Journal of Microbiology

Hana Yi

4 Articles

Fungal Community Associated with Genetically Modified Poplar During Metal Phytoremediation: Moonsuk Hur , Young Woon Lim , Jae Jeong Yu , Se Uk Cheon , Young Im Choi , Seok-Hwan Yoon , Sang-Cheol Park , Dong-Il Kim , Hana Yi; J. Microbiol. 2012;50(6):910-915. Published online December 30, 2012; DOI: https://doi.org/10.1007/s12275-012-2491-9

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Due to the increasing demand for phytoremediation, many transgenic poplars have been developed to enhance the bioremediation of heavy metals. However, structural changes to indigenous fungal communities by genetically modified organisms (GMO) presents a major ecological issue, due to the important role of fungi for plant growth in natural environments. To evaluate the effect of GM plant use on environmental fungal soil communities, extensive sequencing-based community analysis was conducted, while controlling the influence of plant clonality, plant age, soil condition, and harvesting season. The rhizosphere soils of GM and wild type (WT) poplars at a range of growth stages were sampled together with unplanted, contaminated soil, and the fungal community structures were investigated by pyrosequencing the D1/D2 region of the 28S rRNA gene. The results show that the overall structure of the rhizosphere fungal community was not significantly influenced by GM poplars. However, the presence of GM specific taxa, and faster rate of community change during poplar growth, appeared to be characteristic of the GM plant-induced effects on soil-born fungal communities. The results of this study provide additional information about the potential effects of GM poplar trees aged 1.5–3 years, on the soil fungal community.

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Distinct Communities of Poplar Endophytes on an Unpolluted and a Risk Element-Polluted Site and Their Plant Growth-Promoting Potential In Vitro
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A novel nitrous oxide mitigation strategy: expressing nitrous oxide reductase fromPseudomonas stutzeriin transgenic plants
Shen Wan, Trevor Greenham, Kagami Goto, Yaseen Mottiar, Amanda M. Johnson, Julianne M. Staebler, Mohsin A. Zaidi, Qingyao Shu, Illimar Altosaar
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Identifying airborne fungi in Seoul, Korea using metagenomics
Seung-Yoon Oh, Jonathan J. Fong, Myung Soo Park, Limseok Chang, Young Woon Lim
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Tracking Fungal Community Responses to Maize Plants by DNA- and RNA-Based Pyrosequencing
Eiko E. Kuramae, Erik Verbruggen, Remy Hillekens, Mattias de Hollander, Wilfred F. M. Röling, Marcel G. A. van der Heijden, George A. Kowalchuk, Mari Moora
PLoS ONE.2013; 8(7): e69973. CrossRef

TBC: A Clustering Algorithm Based on Prokaryotic Taxonomy: Jae-Hak Lee , Hana Yi , Yoon-Seong Jeon , Sungho Won , Jongsik Chun; J. Microbiol. 2012;50(2):181-185. Published online April 27, 2012; DOI: https://doi.org/10.1007/s12275-012-1214-6

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Abstract PDF

High-throughput DNA sequencing technologies have revolutionized the study of microbial ecology. Massive sequencing of PCR amplicons of the 16S rRNA gene has been widely used to understand the microbial community structure of a variety of environmental samples. The resulting sequencing reads are clustered into operational taxonomic units that are then used to calculate various statistical indices that represent the degree of species diversity in a given sample. Several algorithms have been developed to perform this task, but they tend to produce different outcomes. Herein, we propose a novel sequence clustering algorithm, namely Taxonomy-Based Clustering (TBC). This algorithm incorporates the basic concept of prokaryotic taxonomy in which only comparisons to the type strain are made and used to form species while omitting full-scale multiple sequence alignment. The clustering quality of the proposed method was compared with those of MOTHUR, BLASTClust, ESPRITTree, CD-HIT, and UCLUST. A comprehensive comparison using three different experimental datasets produced by pyrosequencing demonstrated that the clustering obtained using TBC is comparable to those obtained using MOTHUR and ESPRIT-Tree and is computationally efficient. The program was written in JAVA and is available from http://sw. ezbiocloud.net/tbc.

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Effects of Disease Resistant Genetically Modified Rice on Soil Microbial Community Structure According to Growth Stage
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hc-OTU: A Fast and Accurate Method for Clustering Operational Taxonomic Units Based on Homopolymer Compaction
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Metagenomic Insights into the Bioaerosols in the Indoor and Outdoor Environments of Childcare Facilities
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Bacterial community of sediments from the Australian-Antarctic ridge
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Endophytic bacterial diversity of an Antarctic moss, Sanionia uncinata
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Analytical Tools and Databases for Metagenomics in the Next-Generation Sequencing Era
Mincheol Kim, Ki-Hyun Lee, Seok-Whan Yoon, Bong-Soo Kim, Jongsik Chun, Hana Yi
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Eun Soo Noh, Young-Sam Kim, Dong-Hyun Kim, Kyoung-Ho Kim
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Bacterial diversity in ornithogenic soils compared to mineral soils on King George Island, Antarctica
Ok-Sun Kim, Namyi Chae, Hyun Soo Lim, Ahnna Cho, Jeong Hoon Kim, Soon Gyu Hong, Jeongsu Oh
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rRNASelector: A Computer Program for Selecting Ribosomal RNA Encoding Sequences from Metagenomic and Metatranscriptomic Shotgun Libraries: Jae-Hak Lee , Hana Yi , Jongsik Chun; J. Microbiol. 2011;49(4):689-691. Published online September 2, 2011; DOI: https://doi.org/10.1007/s12275-011-1213-z

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Abstract PDF

Metagenomic and metatranscriptomic shotgun sequencing techniques are gaining popularity as more cost-effective next-generation sequencing technologies become commercially available. The initial stage of bioinformatic analysis generally involves the identification of phylogenetic markers such as ribosomal RNA genes. The sequencing reads that do not code for rRNA can then be used for protein-based analysis. Hidden Markov model is a well-known method for pattern recognition. Hidden Markov models that are trained on well-curated rRNA sequence databases have been successfully used to identify DNA sequence coding for rRNAs in prokaryotes. Here, we introduce rRNASelector, which is a computer program for selecting rRNA genes from massive metagenomic and metatranscriptomic sequences using hidden Markov models. The program successfully identified prokaryotic 5S, 26S, and 23S rRNA genes from Roche 454 FLX Titanium-based metagenomic and metatranscriptomic libraries. The rRNASelector program is available at http://sw.ezbiocloud.net/rrnaselector.

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Genome sequencing of Clostridium butyricum DKU-01, isolated from infant feces
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Genome sequence of type strain of Staphylococcus aureus subsp. aureus
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Thalassobius aestuarii sp. nov., Isolated from Tidal Flat Sediment: Hana Yi , Jongsik Chun; J. Microbiol. 2006;44(2):171-176.; DOI: https://doi.org/2368 [pii]

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Abstract PDF: A strictly aerobic, non-motile, ovoid-shaped Alphaproteobacteria, designated strain JC2049T,was isolated from a tidal flat sediment sample. The results of 16S rRNA gene sequence analysis indicated that this isolate belonged to the genus Thalassobius, with a sequence similarity of 96.9-97.3% to other valid Thalassobius spp. The cells required 1-7% NaCl for growth (optimum 2%) and accumulated poly-β-hydroxybutyrate. Nitrite was reduced to nitrogen, but nitrate was not reduced to nitrite. No genetic potential for aerobic anoxygenic photosynthesis was detected. The primary isoprenoid quinone (Ubiquinone-10), predominant cellular fatty acids (C18:1ω7c, 11 methyl C18:1ω7c and C16:0) and DNA G+C content (61 mol%) were all consistent with the assignment of this isolate to the genus Thalassobius. Several phenotypic characteristics clearly distinguished our isolate from other Thalassobius species. The degree of genomic relatedness between strain JC2049T and other Thalassobius species was in a range of 20-43%. The polyphasic data presented in this study indicates that our isolate should be classified as a novel species within the genus Thalassobius. The name Thalassobius aestuarii sp. nov. is therefore proposed for this isolate; the type strain is JC2049T (= IMSNU 14011T = KCTC 12049T = DSM 15283T).

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