Microbial community structure analysis in Acer palmatum bark and isolation of novel bacteria IAD-21 of the candidate division FBP

Background The potential of unidentified microorganisms for academic and other applications is limitless. Plants have diverse microbial communities associated with their biomes. However, few studies have focused on the microbial community structure relevant to tree bark. Methods In this report, the microbial community structure of bark from the broad-leaved tree Acer palmatum was analyzed. Both a culture-independent approach using polymerase chain reaction (PCR) amplification and next generation sequencing, and bacterial isolation and sequence-based identification methods were used to explore the bark sample as a source of previously uncultured microorganisms. Molecular phylogenetic analyses based on PCR-amplified 16S rDNA sequences were performed. Results At the phylum level, Proteobacteria and Bacteroidetes were relatively abundant in the A. palmatum bark. In addition, microorganisms from the phyla Acidobacteria, Gemmatimonadetes, Verrucomicrobia, Armatimonadetes, and candidate division FBP, which contain many uncultured microbial species, existed in the A. palmatum bark. Of the 30 genera present at relatively high abundance in the bark, some genera belonging to the phyla mentioned were detected. A total of 70 isolates could be isolated and cultured using the low-nutrient agar media DR2A and PE03. Strains belonging to the phylum Actinobacteria were isolated most frequently. In addition, the newly identified bacterial strain IAP-33, presumed to belong to Acidobacteria, was isolated on PE03 medium. Of the isolated bacteria, 44 strains demonstrated less than 97% 16S rDNA sequence-similarity with type strains. Molecular phylogenetic analysis of IAD-21 showed the lowest similarity (79%), and analyses suggested it belongs to candidate division FBP. Culture of the strain IAD-21 was deposited in Japan Collection of Microorganisms (JCM) and Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) as JCM 32665 and DSM 108248, respectively. Discussion Our results suggest that a variety of uncultured microorganisms exist in A. palmatum bark. Microorganisms acquirable from the bark may prove valuable for academic pursuits, such as studying microbial ecology, and the bark might be a promising source of uncultured bacterial isolates.

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Relationships between Microbial Community Structure and Hydrochemistry in a Landfill Leachate-Polluted Aquifer

Applied and Environmental Microbiology ◽

10.1128/aem.67.10.4619-4629.2001 ◽

2001 ◽

Vol 67 (10) ◽

pp. 4619-4629 ◽

Cited By ~ 202

Author(s):

Wilfred F. M. Röling ◽

Boris M. van Breukelen ◽

Martin Braster ◽

Bin Lin ◽

Henk W. van Verseveld

Keyword(s):

Community Structure ◽

Microbial Community ◽

Microbial Communities ◽

16S Rdna ◽

Microbial Community Structure ◽

Landfill Leachate ◽

Denaturing Gradient Gel Electrophoresis ◽

Numerical Comparison ◽

Gram Positive ◽

Gram Positive Bacteria

ABSTRACT Knowledge about the relationship between microbial community structure and hydrogeochemistry (e.g., pollution, redox and degradation processes) in landfill leachate-polluted aquifers is required to develop tools for predicting and monitoring natural attenuation. In this study analyses of pollutant and redox chemistry were conducted in parallel with culture-independent profiling of microbial communities present in a well-defined aquifer (Banisveld, The Netherlands). Degradation of organic contaminants occurred under iron-reducing conditions in the plume of pollution, while upstream of the landfill and above the plume denitrification was the dominant redox process. Beneath the plume iron reduction occurred. Numerical comparison of 16S ribosomal DNA (rDNA)-based denaturing gradient gel electrophoresis (DGGE) profiles of Bacteria andArchaea in 29 groundwater samples revealed a clear difference between the microbial community structures inside and outside the contaminant plume. A similar relationship was not evident in sediment samples. DGGE data were supported by sequencing cloned 16S rDNA. Upstream of the landfill members of the β subclass of the class Proteobacteria(β-proteobacteria) dominated. This group was not encountered beneath the landfill, where gram-positive bacteria dominated. Further downstream the contribution of gram-positive bacteria to the clone library decreased, while the contribution of δ-proteobacteria strongly increased and β-proteobacteria reappeared. The β-proteobacteria (Acidovorax,Rhodoferax) differed considerably from those found upstream (Gallionella, Azoarcus). Direct comparisons of cloned 16S rDNA with bands in DGGE profiles revealed that the data from each analysis were comparable. A relationship was observed between the dominant redox processes and the bacteria identified. In the iron-reducing plume members of the familyGeobacteraceae made a strong contribution to the microbial communities. Because the only known aromatic hydrocarbon-degrading, iron-reducing bacteria areGeobacter spp., their occurrence in landfill leachate-contaminated aquifers deserves more detailed consideration.

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High-throughput sequencing revealed differences of microbial community structure and diversity between healthy and diseased Caulerpa lentillifera

BMC Microbiology ◽

10.1186/s12866-019-1605-5 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Zhourui Liang ◽

Fuli Liu ◽

Wenjun Wang ◽

Pengyan Zhang ◽

Xiutao Sun ◽

...

Keyword(s):

Information Processing ◽

Community Structure ◽

Microbial Community ◽

16S Rdna ◽

High Throughput ◽

Microbial Community Structure ◽

18S Rdna ◽

High Throughput Sequencing ◽

Rdna Sequencing ◽

Caulerpa Lentillifera

Abstract Background Caulerpa lentillifera is one of the most important economic green macroalgae in the world. Increasing demand for consumption has led to the commercial cultivation of C. lentillifera in Japan and Vietnam in recent decades. Concomitant with the increase of C. lentillifera cultivation is a rise in disease. We hypothesise that epiphytes or other microorganisms outbreak at the C. lentillifera farm may be an important factor contributing to disease in C. lentillifera. The main aims are obtaining differences in the microbial community structure and diversity between healthy and diseased C. lentillifera and key epiphytes and other microorganisms affecting the differences through the results of high-throughput sequencing and bioinformatics analysis in the present study. Results A total of 14,050, 2479, and 941 operational taxonomic units (OTUs) were obtained from all samples using 16S rDNA, 18S rDNA, and internal transcribed spacer (ITS) high-throughput sequencing, respectively. 16S rDNA sequencing and 18S rDNA sequencing showed that microbial community diversity was higher in diseased C. lentillifera than in healthy C. lentillifera. Both PCoA results and UPGMA results indicated that the healthy and diseased algae samples have characteristically different microbial communities. The predominant prokaryotic phyla were Proteobacteria, Planctomycetes, Bacteroidetes, Cyanobacteria, Acidobacteria, Acidobacteria and Parcubacteria in all sequences. Chlorophyta was the most abundant eukaryotic phylum followed by Bacillariophyta based on 18S rDNA sequencing. Ascomycota was the dominant fungal phylum detected in healthy C. lentillifera based on ITS sequencing, whereas fungi was rare in diseased C. lentillifera, suggesting that Ascomycota was probably fungal endosymbiont in healthy C. lentillifera. There was a significantly higher abundance of Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis in diseased C. lentillifera than in healthy C. lentillifera. Disease outbreaks significantly change carbohydrate metabolism, environmental information processing and genetic information processing of prokaryotic communities in C. lentillifera through predicted functional analyses using the Tax4Fun tool. Conclusions Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis outbreak at the C. lentillifera farm sites was an important factor contributing to disease in C. lentillifera.

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Characterization of depth-related microbial community structure in lake sediment by denaturing gradient gel electrophoresis of amplified 16S rDNA and reversely transcribed 16S rRNA fragments

FEMS Microbiology Ecology ◽

10.1016/s0168-6496(03)00212-5 ◽

2003 ◽

Vol 46 (2) ◽

pp. 147-157 ◽

Cited By ~ 58

Author(s):

Yoshikazu Koizumi ◽

Hisaya Kojima ◽

Manabu Fukui

Keyword(s):

Community Structure ◽

Microbial Community ◽

16S Rrna ◽

16S Rdna ◽

Lake Sediment ◽

Microbial Community Structure ◽

Gel Electrophoresis ◽

Denaturing Gradient Gel Electrophoresis ◽

Gradient Gel Electrophoresis

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Investigation of Fecal Microbial Community Structure Using 16s rDNA Sequence in Pigs Fed Fermented Liquid Feed

Nihon Yoton Gakkaishi ◽

10.5938/youton.44.40 ◽

2007 ◽

Vol 44 (2) ◽

pp. 40-50

Author(s):

Koji KAKUGAWA ◽

Satoru IJIRI ◽

Kimitaka NAKANO ◽

Shinya YAMAUCHI ◽

Yoshinobu TSUCHIYA

Keyword(s):

Community Structure ◽

Microbial Community ◽

16S Rdna ◽

Microbial Community Structure ◽

Rdna Sequence ◽

16S Rdna Sequence ◽

Liquid Feed

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Microbial Community Composition of Mine Wastes in Cornwall and West Devon (UK)

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.262.290 ◽

2017 ◽

Vol 262 ◽

pp. 290-293

Author(s):

Tomasa Sbaffi ◽

Angus Buckling ◽

Christopher G. Bryan

Keyword(s):

Community Structure ◽

Microbial Community ◽

Microbial Community Structure ◽

Microbial Community Composition ◽

Geochemical Data ◽

Mine Wastes ◽

Candidate Division ◽

And Control ◽

Controls Cluster ◽

Total Diversity

Mine wastes and control soils from twelve sites around Cornwall and West Devon (UK) were analysed for microbial community structure, pH and readily extractible metals (an indication of mobility). About 70% of total diversity observed was constituted by six phyla (Acidobacteria, Chloroflexi, Planctomycetes, Proteobacteria, Verrucomicrobia, and candidate division AD3). Microbial community structure revealed patterns of distribution that mostly differed between waste samples and controls. Cluster analysis of the geochemical data (pH and readily extractible metals) indicated the presence of four groups; two groups of controls and two of samples defined by similar features. pH appeared to correlate with the portion of shared community.

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Microbial Community Structure Across a Wastewater-Impacted Riparian Buffer Zone in the Southeastern Coastal Plain

The Open Microbiology Journal ◽

10.2174/1874285801307010099 ◽

2013 ◽

Vol 7 (1) ◽

pp. 99-117 ◽

Cited By ~ 4

Author(s):

T.F. Ducey ◽

P.R. Johnson ◽

A.D. Shriner ◽

T.A. Matheny ◽

P.G. Hunt

Keyword(s):

Community Structure ◽

Microbial Community ◽

16S Rdna ◽

Microbial Community Structure ◽

Buffer Zone ◽

Riparian Buffer ◽

Microbial Populations ◽

Buffer Zones ◽

Riparian Buffer Zones ◽

Riparian Buffer Zone

Riparian buffer zones are important for both natural and developed ecosystems throughout the world because of their ability to retain nutrients, prevent soil erosion, protect aquatic environments from excessive sedimentation, and filter pollutants. Despite their importance, the microbial community structures of riparian buffer zones remains poorly defined. Our objectives for this study were twofold: first, to characterize the microbial populations found in riparian buffer zone soils; and second, to determine if microbial community structure could be linked to denitrification enzyme activity (DEA). To achieve these objectives, we investigated the microbial populations of a riparian buffer zone located downslope of a pasture irrigated with swine lagoon effluent, utilizing DNA sequencing of the 16S rDNA, DEA, and quantitative PCR (qPCR) of the denitrification genes nirK, nirS, and nosZ. Clone libraries of the 16S rDNA gene were generated from each of twelve sites across the riparian buffer with a total of 986 partial sequences grouped into 654 operational taxonomic units (OTUs). The Proteobacteria were the dominant group (49.8% of all OTUs), with the Acidobacteria also well represented (19.57% of all OTUs). Analysis of qPCR results identified spatial relationships between soil series, site location, and gene abundance, which could be used to infer both incomplete and total DEA rates.

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