+1 Recommend
1 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Apophysomycesthailandensis (Mucorales, Mucoromycota), a new species isolated from soil in northern Thailand and its solubilization of non-soluble minerals

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.



          A new species of soil fungi, described herein as Apophysomyces thailandensis , was isolated from soil in Chiang Mai Province, Thailand. Morphologically, this species was distinguished from previously described Apophysomyces species by its narrower trapezoidal sporangiospores. A physiological determination showed that A. thailandensis differs from other Apophysomyces species by its assimilation of D-turanose, D-tagatose, D-fucose, L-fucose, and nitrite. A phylogenetic analysis, performed using combined internal transcribed spacers (ITS), the large subunit (LSU) of ribosomal DNA (rDNA) regions, and a part of the histone 3 (H3) gene, lends support to our the finding that A. thailandensis is distinct from other Apophysomyces species. The genetic distance analysis of the ITS sequence supports A. thailandensis as a new fungal species. A full description, illustrations, phylogenetic tree, and taxonomic key to the new species are provided. Its metal minerals solubilization ability is reported.

          Related collections

          Most cited references 39

          • Record: found
          • Abstract: found
          • Article: not found

          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

           Robert Edgar (2004)
          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
            • Record: found
            • Abstract: found
            • Article: not found

            MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

            We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from free of charge.
              • Record: found
              • Abstract: found
              • Article: not found

              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively.

                Author and article information

                Pensoft Publishers
                29 January 2019
                : 45
                : 75-92
                [1 ] Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand Chiang Mai University Chiang Mai Thailand
                [2 ] PhD Degree Program in Applied Microbiology, Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand University of Phayao Phayao Thailand
                [3 ] Center of Excellence in Microbial Diversity and Sustainable Utilization, Chiang Mai University, Chiang Mai 50200, Thailand Academy of Science, The Royal Society of Thailand Bangkok Thailand
                [4 ] Faculty of Agriculture and Natural Resources, University of Phayao, Phayao 56000, Thailand Chiang Mai University Chiang Mai Thailand
                [5 ] Center of Excellence for Renewable Energy, Chiang Mai University, Chiang Mai 50200, Thailand University of Phayao Phayao Thailand
                [6 ] Academy of Science, The Royal Society of Thailand, Bangkok 10300, Thailand Academy of Science, The Royal Society of Thailand Bangkok Thailand
                Author notes
                Corresponding author: Saisamorn Lumyong ( saisamorn.l@ )

                Academic editor: Maarja Öpik

                Surapong Khuna, Nakarin Suwannarach, Jaturong Kumla, Jomkhwan Meerak, Wipornpan Nuangmek, Tanongkiat Kiatsiriroat, Saisamorn Lumyong

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Research Article
                Identification Key


                Comment on this article