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      Fungal Fight Club: phylogeny and growth rate predict competitive outcomes among ectomycorrhizal fungi

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          Abstract

          Ectomycorrhizal fungi are among the most prevalent fungal partners of plants and can constitute up to one-third of forest microbial biomass. As mutualistic partners that supply nutrients, water, and pathogen defense, these fungi impact host plant health and biogeochemical cycling. Ectomycorrhizal fungi are also extremely diverse, and the community of fungal partners on a single plant host can consist of dozens of individuals. However, the factors that govern competition and coexistence within these communities are still poorly understood. In this study, we used in vitro competitive assays between five ectomycorrhizal fungal strains to examine how competition and pH affect fungal growth. We also tested the ability of evolutionary history to predict the outcomes of fungal competition. We found that the effects of pH and competition on fungal performance varied extensively, with changes in growth media pH sometimes reversing competitive outcomes. Furthermore, when comparing the use of phylogenetic distance and growth rate in predicting competitive outcomes, we found that both methods worked equally well. Our study further highlights the complexity of ectomycorrhizal fungal competition and the importance of considering phylogenetic distance, ecologically relevant traits, and environmental conditions in predicting the outcomes of these interactions.

          Abstract

          While interactions between ectomycorrhizal fungi are complex, considering ecologically relevant traits, phylogenetic relatedness, and environmental conditions all together may provide insight into competitive outcomes.

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          Most cited references91

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          lmerTest Package: Tests in Linear Mixed Effects Models

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            MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

            K Katoh (2002)
            A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Contributors
                Journal
                FEMS Microbiol Ecol
                FEMS Microbiol Ecol
                femsec
                FEMS Microbiology Ecology
                Oxford University Press
                0168-6496
                1574-6941
                October 2023
                11 September 2023
                11 September 2023
                : 99
                : 10
                : fiad108
                Affiliations
                Department of Integrative Biology, University of Colorado , Denver Auraria Campus Science Building 1150 12th St, Denver CO 80204, USA
                Department of Plant Biology, University of California , Davis, 605 Hutchison Dr Green Hall rm 1002 Davis CA 95616-5720, USA
                Department of Ecology, Evolution and Marine Biology, University of California , Santa Barbara CA 93106-9620, USA
                Author notes
                Corresponding author. Department of Integrative Biology, University of Colorado, Denver, 1150 12th St, Denver, CO 80204, USA. E-mail: alex.2.smith@ 123456ucdenver.edu

                Co-senior authors.

                Author information
                https://orcid.org/0000-0002-3890-000X
                https://orcid.org/0000-0001-6121-2224
                https://orcid.org/0000-0002-9335-0039
                Article
                fiad108
                10.1093/femsec/fiad108
                10516346
                37697652
                106c1407-bced-40c7-813a-37710a83217e
                © The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 August 2023
                : 01 September 2023
                : 07 September 2023
                : 20 September 2023
                Page count
                Pages: 11
                Funding
                Funded by: NSF Postdoctoral Fellowship in Biology;
                Award ID: DBI-2011020
                Funded by: NSF IOS-PBI;
                Award ID: 2029168
                Categories
                Research Article
                AcademicSubjects/SCI01150

                Microbiology & Virology
                co-culture experiment,competitive hierarchy,facilitation,mixed effects modeling,niche partitioning,ph tolerance

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