16s-rrna.net Metagenome Sequencing, 16s Sequencing, 18s Sequencing, and Fungi Sequencing with MRDNA

1. J Microbiol Methods. 2016 Aug;127:132-40. doi: 10.1016/j.mimet.2016.06.004. Epub

2016 Jun 6.


Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing

technologies for phylogenetic analysis of the rumen bacterial community in



Myer PR(1), Kim M(2), Freetly HC(3), Smith TP(4).


Author information:

(1)Department of Animal Science, University of Tennesse Institute of Agriculture,

University of Tennessee, Knoxville, TN 37996. Electronic address: pmyer@utk.edu.

(2)USDA-ARS, U.S. Meat Animal Research Center, Clay Center, NE 68933(1).

Electronic address: mkim2276@korea.kr. (3)USDA-ARS, U.S. Meat Animal Research

Center, Clay Center, NE 68933(1). Electronic address:

harvey.freetly@ars.usda.gov. (4)USDA-ARS, U.S. Meat Animal Research Center, Clay

Center, NE 68933(1). Electronic address: tim.smith@ars.usda.gov.


Next generation sequencing technologies have vastly changed the approach of

sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct

technologies are available for large-scale 16S sequencing. All three are subject

to biases introduced by sequencing error rates, amplification primer selection,

and read length, which can affect the apparent microbial community. In this

study, we compared short read 16S rRNA variable regions, V1-V3, with that of

near-full length 16S regions, V1-V8, using highly diverse steer rumen microbial

communities, in order to examine the impact of technology selection on

phylogenetic profiles. Short paired-end reads from the Illumina MiSeq platform

were used to generate V1-V3 sequence, while long "circular consensus" reads from

the Pacific Biosciences RSII instrument were used to generate V1-V8 data. The two

platforms revealed similar microbial operational taxonomic units (OTUs), as well

as similar species richness, Good's coverage, and Shannon diversity metrics.

However, the V1-V8 amplified ruminal community resulted in significant increases

in several orders of taxa, such as phyla Proteobacteria and Verrucomicrobia (P <

0.05). Taxonomic classification accuracy was also greater in the near full-length

read. UniFrac distance matrices using jackknifed UPGMA clustering also noted

differences between the communities. These data support the consensus that longer

reads result in a finer phylogenetic resolution that may not be achieved by

shorter 16S rRNA gene fragments. Our work on the cattle rumen bacterial community

demonstrates that utilizing near full-length 16S reads may be useful in

conducting a more thorough study, or for developing a niche-specific database to

use in analyzing data from shorter read technologies when budgetary constraints

preclude use of near-full length 16S sequencing.


Copyright © 2016 Elsevier B.V. All rights reserved.


DOI: 10.1016/j.mimet.2016.06.004

PMID: 27282101  [PubMed - in process]



2. Int J Clin Exp Med. 2015 Oct 15;8(10):18560-70. eCollection 2015.


16S rRNA gene sequencing is a non-culture method of defining the specific

bacterial etiology of ventilator-associated pneumonia.


Xia LP(1), Bian LY(2), Xu M(3), Liu Y(4), Tang AL(4), Ye WQ(4).


Author information:

(1)Department of Nursing, Changhai Hospital, Second Military Medical

UniversityShanghai 200433, P. R. China; Department of Nursing, Yancheng Health

Vocational and Technical CollegeYancheng 224006, Jiangsu Province, P. R. China.

(2)Department of Nursing, Yancheng Health Vocational and Technical College

Yancheng 224006, Jiangsu Province, P. R. China. (3)Yancheng First People's

Hospital Yancheng 224006, Jiangsu Province, P. R. China. (4)Department of

Nursing, Changhai Hospital, Second Military Medical University Shanghai 200433,

P. R. China.


Ventilator-associated pneumonia (VAP) is an acquired respiratory tract infection

following tracheal intubation. The most common hospital-acquired infection among

patients with acute respiratory failure, VAP is associated with a mortality rate

of 20-30%. The standard bacterial culture method for identifying the etiology of

VAP is not specific, timely, or accurate in identifying the bacterial pathogens.

This study used 16S rRNA gene metagenomic sequencing to identify and quantify the

pathogenic bacteria in lower respiratory tract and oropharyngeal samples of 55

VAP patients. Sequencing of the 16S rRNA gene has served as a valuable tool in

bacterial identification, particularly when other biochemical, molecular, or

phenotypic identification techniques fail. In this study, 16S rRNA gene

sequencing was performed in parallel with the standard bacterial culture method

to identify and quantify bacteria present in the collected patient samples.

Sequence analysis showed the colonization of multidrug-resistant strains in VAP

secretions. Further, this method identified Prevotella, Proteus, Aquabacter, and

Sphingomonas bacterial genera that were not detected by the standard bacterial

culture method. Seven categories of bacteria, Streptococcus, Neisseria,

Corynebacterium, Acinetobacter, Staphylococcus, Pseudomonas and Klebsiella, were

detectable by both 16S rRNA gene sequencing and standard bacterial culture

methods. Further, 16S rRNA gene sequencing had a significantly higher sensitivity

in detecting Streptococcus and Pseudomonas when compared to standard bacterial

culture. Together, these data present 16S rRNA gene sequencing as a novel VAP

diagnosis tool that will further enable pathogen-specific treatment of VAP.



PMCID: PMC4694369

PMID: 26770469  [PubMed]


MRDNA Does 16s Sequencing



3. J Microbiol. 2016 Apr;54(4):296-304. doi: 10.1007/s12275-016-5571-4. Epub 2016

Apr 1.


Uncultured bacterial diversity in a seawater recirculating aquaculture system

revealed by 16S rRNA gene amplicon sequencing.


Lee DE(1), Lee J(2), Kim YM(3), Myeong JI(2), Kim KH(4).


Author information:

(1)Department of Microbiology, Pukyong National University, Busan, 48513,

Republic of Korea. (2)Aquaculture Research Division, National Institute of

Fisheries Science, Busan, 46083, Republic of Korea. (3)Department of Food Science

and Technology, Pukyong National University, Busan, 48513, Republic of Korea.

(4)Department of Microbiology, Pukyong National University, Busan, 48513,

Republic of Korea. kimkh@pknu.ac.kr.


Bacterial diversity in a seawater recirculating aquaculture system (RAS) was

investigated using 16S rRNA amplicon sequencing to understand the roles of

bacterial communities in the system. The RAS was operated at nine different

combinations of temperature (15°C, 20°C, and 25°C) and salinity (20‰, 25‰, and

32.5‰). Samples were collected from five or six RAS tanks (biofilters) for each

condition. Fifty samples were analyzed. Proteobacteria and Bacteroidetes were

most common (sum of both phyla: 67.2% to 99.4%) and were inversely proportional

to each other. Bacteria that were present at an average of ≥ 1% included

Actinobacteria (2.9%) Planctomycetes (2.0%), Nitrospirae (1.5%), and

Acidobacteria (1.0%); they were preferentially present in packed bed biofilters,

mesh biofilters, and maturation biofilters. The three biofilters showed higher

diversity than other RAS tanks (aerated biofilters, floating bed biofilters, and

fish tanks) from phylum to operational taxonomic unit (OTU) level. Samples were

clustered into several groups based on the bacterial communities. Major taxonomic

groups related to family Rhodobacteraceae and Flavobacteriaceae were distributed

widely in the samples. Several taxonomic groups like [Saprospiraceae],

Cytophagaceae, Octadecabacter, and Marivita showed a cluster-oriented

distribution. Phaeobacter and Sediminicola-related reads were detected frequently

and abundantly at low temperature. Nitrifying bacteria were detected frequently

and abundantly in the three biofilters. Phylogenetic analysis of the nitrifying

bacteria showed several similar OTUs were observed widely through the biofilters.

The diverse bacterial communities and the minor taxonomic groups, except for

Proteobacteria and Bacteroidetes, seemed to play important roles and seemed

necessary for nitrifying activity in the RAS, especially in packed bed

biofilters, mesh biofilters, and maturation biofilters.


DOI: 10.1007/s12275-016-5571-4

PMID: 27033205  [PubMed - indexed for MEDLINE]



4. J Basic Microbiol. 2016 Aug 12. doi: 10.1002/jobm.201600358. [Epub ahead of



Comparative analysis of bacteria associated with different mosses by 16S rRNA and

16S rDNA sequencing.


Tian Y(1), Li YH(1).


Author information:

(1)College of Life Science, Capital Normal University, Haidian District, Beijing,



To understand the differences of the bacteria associated with different mosses, a

phylogenetic study of bacterial communities in three mosses was carried out based

on 16S rDNA and 16S rRNA sequencing. The mosses used were Hygroamblystegium

noterophilum, Entodon compressus and Grimmia montana, representing hygrophyte,

shady plant and xerophyte, respectively. In total, the operational taxonomic

units (OTUs), richness and diversity were different regardless of the moss

species and the library level. All the examined 1183 clones were assigned to 248

OTUs, 56 genera were assigned in rDNA libraries and 23 genera were determined at

the rRNA level. Proteobacteria and Bacteroidetes were considered as the most

dominant phyla in all the libraries, whereas abundant Actinobacteria and

Acidobacteria were detected in the rDNA library of Entodon compressus and

approximately 24.7% clones were assigned to Candidate division TM7 in Grimmia

montana at rRNA level. The heatmap showed the bacterial profiles derived from

rRNA and rDNA were partly overlapping. However, the principle component analysis

of all the profiles derived from rDNA showed sharper differences between the

different mosses than that of rRNA-based profiles. This suggests that the

metabolically active bacterial compositions in different mosses were more

phylogenetically similar and the differences of the bacteria associated with

different mosses were mainly detected at the rDNA level. Obtained results clearly

demonstrate that combination of 16S rDNA and 16S rRNA sequencing is preferred

approach to have a good understanding on the constitution of the microbial

communities in mosses.


© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


DOI: 10.1002/jobm.201600358

PMID: 27515736  [PubMed - as supplied by publisher]


MRDNA Does Metagenome Sequencing



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