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The core microbiome of sessile ciliate Stentor coeruleus is not shaped by the environment.

ABSTRACT: Microbiomes of multicellular organisms are one of the hottest topics in microbiology and physiology, while only few studies addressed bacterial communities associated with protists. Protists are widespread in all environments and can be colonized by plethora of different bacteria, including also human pathogens. The aim of this study was to characterize the prokaryotic community associated with the sessile ciliate Stentor coeruleus. 16S rRNA gene metabarcoding was performed on single cells of S. coeruleus and on their environment, water from the sewage stream. Our results showed that the prokaryotic community composition differed significantly between Stentor cells and their environment. The core microbiome common for all ciliate specimens analyzed could be defined, and it was composed mainly by representatives of bacterial genera which include also potential human pathogens and commensals, such as Neisseria, Streptococcus, Capnocytophaga, Porphyromonas. Numerous 16S rRNA gene contigs belonged to endosymbiont "Candidatus Megaira polyxenophila". Our data suggest that each ciliate cell can be considered as an ecological microniche harboring diverse prokaryotic organisms. Possible benefits for persistence and transmission in nature for bacteria associated with protists are discussed. Our results support the hypothesis that ciliates attract potentially pathogenic bacteria and play the role of natural reservoirs for them.

SUBMITTER: Lanzoni O

PROVIDER: S-EPMC6684585 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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The core microbiome of sessile ciliate Stentor coeruleus is not shaped by the environment.

Lanzoni Olivia O Plotnikov Andrey A Khlopko Yuri Y Munz Giulio G Petroni Giulio G Potekhin Alexey A

Scientific reports 20190806 1

Microbiomes of multicellular organisms are one of the hottest topics in microbiology and physiology, while only few studies addressed bacterial communities associated with protists. Protists are widespread in all environments and can be colonized by plethora of different bacteria, including also human pathogens. The aim of this study was to characterize the prokaryotic community associated with the sessile ciliate Stentor coeruleus. 16S rRNA gene metabarcoding was performed on single cells of S. ...[more]

PMID: 31388025

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Project description:BackgroundWound healing is one of the defining features of life and is seen not only in tissues but also within individual cells. Understanding wound response at the single-cell level is critical for determining fundamental cellular functions needed for cell repair and survival. This understanding could also enable the engineering of single-cell wound repair strategies in emerging synthetic cell research. One approach is to examine and adapt self-repair mechanisms from a living system that already demonstrates robust capacity to heal from large wounds. Towards this end, Stentor coeruleus, a single-celled free-living ciliate protozoan, is a unique model because of its robust wound healing capacity. This capacity allows one to perturb the wounding conditions and measure their effect on the repair process without immediately causing cell death, thereby providing a robust platform for probing the self-repair mechanism.ResultsHere we used a microfluidic guillotine and a fluorescence-based assay to probe the timescales of wound repair and of mechanical modes of wound response in Stentor. We found that Stentor requires ~ 100-1000 s to close bisection wounds, depending on the severity of the wound. This corresponds to a healing rate of ~ 8-80 μm2/s, faster than most other single cells reported in the literature. Further, we characterized three distinct mechanical modes of wound response in Stentor: contraction, cytoplasm retrieval, and twisting/pulling. Using chemical perturbations, active cilia were found to be important for only the twisting/pulling mode. Contraction of myonemes, a major contractile fiber in Stentor, was surprisingly not important for the contraction mode and was of low importance for the others.ConclusionsWhile events local to the wound site have been the focus of many single-cell wound repair studies, our results suggest that large-scale mechanical behaviors may be of greater importance to single-cell wound repair than previously thought. The work here advances our understanding of the wound response in Stentor and will lay the foundation for further investigations into the underlying components and molecular mechanisms involved.

Project description:There is still a significant gap between our understanding of neural circuits and the behaviours they compute-i.e. the computations performed by these neural networks (Carandini 2012 Nat. Neurosci. 15, 507-509. (doi:10.1038/nn.3043)). Cellular decision-making processes, learning, behaviour and memory formation-all that have been only associated with animals with neural systems-have also been observed in many unicellular aneural organisms, namely Physarum, Paramecium and Stentor (Tang & Marshall2018 Curr. Biol. 28, R1180-R1184. (doi:10.1016/j.cub.2018.09.015)). As these are fully functioning organisms, yet being unicellular, there is a much better chance to elucidate the detailed mechanisms underlying these learning processes in these organisms without the complications of highly interconnected neural circuits. An intriguing learning behaviour observed in Stentor roeseli (Jennings 1902 Am. J. Physiol. Legacy Content 8, 23-60. (doi:10.1152/ajplegacy.1902.8.1.23)) when stimulated with carmine has left scientists puzzled for more than a century. So far, none of the existing learning paradigm can fully encapsulate this particular series of five characteristic avoidance reactions. Although we were able to observe all responses described in the literature and in a previous study (Dexter et al. 2019), they do not conform to any particular learning model. We then investigated whether models inferred from machine learning approaches, including decision tree, random forest and feed-forward artificial neural networks could infer and predict the behaviour of S. roeseli. Our results showed that an artificial neural network with multiple 'computational' neurons is inefficient at modelling the single-celled ciliate's avoidance reactions. This has highlighted the complexity of behaviours in aneural organisms. Additionally, this report will also discuss the significance of elucidating molecular details underlying learning and decision-making processes in these unicellular organisms, which could offer valuable insights that are applicable to higher animals.

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The core microbiome of sessile ciliate Stentor coeruleus is not shaped by the environment.

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The core microbiome of sessile ciliate Stentor coeruleus is not shaped by the environment.

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