1. J Microbiol Methods. 2016 Aug;127:132-40. doi: 10.1016/j.mimet.2016.06.004. Epub
2016 Jun 6.
Myer PR(1), Kim M(2), Freetly HC(3), Smith TP(4).
(1)Department of Animal Science, University of Tennesse Institute of Agriculture,
University of Tennessee, Knoxville, TN 37996. Electronic address: firstname.lastname@example.org.
(2)USDA-ARS, U.S. Meat Animal Research Center, Clay Center, NE 68933(1).
Electronic address: email@example.com. (3)USDA-ARS, U.S. Meat Animal Research
Center, Clay Center, NE 68933(1). Electronic address:
firstname.lastname@example.org. (4)USDA-ARS, U.S. Meat Animal Research Center, Clay
Center, NE 68933(1). Electronic address: email@example.com.
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.
PMID: 27282101 [PubMed - in process]
2. Int J Clin Exp Med. 2015 Oct 15;8(10):18560-70. eCollection 2015.
Xia LP(1), Bian LY(2), Xu M(3), Liu Y(4), Tang AL(4), Ye WQ(4).
(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.
PMID: 26770469 [PubMed]
3. J Microbiol. 2016 Apr;54(4):296-304. doi: 10.1007/s12275-016-5571-4. Epub 2016
Lee DE(1), Lee J(2), Kim YM(3), Myeong JI(2), Kim KH(4).
(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. firstname.lastname@example.org.
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.
PMID: 27033205 [PubMed - indexed for MEDLINE]
4. J Basic Microbiol. 2016 Aug 12. doi: 10.1002/jobm.201600358. [Epub ahead of
Tian Y(1), Li YH(1).
(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.
PMID: 27515736 [PubMed - as supplied by publisher]