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41. Am J Primatol. 2015 May;77(5):563-78. doi: 10.1002/ajp.22378. Epub 2015 Feb 12.


Influence of age, reproductive cycling status, and menstruation on the vaginal

microbiome in baboons (Papio anubis).


Uchihashi M(1), Bergin IL, Bassis CM, Hashway SA, Chai D, Bell JD.


Author information:

(1)Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor,



The vaginal microbiome is believed to influence host health by providing

protection from pathogens and influencing reproductive outcomes such as fertility

and gestational length. In humans, age-associated declines in diversity of the

vaginal microbiome occur in puberty and persist into adulthood. Additionally,

menstruation has been associated with decreased microbial community stability.

Adult female baboons, like other non-human primates (NHPs), have a different and

highly diverse vaginal microbiome compared to that of humans, which is most

commonly dominated by Lactobacillus spp. We evaluated the influence of age,

reproductive cycling status (cycling vs. non-cycling) and menstruation on the

vaginal microbiome of 38 wild-caught, captive female olive baboons (Papio anubis)

by culture-independent sequencing of the V3-V5 region of the bacterial 16S rRNA

gene. All baboons had highly diverse vaginal microbial communities. Adult baboons

had significantly lower microbial diversity in comparison to subadult baboons,

which was attributable to decreased relative abundance of minor taxa. No

significant differences were detected based on cycling state or menstruation.

Predictive metagenomic analysis showed uniformity in relative abundance of

metabolic pathways regardless of age, cycle stage, or menstruation, indicating

conservation of microbial community functions. This study suggests that selection

of an optimal vaginal microbial community occurs at puberty. Since decreased

diversity occurs in both baboons and humans at puberty, this may reflect a

general strategy for selection of adult vaginal microbial communities.

Comparative evaluation of vaginal microbial community development and composition

may elucidate mechanisms of community formation and function that are conserved

across host species or across microbial community types. These findings have

implications for host health, evolutionary biology, and microbe-host ecosystems.


© 2015 Wiley Periodicals, Inc.


DOI: 10.1002/ajp.22378

PMCID: PMC4458466

PMID: 25676781  [PubMed - indexed for MEDLINE]



42. Sci Rep. 2015 Mar 11;5:8988. doi: 10.1038/srep08988.


The vaginal microbiome during pregnancy and the postpartum period in a European



MacIntyre DA(1), Chandiramani M(1), Lee YS(1), Kindinger L(1), Smith A(2),

Angelopoulos N(3), Lehne B(4), Arulkumaran S(1), Brown R(1), Teoh TG(5), Holmes

E(6), Nicoholson JK(7), Marchesi JR(8), Bennett PR(1).


Author information:

(1)Imperial College Parturition Research Group, Division of the Institute of

Reproduction and Developmental Biology, Imperial College London, UK. (2)School of

Biosciences, Cardiff University, UK. (3)Division of Cancer, Department of Surgery

and Cancer, Imperial College London, UK. (4)Department of Epidemiology

&Biostatistics, Medicine, Imperial College London, UK. (5)St Mary's Hospital,

Imperial College Healthcare NHS Trust, London, UK. (6)Section of Biomolecular

Medicine, Division of Computational Systems Medicine, Department of Surgery and

Cancer, Imperial College London, UK. (7)1] Section of Biomolecular Medicine,

Division of Computational Systems Medicine, Department of Surgery and Cancer,

Imperial College London, UK [2] MRC NIHR National Phenome Centre, Division of

Computational Systems Medicine, Department of Surgery and Cancer, Imperial

College London, UK. (8)1] School of Biosciences, Cardiff University, UK [2]

Section of Biomolecular Medicine, Division of Computational Systems Medicine,

Department of Surgery and Cancer, Imperial College London, UK.


The composition and structure of the pregnancy vaginal microbiome may influence

susceptibility to adverse pregnancy outcomes. Studies on the pregnant vaginal

microbiome have largely been limited to Northern American populations. Using

MiSeq sequencing of 16S rRNA gene amplicons, we characterised the vaginal

microbiota of a mixed British cohort of women (n = 42) who experienced

uncomplicated term delivery and who were sampled longitudinally throughout

pregnancy (8-12, 20-22, 28-30 and 34-36 weeks gestation) and 6 weeks postpartum.

We show that vaginal microbiome composition dramatically changes postpartum to

become less Lactobacillus spp. dominant with increased alpha-diversity

irrespective of the community structure during pregnancy and independent of

ethnicity. While the pregnancy vaginal microbiome was characteristically

dominated by Lactobacillus spp. and low alpha-diversity, unlike Northern American

populations, a significant number of pregnant women this British population had a

L. jensenii-dominated microbiome characterised by low alpha-diversity. L.

jensenii was predominantly observed in women of Asian and Caucasian ethnicity

whereas L. gasseri was absent in samples from Black women. This study reveals new

insights into biogeographical and ethnic effects upon the pregnancy and

postpartum vaginal microbiome and has important implications for future studies

exploring relationships between the vaginal microbiome, host health and pregnancy



DOI: 10.1038/srep08988

PMCID: PMC4355684

PMID: 25758319  [PubMed - indexed for MEDLINE]



47. PLoS One. 2015 May 5;10(5):e0124631. doi: 10.1371/journal.pone.0124631.

eCollection 2015.


The impact of various time intervals on the supragingival plaque dynamic core



Jiang WX(1), Hu YJ(1), Gao L(1), He ZY(1), Zhu CL(1), Ma R(1), Huang ZW(1).


Author information:

(1)Department of Endodontics, Ninth People's Hospital, Shanghai Jiao Tong

University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai,



OBJECTIVE: The aim of this study was to examine the influence of various time

intervals on the composition of the supragingival plaque microbiome, especially

the dynamic core microbiome, and to find a suitable observation interval for

further studies on oral microbiota.

METHODS AND MATERIALS: Eight qualified volunteers whose respective age ranges

from 25 to 28 years participated in the present study. The supragingival plaque

was collected from the buccogingival surface of the maxillary first molar at

eight time slots with different intervals (day 0, 1 day, 3 days, 1 week, 2 weeks,

3 weeks, 1 month, and 3 months). Bioinformatic analyses was performed based on

16S rDNA pyrosequencing (454 sequencing platform) targeting at the hypervariable

V4-V5 region, in order to assess the diversity and variation of the supragingival

plaque microbiome.

RESULTS: A total of 359,565 qualified reads for 64 samples were generated for

subsequent analyses, which represents 8,452 operational taxonomic units

identified at 3% dissimilarity. The dynamic core microbiome detected in the

current study included five phyla, 12 genera and 13 species. At the genus level,

the relative abundance of bacterial communities under the "1 day," "1 month," and

"3 months" intervals was clustered into sub-category. At the species level, the

number of overlapping species remained stable between the "1 month" and "3

months" intervals, whereas the number of dynamic core species became stable

within only 1 week.

CONCLUSIONS: This study emphasized the impact of different time intervals (days,

weeks and months) on the composition, commonality and diversity of the

supragingival microbiome. The analyses found that for various types of studies,

the time interval of a month is more suitable for observing the general

composition of the supragingival microbiome, and that a week is better for

observing the dynamic core microbiome.


DOI: 10.1371/journal.pone.0124631

PMCID: PMC4420457

PMID: 25942317  [PubMed - indexed for MEDLINE]


101. PLoS One. 2014 Mar 11;9(3):e90731. doi: 10.1371/journal.pone.0090731. eCollection



Seasonal variation in human gut microbiome composition.


Davenport ER(1), Mizrahi-Man O(1), Michelini K(1), Barreiro LB(1), Ober C(1),

Gilad Y(1).


Author information:

(1)Department of Human Genetics, University of Chicago, Chicago, Illinois, United

States of America.


The composition of the human gut microbiome is influenced by many environmental

factors. Diet is thought to be one of the most important determinants, though we

have limited understanding of the extent to which dietary fluctuations alter

variation in the gut microbiome between individuals. In this study, we examined

variation in gut microbiome composition between winter and summer over the course

of one year in 60 members of a founder population, the Hutterites. Because of

their communal lifestyle, Hutterite diets are similar across individuals and

remarkably stable throughout the year, with the exception that fresh produce is

primarily served during the summer and autumn months. Our data indicate that

despite overall gut microbiome stability within individuals over time, there are

consistent and significant population-wide shifts in microbiome composition

across seasons. We found seasonal differences in both (i) the abundance of

particular taxa (false discovery rate <0.05), including highly abundant phyla

Bacteroidetes and Firmicutes, and (ii) overall gut microbiome diversity (by

Shannon diversity; P = 0.001). It is likely that the dietary fluctuations between

seasons with respect to produce availability explain, at least in part, these

differences in microbiome composition. For example, high levels of produce

containing complex carbohydrates consumed during the summer months might explain

increased abundance of Bacteroidetes, which contain complex carbohydrate

digesters, and decreased levels of Actinobacteria, which have been negatively

correlated to fiber content in food questionnaires. Our observations demonstrate

the plastic nature of the human gut microbiome in response to variation in diet.


DOI: 10.1371/journal.pone.0090731

PMCID: PMC3949691

PMID: 24618913  [PubMed - indexed for MEDLINE]



102. Chemosphere. 2014 Oct;112:1-8. doi: 10.1016/j.chemosphere.2014.03.068. Epub 2014

Apr 21.


Metagenomic profiles and antibiotic resistance genes in gut microbiota of mice

exposed to arsenic and iron.


Guo X(1), Liu S(1), Wang Z(1), Zhang XX(1), Li M(1), Wu B(2).


Author information:

(1)State Key Lab of Pollutant Control and Resource Reuse, School of the

Environment, Nanjing University, Nanjing 210023, PR China. (2)State Key Lab of

Pollutant Control and Resource Reuse, School of the Environment, Nanjing

University, Nanjing 210023, PR China. Electronic address:


Iron (Fe) has been widely applied to treat arsenic (As)-contaminated water, and

Fe could influence bioavailability and toxicity of As. However, little is known

about the impact of As and/or Fe on gut microbiota, which plays important roles

in host health. In this study, high-throughput sequencing and quantitative real

time PCR were applied to analyze the impact of As and Fe on mouse gut microbiota.

Co-exposure of As and Fe mitigated effects on microbial community to a certain

extent. Correlation analysis showed the shifts in gut microbiota caused by As

and/or Fe exposure might be important reason of changes in metabolic profiles of

mouse. For antibiotic resistance genes (ARGs), co-exposure of As and Fe increased

types and abundance of ARGs. But for high abundance ARGs, such as tetQ, tetO and

tetM, co-exposure of As and Fe mitigated effects on their abundances compared to

exposure to As and Fe alone. No obvious relationship between ARGs and mobile

genetic elements were found. The changes in ARGs caused by metal exposure might

be due to the alteration of gut microbial diversity. Our results show that

changes of gut microbial community caused by As and/or Fe can influence host

metabolisms and abundances of ARGs in gut, indicating that changes of gut

microbiota should be considered during the risk assessment of As and/or Fe.


Copyright © 2014 Elsevier Ltd. All rights reserved.


DOI: 10.1016/j.chemosphere.2014.03.068

PMID: 25048881  [PubMed - indexed for MEDLINE]



103. Int J Mol Sci. 2014 Jul 14;15(7):12364-78. doi: 10.3390/ijms150712364.


Exploring neighborhoods in the metagenome universe.


Aßhauer KP(1), Klingenberg H(2), Lingner T(3), Meinicke P(4).


Author information:

(1)Department of Bioinformatics, Institute for Microbiology and Genetics,

University of Göttingen, 37077 Göttingen, Germany.

(2)Department of Bioinformatics, Institute for Microbiology and Genetics,

University of Göttingen, 37077 Göttingen, Germany.

(3)Department of Bioinformatics, Institute for Microbiology and Genetics,

University of Göttingen, 37077 Göttingen, Germany.

(4)Department of Bioinformatics, Institute for Microbiology and Genetics,

University of Göttingen, 37077 Göttingen, Germany.


The variety of metagenomes in current databases provides a rapidly growing source

of information for comparative studies. However, the quantity and quality of

supplementary metadata is still lagging behind. It is therefore important to be

able to identify related metagenomes by means of the available sequence data

alone. We have studied efficient sequence-based methods for large-scale

identification of similar metagenomes within a database retrieval context. In a

broad comparison of different profiling methods we found that vector-based

distance measures are well-suitable for the detection of metagenomic neighbors.

Our evaluation on more than 1700 publicly available metagenomes indicates that

for a query metagenome from a particular habitat on average nine out of ten

nearest neighbors represent the same habitat category independent of the utilized

profiling method or distance measure. While for well-defined labels a

neighborhood accuracy of 100% can be achieved, in general the neighbor detection

is severely affected by a natural overlap of manually annotated categories. In

addition, we present results of a novel visualization method that is able to

reflect the similarity of metagenomes in a 2D scatter plot. The visualization

method shows a similarly high accuracy in the reduced space as compared with the

high-dimensional profile space. Our study suggests that for inspection of

metagenome neighborhoods the profiling methods and distance measures can be

chosen to provide a convenient interpretation of results in terms of the

underlying features. Furthermore, supplementary metadata of metagenome samples in

the future needs to comply with readily available ontologies for fine-grained and

standardized annotation. To make profile-based k-nearest-neighbor search and the

2D-visualization of the metagenome universe available to the research community,

we included the proposed methods in our CoMet-Universe server for comparative

metagenome analysis.


DOI: 10.3390/ijms150712364

PMCID: PMC4139848

PMID: 25026170  [PubMed - indexed for MEDLINE]



104. Clin Transl Sci. 2014 Feb;7(1):74-81. doi: 10.1111/cts.12131. Epub 2014 Jan 14.


Understanding the apothecaries within: the necessity of a systematic approach for

defining the chemical output of the human microbiome.


Beebe K(1), Sampey B, Watkins SM, Milburn M, Eckhart AD.


Author information:

(1)Metabolon Inc, Durham, North Carolina, USA.


The human microbiome harbors a massive diversity of microbes that effectively

form an "organ" that strongly influences metabolism and immune function and

hence, human health. Although the growing interest in the microbiome has chiefly

arisen due to its impact on human physiology, the probable rules of operation are

embedded in the roots of microbiology where chemical communication (i.e., with

metabolites) is a dominant feature of coexistence. Indeed, recent examples in

microbiome research offer the impression that the collective microbiome operates

as an "apothecary," creating chemical concoctions that influence health and alter

drug response. Although these principles are not unappreciated, the majority of

emphasis is on metagenomics and research efforts often omit systematic efforts to

interrogate the chemical component of the complex equation between microbial

community and host phenotype. One of the reasons for this omission may be due to

the inaccessibility to high-breadth, high-throughput, and scalable technologies.

Since these technologies are now available, we propose that a more systematic

effort to survey the host-microbiota chemical output be embedded into microbiome

research as there is strong likelihood, and growing precedence, that this

component may often be integral to developing our understanding of these ultimate

apothecaries and how they impact human health.


© 2014 Wiley Periodicals, Inc.


DOI: 10.1111/cts.12131

PMID: 24422665  [PubMed - indexed for MEDLINE]



105. PLoS One. 2015 Dec 3;10(12):e0144448. doi: 10.1371/journal.pone.0144448.

eCollection 2015.


Functional Metagenomics of the Bronchial Microbiome in COPD.


Millares L(1,)(2,)(3,)(4), Pérez-Brocal V(5,)(6,)(7), Ferrari R(5,)(6,)(7),

Gallego M(8), Pomares X(2,)(8), García-Núñez M(1,)(2,)(3,)(4), Montón C(2,)(8),

Capilla S(9), Monsó E(2,)(3,)(8), Moya A(5,)(6,)(7).


Author information:

(1)Fundació Parc Taulí, Sabadell, Spain. (2)CIBER de Enfermedades Respiratorias,

CIBERES, Bunyola, Spain. (3)Universitat Autònoma de Barcelona, Esfera UAB,

Barcelona, Spain. (4)Fundació Insitut d'Investigació Germans Trias i Pujol,

Badalona, Spain. (5)Genomics and Health Area, Fundación para el Fomento de la

Investigación Sanitaria y Biomédica de la Comunidad Valenciana (FISABIO-Public

Health), Valencia, Spain. (6)CIBER Epidemiología y Salud Pública (CIBERESP),

Barcelona, Spain. (7)Evolutionary Genetics Unit, Institut Cavanilles de

Biodiversitat i Biologia Evolutiva (ICBiBE), Universitat de València, Valencia,

Spain. (8)Department of Respiratory Medicine, Hospital Universitari Parc Taulí,

Sabadell, Spain. (9)Department of Microbiology, Hospital Universitari Parc Taulí,

Sabadell, Spain.


The course of chronic obstructive pulmonary disease (COPD) is frequently

aggravated by exacerbations, and changes in the composition and activity of the

microbiome may be implicated in their appearance. The aim of this study was to

analyse the composition and the gene content of the microbial community in

bronchial secretions of COPD patients in both stability and exacerbation.

Taxonomic data were obtained by 16S rRNA gene amplification and pyrosequencing,

and metabolic information through shotgun metagenomics, using the Metagenomics

RAST server (MG-RAST), and the PICRUSt (Phylogenetic Investigation of Communities

by Reconstruction of Unobserved States) programme, which predict metagenomes from

16S data. Eight severe COPD patients provided good quality sputum samples, and no

significant differences in the relative abundance of any phyla and genera were

found between stability and exacerbation. Bacterial biodiversity (Chao1 and

Shannon indexes) did not show statistical differences and beta-diversity analysis

(Bray-Curtis dissimilarity index) showed a similar microbial composition in the

two clinical situations. Four functional categories showed statistically

significant differences with MG-RAST at KEGG level 2: in exacerbation, Cell

growth and Death and Transport and Catabolism decreased in abundance [1.6

(0.2-2.3) vs 3.6 (3.3-6.9), p = 0.012; and 1.8 (0-3.3) vs 3.6 (1.8-5.1), p =

0.025 respectively], while Cancer and Carbohydrate Metabolism increased [0.8

(0-1.5) vs 0 (0-0.5), p = 0.043; and 7 (6.4-9) vs 5.9 (6.3-6.1), p = 0.012

respectively]. In conclusion, the bronchial microbiome as a whole is not

significantly modified when exacerbation symptoms appear in severe COPD patients,

but its functional metabolic capabilities show significant changes in several



DOI: 10.1371/journal.pone.0144448

PMCID: PMC4669145

PMID: 26632844  [PubMed - indexed for MEDLINE]



106. Hepatology. 2016 Mar;63(3):764-75. doi: 10.1002/hep.28356. Epub 2016 Jan 13.


The severity of nonalcoholic fatty liver disease is associated with gut dysbiosis

and shift in the metabolic function of the gut microbiota.


Boursier J(1,)(2), Mueller O(3), Barret M(4), Machado M(5), Fizanne L(2),

Araujo-Perez F(6), Guy CD(7), Seed PC(3,)(6), Rawls JF(3), David LA(3), Hunault

G(2), Oberti F(1,)(2), Calès P(1,)(2), Diehl AM(5).


Author information:

(1)Hepato-Gastroenterology Department, University Hospital, Angers, France.

(2)HIFIH Laboratory, UPRES 3859, SFR 4208, LUNAM University, Angers, France.

(3)Center for Genomics of Microbial Systems, Department of Molecular Genetics and

Microbiology, Duke University Medical Center, Durham, NC. (4)INRA, UMR1345

Institut de Recherches en Horticulture et Semences, SFR4207 QUASAV, Beaucouzé,

France. (5)Division of Gastroenterology, Department of Medicine, Duke University

Medical Center, Durham, NC. (6)Department of Pediatrics, Duke University Medical

Center, Durham, NC. (7)Department of Pathology, Duke University Medical Center,

Durham, NC.


Several animal studies have emphasized the role of gut microbiota in nonalcoholic

fatty liver disease (NAFLD). However, data about gut dysbiosis in human NAFLD

remain scarce in the literature, especially studies including the whole spectrum

of NAFLD lesions. We aimed to evaluate the association between gut dysbiosis and

severe NAFLD lesions, that is, nonalcoholic steatohepatitis (NASH) and fibrosis,

in a well-characterized population of adult NAFLD. Fifty-seven patients with

biopsy-proven NAFLD were enrolled. Taxonomic composition of gut microbiota was

determined using 16S ribosomal RNA gene sequencing of stool samples. Thirty

patients had F0/F1 fibrosis stage at liver biopsy (10 with NASH), and 27 patients

had significant F≥2 fibrosis (25 with NASH). Bacteroides abundance was

significantly increased in NASH and F≥2 patients, whereas Prevotella abundance

was decreased. Ruminococcus abundance was significantly higher in F≥2 patients.

By multivariate analysis, Bacteroides abundance was independently associated with

NASH and Ruminococcus with F≥2 fibrosis. Stratification according to the

abundance of these two bacteria generated three patient subgroups with increasing

severity of NAFLD lesions. Based on imputed metagenomic profiles, Kyoto

Encyclopedia of Genes and Genomes pathways significantly related to NASH and

fibrosis F≥2 were mostly related to carbohydrate, lipid, and amino acid

metabolism.CONCLUSION: NAFLD severity associates with gut dysbiosis and a shift

in metabolic function of the gut microbiota. We identified Bacteroides as

independently associated with NASH and Ruminococcus with significant fibrosis.

Thus, gut microbiota analysis adds information to classical predictors of NAFLD

severity and suggests novel metabolic targets for pre-/probiotics therapies.


© 2015 by the American Association for the Study of Liver Diseases.


DOI: 10.1002/hep.28356

PMCID: PMC4975935 [Available on 2017-03-01]

PMID: 26600078  [PubMed - indexed for MEDLINE]



107. Nature. 2015 May 14;521(7551):S10-1. doi: 10.1038/521S10a.


Microbiome: Microbial mystery.


DeWeerdt S.


DOI: 10.1038/521S10a

PMID: 25970451  [PubMed - indexed for MEDLINE]



108. BMC Microbiol. 2013 Dec 28;13:303. doi: 10.1186/1471-2180-13-303.


The murine lung microbiome in relation to the intestinal and vaginal bacterial



Barfod KK(1), Roggenbuck M, Hansen LH, Schjørring S, Larsen ST, Sørensen SJ,

Krogfelt KA.


Author information:

(1)Statens Serum Institut, Artillerivej 5, 2300 Copenhagen S, Denmark.


BACKGROUND: This work provides the first description of the bacterial population

of the lung microbiota in mice. The aim of this study was to examine the lung

microbiome in mice, the most used animal model for inflammatory lung diseases

such as COPD, cystic fibrosis and asthma.Bacterial communities from

broncho-alveolar lavage fluids and lung tissue were compared to samples taken

from fecal matter (caecum) and vaginal lavage fluid from female BALB/cJ mice.

RESULTS: Using a customized 16S rRNA sequencing protocol amplifying the V3-V4

region our study shows that the mice have a lung microbiome that cluster

separately from mouse intestinal microbiome (caecum). The mouse lung microbiome

is dominated by Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes and

Cyanobacteria overlapping the vaginal microbiome. We also show that removal of

host tissue or cells from lung fluid during the DNA extraction step has an impact

on the resulting bacterial community profile. Sample preparation needs to be

considered when choosing an extraction method and interpreting data.

CONCLUSIONS: We have consistently amplified bacterial DNA from mouse lungs that

is distinct from the intestinal microbiome in these mice. The gut microbiome has

been extensively studied for its links to development of disease. Here we suggest

that also the lung microbiome could be important in relation to inflammatory lung

diseases. Further research is needed to understand the contribution of the lung

microbiome and the gut-lung axis to the development of lung diseases such as COPD

and asthma.


DOI: 10.1186/1471-2180-13-303

PMCID: PMC3878784

PMID: 24373613  [PubMed - indexed for MEDLINE]



109. PLoS One. 2014 Jan 15;9(1):e84963. doi: 10.1371/journal.pone.0084963. eCollection



Recruiting human microbiome shotgun data to site-specific reference genomes.


Xie G(1), Lo CC(1), Scholz M(1), Chain PS(1).


Author information:

(1)Genome Science Group, Los Alamos National Laboratory, Los Alamos, New Mexico,

United States of America ; Microbial and Metagenome Program, Joint Genome

Institute, Walnut Creek, California, United States of America.


The human body consists of innumerable multifaceted environments that predispose

colonization by a number of distinct microbial communities, which play

fundamental roles in human health and disease. In addition to community surveys

and shotgun metagenomes that seek to explore the composition and diversity of

these microbiomes, there are significant efforts to sequence reference microbial

genomes from many body sites of healthy adults. To illustrate the utility of

reference genomes when studying more complex metagenomes, we present a

reference-based analysis of sequence reads generated from 55 shotgun metagenomes,

selected from 5 major body sites, including 16 sub-sites. Interestingly, between

13% and 92% (62.3% average) of these shotgun reads were aligned to a

then-complete list of 2780 reference genomes, including 1583 references for the

human microbiome. However, no reference genome was universally found in all body

sites. For any given metagenome, the body site-specific reference genomes,

derived from the same body site as the sample, accounted for an average of 58.8%

of the mapped reads. While different body sites did differ in abundant genera,

proximal or symmetrical body sites were found to be most similar to one another.

The extent of variation observed, both between individuals sampled within the

same microenvironment, or at the same site within the same individual over time,

calls into question comparative studies across individuals even if sampled at the

same body site. This study illustrates the high utility of reference genomes and

the need for further site-specific reference microbial genome sequencing, even

within the already well-sampled human microbiome.


DOI: 10.1371/journal.pone.0084963

PMCID: PMC3893169

PMID: 24454771  [PubMed - indexed for MEDLINE]






16s rRNA Sequencing with MR DNA

16S ribosomal  (rRNA) sequencing using next generation sequencing is a method used to identify and compare bacteria and archaea present within almost any type of sample. 16S rRNA gene sequencing is a well-established method for studying phylogeny and taxonomy of samples from complex microbiomes or environments that are difficult or impossible to study.





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