Wan-Taek Im

Bio: Wan-Taek Im is an academic researcher from Hankyong National University. The author has contributed to research in topics: Ginsenoside & Sphingomonas. The author has an hindex of 37, co-authored 216 publications receiving 4851 citations. Previous affiliations of Wan-Taek Im include Kyung Hee University & KAIST.

Sphingopyxis granuli sp. nov., a beta-glucosidase-producing bacterium in the family Sphingomonadaceae in alpha-4 subclass of the Proteobacteria.

Abstract: Strain Kw07T, a Gram-negative, non-spore-forming, rod-shaped bacterium, was isolated from granules in an Up-flow Anaerobic Sludge Blanket (UASB) bioreactor used in the treatment of brewery wastewater. 16S rRNA gene sequence analysis revealed that strain Kw07T belongs to the alpha-4 subclass of the Proteobacteria, and the highest degree of sequence similarity was determined to be to Sphingopyxis macrogoltabida IFO 15033T(97.8%). Chemotaxonomic data revealed that strain Kw07T possesses a quinone system with the predominant compound Q-10, the predominant fatty acid C18:1 omega7c, and sphingolipids, all of which corroborated our assignment of the strain to the Sphingopyxis genus. The results of DNA-DNA hybridization and physiological and biochemical tests clearly demonstrated that strain Kw07T represents a distinct species. Based on these data, Kw07T (=KCTC 12209T=NBRC 100800T) should be classified as the type strain for a novel Sphingopyxis species, for which the name Sphingopyxis granuli sp. nov. has been proposed.

Two Ginseng UDP-Glycosyltransferases Synthesize Ginsenoside Rg3 and Rd

Abstract: Ginseng is a medicinal herb that requires cultivation under shade conditions, typically for 4–6 years, before harvesting. The principal components of ginseng are ginsenosides, glycosylated tetracyclic terpenes. Dammarene-type ginsenosides are classified into two groups, protopanaxadiol (PPD) and protopanaxatriol (PPT), based on their hydroxylation patterns, and further diverge to diverse ginsenosides through differential glycosylation. Three early enzymes, dammarenediol-II synthase (DS) and two P450 enzymes, protopanaxadiol synthase (PPDS) and protopanaxatriol synthase (PPTS), have been reported, but glycosyltransferases that are necessary to synthesize specific ginsenosides have not yet been fully identified. To discover glycosyltransferases responsible for ginsenoside biosynthesis, we sequenced and assembled the ginseng transcriptome de novo and characterized two UDP-glycosyltransferases (PgUGTs): PgUGT74AE2 and PgUGT94Q2. PgUGT74AE2 transfers a glucose moiety from UDP-glucose (UDP-Glc) to the C3 hydroxyl groups of PPD and compound K to form Rh ₂ and F2, respectively, whereas PgUGT94Q2 transfers a glucose moiety from UDP-Glc to Rh ₂ and F2 to form Rg ₃ and Rd, respectively. Introduction of the two UGT genes into yeast together with PgDS and PgPPDS resulted in the de novo production of Rg ₃. Our results indicate that these two UGTs are key enzymes for the synthesis of ginsenosides and provide a method for producing specific ginsenosides through yeast fermentation.

Odorous swine wastewater treatment by purple non-sulfur bacteria, Rhodopseudomonas palustris, isolated from eutrophicated ponds

Abstract: Three strains of phototrophic, purple, non-sulfur bacteria, isolated from eutrophic ponds, were used to treat odorous swine wastewater. One isolate, Rhodopseudomonas palustris, when cultured in swine wastewater without supplementation for 7 d, removed odorous organic acids (170 mg l(-1)), COD (10,000 mg l(-1)) and phosphate (180 mg l(-1)).

The Ribosomal Database Project: improved alignments and new tools for rRNA analysis

Abstract: The Ribosomal Database Project (RDP) provides researchers with quality-controlled bacterial and archaeal small subunit rRNA alignments and analysis tools. An improved alignment strategy uses the Infernal secondary structure aware aligner to provide a more consistent higher quality alignment and faster processing of user sequences. Substantial new analysis features include a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data. This pipeline offers a collection of tools that automate the data processing and simplify the computationally intensive analysis of large sequencing libraries. In addition, a new Taxomatic visualization tool allows rapid visualization of taxonomic inconsistencies and suggests corrections, and a new class Assignment Generator provides instructors with a lesson plan and individualized teaching materials. Details about RDP data and analytical functions can be found at http://rdp.cme.msu.edu/.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Structure, variation, and assembly of the root-associated microbiomes of rice.

Abstract: Plants depend upon beneficial interactions between roots and microbes for nutrient availability, growth promotion, and disease suppression. High-throughput sequencing approaches have provided recent insights into root microbiomes, but our current understanding is still limited relative to animal microbiomes. Here we present a detailed characterization of the root-associated microbiomes of the crop plant rice by deep sequencing, using plants grown under controlled conditions as well as field cultivation at multiple sites. The spatial resolution of the study distinguished three root-associated compartments, the endosphere (root interior), rhizoplane (root surface), and rhizosphere (soil close to the root surface), each of which was found to harbor a distinct microbiome. Under controlled greenhouse conditions, microbiome composition varied with soil source and genotype. In field conditions, geographical location and cultivation practice, namely organic vs. conventional, were factors contributing to microbiome variation. Rice cultivation is a major source of global methane emissions, and methanogenic archaea could be detected in all spatial compartments of field-grown rice. The depth and scale of this study were used to build coabundance networks that revealed potential microbial consortia, some of which were involved in methane cycling. Dynamic changes observed during microbiome acquisition, as well as steady-state compositions of spatial compartments, support a multistep model for root microbiome assembly from soil wherein the rhizoplane plays a selective gating role. Similarities in the distribution of phyla in the root microbiomes of rice and other plants suggest that conclusions derived from this study might be generally applicable to land plants.

A taxonomic note on the genus Lactobacillus: Description of 23 novel genera, emended description of the genus Lactobacillus Beijerinck 1901, and union of Lactobacillaceae and Leuconostocaceae.

Abstract: The genus Lactobacillus comprises 261 species (at March 2020) that are extremely diverse at phenotypic, ecological and genotypic levels. This study evaluated the taxonomy of Lactobacillaceae and Leuconostocaceae on the basis of whole genome sequences. Parameters that were evaluated included core genome phylogeny, (conserved) pairwise average amino acid identity, clade-specific signature genes, physiological criteria and the ecology of the organisms. Based on this polyphasic approach, we propose reclassification of the genus Lactobacillus into 25 genera including the emended genus Lactobacillus, which includes host-adapted organisms that have been referred to as the Lactobacillus delbrueckii group, Paralactobacillus and 23 novel genera for which the names Holzapfelia, Amylolactobacillus, Bombilactobacillus, Companilactobacillus, Lapidilactobacillus, Agrilactobacillus, Schleiferilactobacillus, Loigolactobacilus, Lacticaseibacillus, Latilactobacillus, Dellaglioa, Liquorilactobacillus, Ligilactobacillus, Lactiplantibacillus, Furfurilactobacillus, Paucilactobacillus, Limosilactobacillus, Fructilactobacillus, Acetilactobacillus, Apilactobacillus, Levilactobacillus, Secundilactobacillus and Lentilactobacillus are proposed. We also propose to emend the description of the family Lactobacillaceae to include all genera that were previously included in families Lactobacillaceae and Leuconostocaceae. The generic term 'lactobacilli' will remain useful to designate all organisms that were classified as Lactobacillaceae until 2020. This reclassification reflects the phylogenetic position of the micro-organisms, and groups lactobacilli into robust clades with shared ecological and metabolic properties, as exemplified for the emended genus Lactobacillus encompassing species adapted to vertebrates (such as Lactobacillus delbrueckii, Lactobacillus iners, Lactobacillus crispatus, Lactobacillus jensensii, Lactobacillus johnsonii and Lactobacillus acidophilus) or invertebrates (such as Lactobacillus apis and Lactobacillus bombicola).