Deep learning predicts microbial interactions from self-organized spatiotemporal patterns

Computational and Structural Biotechnology Journal, Год журнала: 2020, Номер 18, С. 1259 - 1269

Опубликована: Янв. 1, 2020

Graphical abstractAbstractMicrobial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of predicting microbial interactions currently lacking. Here we propose supervised deep learning as a new tool network inference. An agent-based model was used to simulate spatiotemporal evolution two interacting organisms under diverse growth and interaction scenarios, data which subsequently train neural networks. For small-size domains (100 µm × 100 µm) over coefficients assumed be invariant, obtained fairly accurate predictions, indicated average R2 value 0.84. In application relatively larger (450 450 where varying in space, models correctly predicted distributions without any additional training. Lastly, evaluated our against real biological using Pseudomonas fluorescens Escherichia coli co-cultures treated with polymeric chitin or N-acetylglucosamine, hydrolysis product chitin. While P. can utilize both substrates growth, E. lacked ability degrade Consistent expectations, context-dependent across substrates, i.e., degrader-cheater relationship on polymers competition monomers. The combined machine algorithm successfully demonstrates how infer from spatially distributed data, presenting itself useful analysis more complex

Язык: Английский

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An invisible workforce in soil: The neglected role of soil biofilms in conjugative transfer of antibiotic resistance genes

Critical Reviews in Environmental Science and Technology, Год журнала: 2021, Номер 52(15), С. 2720 - 2748

Опубликована: Март 5, 2021

Soil, a potential reservoir of antibiotic resistance genes (ARGs), is inhabited by numerous microorganisms. Many microorganisms in soil are embedded within self-produced matrix extracellular polymeric substances to form supracellular structures, i.e., biofilms. Representing the predominant microbial lifestyle soil, biofilms considered hot spots horizontal gene transfer. Herein, we discuss distribution, transfer, and fate ARGs environment at macro- micro-scales. Applications microfluidic platforms, with an advantage mimicking complex environments permitting study behaviors micro-scale, coupled high-throughput sequencing other innovative transfer also discussed. This review aims highlight neglected role spread expand current limited knowledge about microenvironment.

Язык: Английский

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Whole-Cell Microbial Bioreporter for Soil Contaminants Detection

Frontiers in Bioengineering and Biotechnology, Год журнала: 2021, Номер 9

Опубликована: Фев. 23, 2021

Anthropogenic activities have released various contaminants into soil that pose a serious threat to the ecosystem and human well-being. Compared conventional analytical methodologies, microbial cell-based bioreporters are offering flexible, rapid, cost-effective strategy assess environmental risks. This review aims summarize recent progress in application of contamination detection provide insight challenges current strategies. The biosensing principles genetic circuit engineering introduced. Developments detect quantify heavy metal organic reviewed. Moreover, future opportunities whole-cell for monitoring discussed.

Язык: Английский

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Soil-root interface influences the assembly of the endophytic bacterial community in rice plants

Biology and Fertility of Soils, Год журнала: 2021, Номер 58(1), С. 35 - 48

Опубликована: Ноя. 25, 2021

Язык: Английский

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Biotic Interactions in Soil are Underestimated Drivers of Microbial Carbon Use Efficiency

Current Microbiology, Год журнала: 2022, Номер 80(1)

Опубликована: Дек. 2, 2022

Abstract Microbial carbon use efficiency (CUE)—the balance between microbial growth and respiration—strongly impacts mediated soil storage is sensitive to many well-studied abiotic environmental factors. However, surprisingly, little work has examined how biotic interactions in may impact CUE. Here, we review the theoretical empirical lines of evidence exploring affect CUE through lens life history strategies. Fundamentally, a population constrained by density carrying capacity, which, when reached, causes species grow more quickly less efficiently. When microbes engage interspecific competition, they accelerate rates acquire limited resources release secondary chemicals toxic competitors. Such processes are not anabolic thus constrain In turn, antagonists activate one number stress responses that also do involve biomass production, potentially further reducing contrast, facilitation can increase expanding realized niches, mitigating production costs extracellular enzymes. at higher trophic levels influence For instance, predation on positively or negatively changing outcomes competition. Finally, discuss plants select for efficient under different contexts. short, this demonstrates potential be strong regulator additionally provides blueprint future research address key knowledge gaps ecological applied importance sequestration.

Язык: Английский

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