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      Isolation and Biochemical Characterization of Six Anaerobic Fungal Strains from Zoo Animal Feces

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      Microorganisms
      MDPI AG

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          Abstract

          Anaerobic fungi are prime candidates for the conversion of agricultural waste products to biofuels. Despite the increasing interest in these organisms, their growth requirements and metabolism remain largely unknown. The isolation of five strains of anaerobic fungi and their identification as Neocallimastix cameroonii, Caecomyces spec., Orpinomyces joyonii, Pecoramyces ruminantium, and Khoyollomyces ramosus, is described. The phylogeny supports the reassignment of Neocallimastix californiae and Neocallimastix lanati to Neocallimastix cameroonii and points towards the redesignation of Cyllamyces as a species of Caecomyces. All isolated strains including strain A252, which was described previously as Aestipascuomyces dubliciliberans, were further grown on different carbon sources and the produced metabolites were analyzed; hydrogen, acetate, formate, lactate, and succinate were the main products. Orpinomyces joyonii was lacking succinate production and Khoyollomyces ramosus was not able to produce lactate under the studied conditions. The results further suggested a sequential production of metabolites with a preference for hydrogen, acetate, and formate. By comparing fungal growth on monosaccharides or on the straw, a higher hydrogen production was noticed on the latter. Possible reactions to elevated sugar concentrations by anaerobic fungi are discussed.

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          ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

          Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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            IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

            Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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              UFBoot2: Improving the Ultrafast Bootstrap Approximation

              Abstract The standard bootstrap (SBS), despite being computationally intensive, is widely used in maximum likelihood phylogenetic analyses. We recently proposed the ultrafast bootstrap approximation (UFBoot) to reduce computing time while achieving more unbiased branch supports than SBS under mild model violations. UFBoot has been steadily adopted as an efficient alternative to SBS and other bootstrap approaches. Here, we present UFBoot2, which substantially accelerates UFBoot and reduces the risk of overestimating branch supports due to polytomies or severe model violations. Additionally, UFBoot2 provides suitable bootstrap resampling strategies for phylogenomic data. UFBoot2 is 778 times (median) faster than SBS and 8.4 times (median) faster than RAxML rapid bootstrap on tested data sets. UFBoot2 is implemented in the IQ-TREE software package version 1.6 and freely available at http://www.iqtree.org.
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                Author and article information

                Contributors
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                Journal
                MICRKN
                Microorganisms
                Microorganisms
                MDPI AG
                2076-2607
                August 2021
                August 03 2021
                : 9
                : 8
                : 1655
                Article
                10.3390/microorganisms9081655
                34442734
                fa4aa1e0-8a5f-49f9-b9b4-045a370ee7a7
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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