Flow sensing in mycelial fungi

Oh, Ki‐Bong; Nishiyama, T.; Sakai, Eiko; Matsuoka, Hiroaki; Kurata, Hiroshi

doi:10.1016/s0168-1656(97)00147-8

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…with poly-L-lysine, to which yeast cells and hyphae adhered throughout the experiment (19). Yeast cells (5 ϫ 10 5 cells) were inoculated and allowed to form hyphae at 37°C under a constant flow rate (400 l͞min) or without flow.…”

Section: Methodsmentioning

confidence: 99%

Purification and characterization of an autoregulatory substance capable of regulating the morphological transition in Candida albicans

Miyazawa

Naito

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

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146

141

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The yeast Candida albicans has a distinguishing feature, dimorphism, which is the ability to switch between two morphological forms: a budding yeast form and a multicellular invasive filamentous form. This ability has been postulated to contribute to the virulence of this organism. Studies on the morphological transition from a filamentous to a budding yeast form in C. albicans have shown that this organism excretes an autoregulatory substance into the culture medium. This substance was extracted and purified by normal-phase and reversed-phase HPLC. The autoregulatory substance was structurally identified as 3,7,11-trimethyl-2,6,10-dodecatrienoate (farnesoic acid) by NMR and mass spectrometry. Growth experiments suggest that this substance does not inhibit yeast cell growth but inhibits filamentous growth. These findings have implications for developmental signaling by the fungus and might have medicinal value in the development of antifungal therapies.

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Section: Methodsmentioning

confidence: 99%

Purification and characterization of an autoregulatory substance capable of regulating the morphological transition in Candida albicans

Miyazawa

Naito

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

146

141

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“…Fungi sense light, chemicals, gases, gravity and electric fields. Fungi show a pronounced response to changes in a substrate pH [110], demonstrate mechanosensing [111]; they sense toxic metals [112], CO 2 [113] and direction of fluid flow [114]. Fungi exhibit thigmotactic and thigmomorphogenetic responses, which might be reflected in dynamic patterns of their electrical activity [115].…”

Section: Application Domainsmentioning

confidence: 99%

Towards fungal computer

Adamatzky¹

2018

Interface Focus.

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We propose that fungi Basidiomycetes can be used as computing devices: information is represented by spikes of electrical activity, a computation is implemented in a mycelium network and an interface is realized via fruit bodies. In a series of scoping experiments, we demonstrate that electrical activity recorded on fruits might act as a reliable indicator of the fungi’s response to thermal and chemical stimulation. A stimulation of a fruit is reflected in changes of electrical activity of other fruits of a cluster, i.e. there is distant information transfer between fungal fruit bodies. In an automaton model of a fungal computer, we show how to implement computation with fungi and demonstrate that a structure of logical functions computed is determined by mycelium geometry.

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“…Using the process of dichotomous and lateral branching [5], hyphae create the mycelial network, in which the older branches eventually collides with existing braches and annihilated by the process of anastomosis [6]. The nutrients are internalized by the hyphae [7][8][9][10] and are sent through the mycelial network to the area of high nutrient demand, using a process called translocation [8,11,12].As hyphae propagate, they leave behind a stationary biomass [13]that consists of older cells, which are structurally stable and promote further growth of the hyphae. Earlier studies with mycotoxin producers suggest that mycotoxin production promoteshyphal growth and vice-versa.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Quantification Driven Predictive Multi-Scale Model for Synthesis of Mycotoxins

Banerjee¹,

Terejanu

Chanda

2014

CBB

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Abstract:Many toxic molds synthesize and release an array of poisons, termed mycotoxins that have an enormous impact on human health, agriculture and economy [1]. These molds contaminate our buildings, indoor air and crops, cause life threatening human and animal diseases and reduce agricultural output [2]. In order to design appropriate approaches to minimize the detrimental effects of these fungi, it is essential to develop diagnostic methodologies that can rapidly and accurately determine based on fungal strains and their growth patterns, the extent of mycotoxin mediated damage caused to the environment.Here we developed a novel multi-scale predictive mathematical model that could reliably estimate aflatoxin synthesis from growth features extracted from Aspergillusparasiticus, a well-characterized model for studying mycotoxin biosynthesis. We conducted acoustic imaging experiments to observe and extract the growth features from the biomass profiles of the growing Aspergillus colony growing on an aflatoxin-inducing solid growth medium. We employed the probability-based representation of uncertainty and used Bayes' theorem to infer the uncertain parameters in our mathematical model using biomass observations of the colony at 24h (aflatoxin is not synthesized yet at this time-point) and 48 hours (aflatoxin synthesis occurs at peak levels). We demonstrate that our model could successfully predict with quantified uncertainties the levels of aflatoxin secreted to the environment by the fungus.

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Flow sensing in mycelial fungi

Cited by 9 publications

References 27 publications

Purification and characterization of an autoregulatory substance capable of regulating the morphological transition in Candida albicans

Purification and characterization of an autoregulatory substance capable of regulating the morphological transition in Candida albicans

Towards fungal computer

Uncertainty Quantification Driven Predictive Multi-Scale Model for Synthesis of Mycotoxins

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