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      Analysis of spatio-temporal fungal growth dynamics under different environmental conditions

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          Abstract

          Traditionally, fungal growth dynamics were assessed manually, limiting the research to a few environmental conditions and/or fungal species. Fortunately, more automated ways of measurement are gaining momentum due to the availability of cheap imaging and processing equipment and the development of dedicated image analysis algorithms. In this paper, we use image analysis to assess the impact of environmental conditions on the growth dynamics of two economically important fungal species, Coniophora puteana and Rhizoctonia solani. Sixteen environmental conditions combining four temperatures (15, 20, 25 and 30 °C) and four relative humidity (RH) conditions (65, 70, 75 and 80% RH) were tested. Fungal growth characteristics were extracted from images of the growing fungi, taken at regular points in time. Advanced time series analysis was applied to quantitatively compare the effect of the environmental conditions on these growth characteristics. The evolution of the mycelial area and the number of tips over time resulted in typical sigmoidal growth curves. Other growth characteristics such as the mean hyphal segment length did not vary significantly over time. Temperature and RH usually had a combined effect on the growth dynamics of the mycelial area and the number of tips. When defining optimal growth conditions for a fungus, it is therefore of primordial importance that the effect of temperature and RH is assessed simultaneously. At the most extreme conditions we tested, the mycelium most probably experienced water stress when developing over the inert Petri dish surface. An RH of 65% (independent of temperature) for C. puteana and a temperature of 30 °C (independent of RH) for both C. puteana and R. solani therefore always resulted in limited fungal growth, while the optimal growing conditions were at 20 °C and 75% RH and at 25 °C and 80% RH for R. solani and at 20 °C and 75% RH for C. puteana. The method applied in this study offers an updated and broader alternative to classical and narrowly focused studies on fungal growth dynamics, and is well suited to efficiently assess the effect of environmental conditions on fungal growth.

          Electronic supplementary material

          The online version of this article (10.1186/s43008-019-0009-3) contains supplementary material, which is available to authorized users.

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          Most cited references61

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          How does a hypha grow? The biophysics of pressurized growth in fungi.

          The mechanisms underlying the growth of fungal hyphae are rooted in the physical property of cell pressure. Internal hydrostatic pressure (turgor) is one of the major forces driving the localized expansion at the hyphal tip which causes the characteristic filamentous shape of the hypha. Calcium gradients regulate tip growth, and secretory vesicles that contribute to this process are actively transported to the growing tip by molecular motors that move along cytoskeletal structures. Turgor is controlled by an osmotic mitogen-activated protein kinase cascade that causes de novo synthesis of osmolytes and uptake of ions from the external medium. However, as discussed in this Review, turgor and pressure have additional roles in hyphal growth, such as causing the mass flow of cytoplasm from the basal mycelial network towards the expanding hyphal tips at the colony edge.
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              Analysis of growth characteristics of filamentous fungi in different nutrient media.

              A microbroth kinetic model based on turbidity measurements was developed in order to analyze the growth characteristics of three species of filamentous fungi (Rhizopus microsporus, Aspergillus fumigatus, and Scedosporium prolificans) characterized by different growth rates in five nutrient media (antibiotic medium 3, yeast nitrogen base medium, Sabouraud broth, RPMI 1640 alone, and RPMI 1640 with 2% glucose). In general, five distinct phases in the growth of filamentous fungi could be distinguished, namely, the lag phase, the first transition period, the log phase, the second transition period, and the stationary phase. The growth curves were smooth and were characterized by the presence of long transition periods. Among the different growth phases distinguished, the smallest variability in growth rates among the strains of each species was found during the log phase in all nutrient media. The different growth phases of filamentous fungi were barely distinguishable in RPMI 1640, in which the poorest growth was observed for all fungi even when the medium was supplemented with 2% glucose. R. microsporus and A. fumigatus grew better in Sabouraud and yeast nitrogen base medium than in RPMI 1640, with growth rates three to four times higher. None of the media provided optimal growth of S. prolificans. The germination of Rhizopus spores and Aspergillus and Scedosporium conidia commenced after 2 and 5 h of incubation, respectively. The elongation rates ranged from 39.6 to 26.7, 25.4 to 20.2, and 16.9 to 9.9 microm/h for Rhizopus, Aspergillus, and Scedoporium hyphae, respectively. The germination of conidia and spores and the elongation rates of hyphae were enhanced in antibiotic medium 3 and delayed in yeast nitrogen base medium. In conclusion, the growth curves provide a useful tool to gain insight into the growth characteristics of filamentous fungi in different nutrient media and may help to optimize the methodology for antifungal susceptibility testing.
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                Author and article information

                Contributors
                Liselotte.DeLigne@UGent.be
                gvidal@gate.sinica.edu.tw
                Jan.Baetens@UGent.be
                Jan.VandenBulcke@UGent.be
                Joris.VanAcker@UGent.be
                Bernard.DeBaets@UGent.be
                Journal
                IMA Fungus
                IMA Fungus
                IMA Fungus
                BioMed Central (London )
                2210-6340
                2210-6359
                21 June 2019
                21 June 2019
                2019
                : 10
                : 7
                Affiliations
                [1 ]ISNI 0000 0001 2069 7798, GRID grid.5342.0, KERMIT, Department of Data Analysis and Mathematical Modelling, , Ghent University, ; Coupure links 653, 9000 Ghent, Belgium
                [2 ]ISNI 0000 0001 2069 7798, GRID grid.5342.0, UGent-Woodlab - Laboratory of Wood Technology, Department of Environment, , Ghent University, ; Coupure links 653, 9000 Ghent, Belgium
                Author information
                http://orcid.org/0000-0002-2202-4228
                Article
                9
                10.1186/s43008-019-0009-3
                7325663
                32647616
                37cf7dc0-84f5-4cdf-9dfd-e276d5a09822
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 4 May 2019
                : 9 May 2019
                Funding
                Funded by: Research Foundation Flanders FWO
                Award ID: FWO SB grant 1S53417N
                Award ID: FWO project 3G.0838.12.N
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Plant science & Botany
                time series analysis,temperature,relative humidity,fungal networks,coniophora puteana,rhizoctonia solani

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