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

1. PLoS Negl Trop Dis. 2015 Aug 18;9(8):e0003929. doi: 10.1371/journal.pntd.0003929.

eCollection 2015.

 

A Comparison between Transcriptome Sequencing and 16S Metagenomics for Detection

of Bacterial Pathogens in Wildlife.

 

Razzauti M(1), Galan M(1), Bernard M(2), Maman S(3), Klopp C(3), Charbonnel N(1),

Vayssier-Taussat M(4), Eloit M(5), Cosson JF(1).

 

Author information:

(1)INRA, UMR CBGP (INRA / IRD / Cirad / Montpellier SupAgro), Montpellier,

France. (2)INRA, GABI, Domaine de Vilvert, Jouy-en-Josas, France. (3)INRA,

Sigenae Group, GenPhySE, INRA Auzeville, Castanet Tolosan, France. (4)INRA, UMR

Bipar, ENVA, ANSES, USC INRA, Maisons-Alfort, France. (5)PathoQuest SAS, Paris,

France; Ecole Nationale Vétérinaire d'Alfort, UMR 1161, Virologie ENVA, ANSES,

INRA, Maisons-Alfort, France; Pasteur Institute, Laboratory of Pathogen

Discovery, Biology of Infection Unit, Inserm U1117, Paris, France.

 

BACKGROUND: Rodents are major reservoirs of pathogens responsible for numerous

zoonotic diseases in humans and livestock. Assessing their microbial diversity at

both the individual and population level is crucial for monitoring endemic

infections and revealing microbial association patterns within reservoirs.

Recently, NGS approaches have been employed to characterize microbial communities

of different ecosystems. Yet, their relative efficacy has not been assessed.

Here, we compared two NGS approaches, RNA-Sequencing (RNA-Seq) and

16S-metagenomics, assessing their ability to survey neglected zoonotic bacteria

in rodent populations.

METHODOLOGY/PRINCIPAL FINDINGS: We first extracted nucleic acids from the spleens

of 190 voles collected in France. RNA extracts were pooled, randomly

retro-transcribed, then RNA-Seq was performed using HiSeq. Assembled bacterial

sequences were assigned to the closest taxon registered in GenBank. DNA extracts

were analyzed via a 16S-metagenomics approach using two sequencers: the 454

GS-FLX and the MiSeq. The V4 region of the gene coding for 16S rRNA was amplified

for each sample using barcoded universal primers. Amplicons were multiplexed and

processed on the distinct sequencers. The resulting datasets were de-multiplexed,

and each read was processed through a pipeline to be taxonomically classified

using the Ribosomal Database Project. Altogether, 45 pathogenic bacterial genera

were detected. The bacteria identified by RNA-Seq were comparable to those

detected by 16S-metagenomics approach processed with MiSeq (16S-MiSeq). In

contrast, 21 of these pathogens went unnoticed when the 16S-metagenomics approach

was processed via 454-pyrosequencing (16S-454). In addition, the 16S-metagenomics

approaches revealed a high level of coinfection in bank voles.

CONCLUSIONS/SIGNIFICANCE: We concluded that RNA-Seq and 16S-MiSeq are equally

sensitive in detecting bacteria. Although only the 16S-MiSeq method enabled

identification of bacteria in each individual reservoir, with subsequent

derivation of bacterial prevalence in host populations, and generation of

intra-reservoir patterns of bacterial interactions. Lastly, the number of

bacterial reads obtained with the 16S-MiSeq could be a good proxy for bacterial

prevalence.

 

DOI: 10.1371/journal.pntd.0003929

PMCID: PMC4540314

PMID: 26284930  [PubMed - indexed for MEDLINE]

 

 

2. BMC Res Notes. 2015 Dec 8;8:754. doi: 10.1186/s13104-015-1726-3.

 

Efficient extraction of small and large RNAs in bacteria for excellent total RNA

sequencing and comprehensive transcriptome analysis.

 

Heera R(1,)(2), Sivachandran P(3), Chinni SV(4), Mason J(5,)(6), Croft L(7),

Ravichandran M(8), Yin LS(9).

 

Author information:

(1)Department of Biotechnology, Faculty of Applied Sciences, AIMST University,

Semeling, 08100, Bedong, Kedah, Malaysia. heraadaas@gmail.com. (2)Unit of

Biochemistry, Faculty of Medicine, AIMST University, Semeling, 08100, Bedong,

Kedah, Malaysia. heraadaas@gmail.com. (3)Department of Biotechnology, Faculty of

Applied Sciences, AIMST University, Semeling, 08100, Bedong, Kedah, Malaysia.

sivachandranparimannan@gmail.com. (4)Department of Biotechnology, Faculty of

Applied Sciences, AIMST University, Semeling, 08100, Bedong, Kedah, Malaysia.

cvsureshgupta@gmail.com. (5)Malaysian Genomics Resource Centre, 27-9, Level 9

Boulevard Signature Offices, 59200, Mid Valley City, Malaysia.

Joanne.mason@ouh.nhs.uk. (6)Oxford Biomedical Research Centre, Old Road

Headington Oxford, Oxfordshire, OX3 7LE, UK. Joanne.mason@ouh.nhs.uk.

(7)Malaysian Genomics Resource Centre, 27-9, Level 9 Boulevard Signature Offices,

59200, Mid Valley City, Malaysia. laurence@mgrc.com.my. (8)Department of

Biotechnology, Faculty of Applied Sciences, AIMST University, Semeling, 08100,

Bedong, Kedah, Malaysia. ravichandran@aimst.edu.my. (9)Department of

Biotechnology, Faculty of Applied Sciences, AIMST University, Semeling, 08100,

Bedong, Kedah, Malaysia. su_yin@aimst.edu.my.

 

BACKGROUND: Next-generation transcriptome sequencing (RNA-Seq) has become the

standard practice for studying gene splicing, mutations and changes in gene

expression to obtain valuable, accurate biological conclusions. However,

obtaining good sequencing coverage and depth to study these is impeded by the

difficulties of obtaining high quality total RNA with minimal genomic DNA

contamination. With this in mind, we evaluated the performance of Phenol-free

total RNA purification kit (Amresco) in comparison with TRI Reagent (MRC) and

RNeasy Mini (Qiagen) for the extraction of total RNA of Pseudomonas aeruginosa

which was grown in glucose-supplemented (control) and polyethylene-supplemented

(growth-limiting condition) minimal medium. All three extraction methods were

coupled with an in-house DNase I treatment before the yield, integrity and size

distribution of the purified RNA were assessed. RNA samples extracted with the

best extraction kit were then sequenced using the Illumina HiSeq 2000 platform.

RESULTS: TRI Reagent gave the lowest yield enriched with small RNAs (sRNAs),

while RNeasy gave moderate yield of good quality RNA with trace amounts of sRNAs.

The Phenol-free kit, on the other hand, gave the highest yield and the best

quality RNA (RIN value of 9.85 ± 0.3) with good amounts of sRNAs. Subsequent

bioinformatic analysis of the sequencing data revealed that 5435 coding genes,

452 sRNAs and 7 potential novel intergenic sRNAs were detected, indicating

excellent sequencing coverage across RNA size ranges. In addition, detection of

low abundance transcripts and consistency of their expression profiles across

replicates from the same conditions demonstrated the reproducibility of the RNA

extraction technique.

CONCLUSIONS: Amresco's Phenol-free Total RNA purification kit coupled with DNase

I treatment yielded the highest quality RNAs containing good ratios of high and

low molecular weight transcripts with minimal genomic DNA. These RNA extracts

gave excellent non-biased sequencing coverage useful for comprehensive total

transcriptome sequencing and analysis. Furthermore, our findings would be useful

for those interested in studying both coding and non-coding RNAs from precious

bacterial samples cultivated in growth-limiting condition, in a single sequencing

run.

 

DOI: 10.1186/s13104-015-1726-3

PMCID: PMC4673735

PMID: 26645211  [PubMed - indexed for MEDLINE]

 

 

3. Microbiol Res. 2015 Jan;170:248-54. doi: 10.1016/j.micres.2014.10.003. Epub 2014

Nov 6.

 

Deep sequencing analysis of the Kineococcus radiotolerans transcriptome in

response to ionizing radiation.

 

Li L(1), Chen Z(2), Ding X(3), Shan Z(4), Liu L(5), Guo J(6).

 

Author information:

(1)College of Life Sciences, Zhejiang Sci-Tech University, No.2 Road, Xiasha,

Hangzhou, Zhejiang, PR China. Electronic address: rabbitlee.bio@gmail.com.

(2)College of Life Sciences, Zhejiang Sci-Tech University, No.2 Road, Xiasha,

Hangzhou, Zhejiang, PR China. Electronic address: chenzhouweiwenzhou@126.com.

(3)College of Life Sciences, Zhejiang Sci-Tech University, No.2 Road, Xiasha,

Hangzhou, Zhejiang, PR China. Electronic address: bdd114@163.com. (4)College of

Life Sciences, Zhejiang Sci-Tech University, No.2 Road, Xiasha, Hangzhou,

Zhejiang, PR China. Electronic address: zjzj@live.com. (5)College of Life

Sciences, Zhejiang Sci-Tech University, No.2 Road, Xiasha, Hangzhou, Zhejiang, PR

China. Electronic address: llliu@zstu.edu.cn. (6)College of Life Sciences,

Zhejiang Sci-Tech University, No.2 Road, Xiasha, Hangzhou, Zhejiang, PR China.

Electronic address: jfguo@zstu.edu.cn.

 

Kineococcus radiotolerans is a gram-positive, radiation-resistant bacterium that

was isolated from a radioactive environment. The synergy of several groups of

genes is thought to contribute to the radio-resistance of this species of

bacteria. Sequencing of the transcriptome, RNA sequencing (RNA-seq), using deep

sequencing technology can reveal the genes that are differentially expressed in

response to radiation in this bacterial strain. In this study, the transcriptomes

of two samples (with and without irradiation treatment) were sequencing by deep

sequencing technology. After the bioinformatics process, 143 genes were screened

out by the differential expression (DE) analysis. In all 143 differentially

expressed genes, 20 genes were annotated to be related to the radio-resistance

based on the cluster analysis by the cluster of orthologous groups of proteins

(COG) annotation which were validated by the quantitative RT-PCR. The pathway

analysis revealed that these 20 validated genes were related to DNA damage

repair, including recA, ruvA and ruvB, which were considered to be the key genes

in DNA damage repair. This study provides the foundation to investigate the

regulatory mechanism of these genes.

 

Copyright © 2014 Elsevier GmbH. All rights reserved.

 

DOI: 10.1016/j.micres.2014.10.003

PMID: 25467197  [PubMed - indexed for MEDLINE]

 

 

4. Plant Physiol. 2015 Sep;169(1):233-65. doi: 10.1104/pp.15.00350. Epub 2015 Jul

14.

 

Deep Sequencing of the Medicago truncatula Root Transcriptome Reveals a Massive

and Early Interaction between Nodulation Factor and Ethylene Signals.

 

Larrainzar E(1), Riely BK(1), Kim SC(1), Carrasquilla-Garcia N(1), Yu HJ(1),

Hwang HJ(1), Oh M(1), Kim GB(1), Surendrarao AK(1), Chasman D(1), Siahpirani

AF(1), Penmetsa RV(1), Lee GS(1), Kim N(1), Roy S(1), Mun JH(2), Cook DR(2).

 

Author information:

(1)Department of Plant Pathology (E.L., B.K.R., N.C.-G., R.V.P., D.R.C) and Plant

Biology Graduate Group (A.K.S.), University of California, Davis, California

95616;Korean Research Institute of Bioscience and Biotechnology, Daejeon 305-806,

Republic of Korea (S.C.K., N.K.);Catholic University of Korea, Bucheon 420-743,

Republic of Korea (H.-J.Y.);Rural Development Administration, Jeonju 560-500,

Republic of Korea (H.-J.H., M.O., G.-S.L.);Myongji University, Yongin 449-728,

Republic of Korea (G.B.K., J.-H.M.);Wisconsin Institute for Discovery, Madison,

Wisconsin 53715 (D.C., S.R.); andDepartment of Computer Sciences (A.F.S.) and

Department of Biostatistics and Medical Informatics (S.R.), University of

Wisconsin, Madison, Wisconsin 53715. (2)Department of Plant Pathology (E.L.,

B.K.R., N.C.-G., R.V.P., D.R.C) and Plant Biology Graduate Group (A.K.S.),

University of California, Davis, California 95616;Korean Research Institute of

Bioscience and Biotechnology, Daejeon 305-806, Republic of Korea (S.C.K.,

N.K.);Catholic University of Korea, Bucheon 420-743, Republic of Korea

(H.-J.Y.);Rural Development Administration, Jeonju 560-500, Republic of Korea

(H.-J.H., M.O., G.-S.L.);Myongji University, Yongin 449-728, Republic of Korea

(G.B.K., J.-H.M.);Wisconsin Institute for Discovery, Madison, Wisconsin 53715

(D.C., S.R.); andDepartment of Computer Sciences (A.F.S.) and Department of

Biostatistics and Medical Informatics (S.R.), University of Wisconsin, Madison,

Wisconsin 53715 munjh@mju.ac.kr drcook@ucdavis.edu.

 

The legume-rhizobium symbiosis is initiated through the activation of the

Nodulation (Nod) factor-signaling cascade, leading to a rapid reprogramming of

host cell developmental pathways. In this work, we combine transcriptome

sequencing with molecular genetics and network analysis to quantify and

categorize the transcriptional changes occurring in roots of Medicago truncatula

from minutes to days after inoculation with Sinorhizobium medicae. To identify

the nature of the inductive and regulatory cues, we employed mutants with absent

or decreased Nod factor sensitivities (i.e. Nodulation factor perception and

Lysine motif domain-containing receptor-like kinase3, respectively) and an

ethylene (ET)-insensitive, Nod factor-hypersensitive mutant (sickle). This unique

data set encompasses nine time points, allowing observation of the symbiotic

regulation of diverse biological processes with high temporal resolution. Among

the many outputs of the study is the early Nod factor-induced, ET-regulated

expression of ET signaling and biosynthesis genes. Coupled with the observation

of massive transcriptional derepression in the ET-insensitive background, these

results suggest that Nod factor signaling activates ET production to attenuate

its own signal. Promoter:β-glucuronidase fusions report ET biosynthesis both in

root hairs responding to rhizobium as well as in meristematic tissue during

nodule organogenesis and growth, indicating that ET signaling functions at

multiple developmental stages during symbiosis. In addition, we identified

thousands of novel candidate genes undergoing Nod factor-dependent, ET-regulated

expression. We leveraged the power of this large data set to model Nod factor-

and ET-regulated signaling networks using MERLIN, a regulatory network inference

algorithm. These analyses predict key nodes regulating the biological process

impacted by Nod factor perception. We have made these results available to the

research community through a searchable online resource.

 

© 2015 American Society of Plant Biologists. All Rights Reserved.

 

DOI: 10.1104/pp.15.00350

PMCID: PMC4577383

PMID: 26175514  [PubMed - indexed for MEDLINE]

 

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