultured microorganisms such as those evidenced in microbiomes with metagenomic techniques. In both cases, flux optimisation techniques may not be applicable to elucidate systems functioning. In this context, we describe how automatic reasoning allows relevant features of an unconventional biological system to be identified despite a lack of data. A particular focus is put on the use of Answer Set Programming, a logic programming paradigm with combinatorial optimisation functionalities. We describe its usage to over-approximate metabolic responses of biological systems and solve gap-filling problems. In this review, we compare steady-states and Boolean abstractions of metabolic models and illustrate their complementarity via applications to the metabolic analysis of macro-algae. Ongoing applications of this formalism explore the emerging field of systems ecology, notably elucidating interactions between a consortium of microbes and a host organism. As the first step in this field, we will illustrate how the reduction in microbiotas according to expected metabolic phenotypes can be addressed with gap-filling problems.

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Need for Laboratory Ecosystems To Unravel the Structures and Functions of Soil Microbial Communities Mediated by Chemistry

mBio ◽

10.1128/mbio.01175-18 ◽

2018 ◽

Vol 9 (4) ◽

Cited By ~ 13

Author(s):

Kateryna Zhalnina ◽

Karsten Zengler ◽

Dianne Newman ◽

Trent R. Northen

Keyword(s):

Microbial Communities ◽

Metabolic Networks ◽

Soil Microbial Communities ◽

Microbial Interactions ◽

Microbial Consortia ◽

Cellular Biology ◽

Model Organisms ◽

Soil Microbial ◽

Integrative Framework ◽

Genome Annotations

ABSTRACTThe chemistry underpinning microbial interactions provides an integrative framework for linking the activities of individual microbes, microbial communities, plants, and their environments. Currently, we know very little about the functions of genes and metabolites within these communities because genome annotations and functions are derived from the minority of microbes that have been propagated in the laboratory. Yet the diversity, complexity, inaccessibility, and irreproducibility of native microbial consortia limit our ability to interpret chemical signaling and map metabolic networks. In this perspective, we contend that standardized laboratory ecosystems are needed to dissect the chemistry of soil microbiomes. We argue that dissemination and application of standardized laboratory ecosystems will be transformative for the field, much like how model organisms have played critical roles in advancing biochemistry and molecular and cellular biology. Community consensus on fabricated ecosystems (“EcoFABs”) along with protocols and data standards will integrate efforts and enable rapid improvements in our understanding of the biochemical ecology of microbial communities.

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Logical methods for computational intelligence

The Knowledge Engineering Review ◽

10.1017/s0269888997003056 ◽

1997 ◽

Vol 12 (4) ◽

pp. 407-409

Author(s):

GRIGORIS ANTONIOU ◽

NEIL V. MURRAY

Keyword(s):

Computational Intelligence ◽

Automated Reasoning ◽

Special Session ◽

Computational Logic ◽

Joint Conference ◽

The Past ◽

Precise Understanding ◽

Symbolic Approach ◽

Information Sciences

Over the past years, two main approaches to computational intelligence have emerged: the symbolic and the non-symbolic approach. The perhaps most prominent methods of the symbolic approach are based on logic. Logical methods exhibit a series of desirable properties:[bull ] Transparent representation of meaning[bull ] Precise understanding of the meaning of statements (semantics).[bull ] Sound reasoning methods.[bull ] Explanation capabilities.A special session on logical methods for computational intelligence was held at the 3rd Joint Conference on Information Sciences. The field of computational logic is so broad that it is impossible to review the main developments in an article. Therefore, in the following we will restrict attention to two areas that turned out to be the focus of the special session: automated reasoning, and reasoning with incomplete and changing information.

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Individual differences, social attention, and the history of the social motivation hypotheses of autism

Behavioral and Brain Sciences ◽

10.1017/s0140525x18002509 ◽

2019 ◽

Vol 42 ◽

Author(s):

Peter C. Mundy

Keyword(s):

Individual Differences ◽

Early Development ◽

Emotional Development ◽

Social Motivation ◽

Social Attention ◽

Social Emotional Development ◽

Social Emotional ◽

Precise Understanding ◽

The Social ◽

History Of

Abstract The stereotype of people with autism as unresponsive or uninterested in other people was prominent in the 1980s. However, this view of autism has steadily given way to recognition of important individual differences in the social-emotional development of affected people and a more precise understanding of the possible role social motivation has in their early development.

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A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

Biochemical Society Transactions ◽

10.1042/bst20190172 ◽

2020 ◽

Vol 48 (2) ◽

pp. 399-409

Author(s):

Baizhen Gao ◽

Rushant Sabnis ◽

Tommaso Costantini ◽

Robert Jinkerson ◽

Qing Sun

Keyword(s):

Microbial Community ◽

Microbial Communities ◽

Environmental Remediation ◽

Real Life ◽

Design Principles ◽

Microbial Interactions ◽

Potential Applications ◽

New Gene ◽

Global Biogeochemical Cycles ◽

Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

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Artificial cells containing sustainable energy conversion engines

Emerging Topics in Life Sciences ◽

10.1042/etls20190103 ◽

2019 ◽

Vol 3 (5) ◽

pp. 573-578 ◽

Cited By ~ 3

Author(s):

Kwanwoo Shin

Keyword(s):

Energy Conversion ◽

Nicotinamide Adenine Dinucleotide ◽

Sustainable Energy ◽

Living Cells ◽

Energy Transduction ◽

Artificial Cells ◽

Energy Conversion Process ◽

Metabolic Reactions ◽

Metabolic Activities ◽

Reduced Nicotinamide Adenine Dinucleotide

Living cells naturally maintain a variety of metabolic reactions via energy conversion mechanisms that are coupled to proton transfer across cell membranes, thereby producing energy-rich compounds. Until now, researchers have been unable to maintain continuous biochemical reactions in artificially engineered cells, mainly due to the lack of mechanisms that generate energy-rich resources, such as adenosine triphosphate (ATP) and reduced nicotinamide adenine dinucleotide (NADH). If these metabolic activities in artificial cells are to be sustained, reliable energy transduction strategies must be realized. In this perspective, this article discusses the development of an artificially engineered cell containing a sustainable energy conversion process.

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