Convenience Sample of 4 Adults and 6 Infants. Adults 4 visits over 2 weeks; infants 2 visits over 2 weeks Adult specimens: 1) plaque (by method, teeth,

Slides:



Advertisements
Similar presentations
Lab 1: Using data output from Qiime, transformations, quality control
Advertisements

16S sequencing for microbiome studies Nicola Segata and Nick Loman
Clostridium difficile Colitis or Dysbiosis. Symbiostasis/Dysbiosis.
Forecasting Using the Simple Linear Regression Model and Correlation
Metagenomic investigation of the intestinal microbiome in healthy and diarrheic horses M. COSTA 1, A. STURGEON 1, L. G. ARROYO 2, H. R. STAEMPFLI 2, J.
+ Wrap up and future studies October 1st, Outcome: this could not have been more successful.
Use of the genomic data o Reconstruction of metabolic properties o Nature’s Microbiome o NGS in Population Genetics.
Metabarcoding 16S RNA targeted sequencing
Metagenomics. What is metagenomics? Term first used in 1998 by Jo Handelsman "the application of modern genomics techniques to the study of communities.
Microbiome Analysis from sample to data MGL Users Group June 18, 2014.
1 General Phylogenetics Points that will be covered in this presentation Tree TerminologyTree Terminology General Points About Phylogenetic TreesGeneral.
Characterization of microbial communities in a fluidized-pellet-bed bioreactor by DGGE analysis As an extension of the fluidized pellet bed operation used.
Practical Bioinformatics Community structure measures for meta-genomics István Albert Bioinformatics Consulting Center Penn State.
Little Things Rule the World: Microbial Responses to Oil
The Sorcerer II Global ocean sampling expedition Katrine Lekang Global Ocean Sampling project (GOS) Global Ocean Sampling project (GOS) CAMERA CAMERA METAREP.
High Throughput Sequencing
The Microbiome and Metagenomics
Discussion on Metagenomic Data for ANGUS Course Adina Howe.
Discovery of new biomarkers as indicators of watershed health and water quality Anamaria Crisan & Mike Peabody.
From Metagenomic Sample to Useful Visual Anna Shcherbina 01/10/ Anna Shcherbina Bioinformatics Challenge Day 02/02/2013 From Metagenomic Sample to.
H = -Σp i log 2 p i. SCOPI Each one of the many microbial communities has its own structure and ecosystem, depending on the body environment it exists.
Species  OTUs  OPUs  Species  OTUs  OPUs. Rosselló-Mora & Amann 2001, FEMS Rev. 25:39-67 Taxa circumscription depends on the observable characters.
Accurate estimation of microbial communities using 16S tags Julien Tremblay, PhD
Identify gene markers for different taxonomic groups in Archaea and Bacteria Genomes Dongying Wu 1,2, Jonathan A. Eisen 1,2 1. DOE Joint Genome Institute,
Figure S1 The North Sea beach of the Dutch barrier island of Schiermonnikoog (N53°30’ E6°10’). The transect indicates the chronosequence along the developing.
How will new sequencing technologies enable the HMP? Elaine Mardis, Ph.D. Associate Professor of Genetics Co-Director, Genome Sequencing Center Washington.
Current Challenges in Metagenomics: an Overview Chandan Pal 17 th December, GoBiG Meeting.
Microbial biomass and community composition of a tallgrass prairie soil subjected to simulated global warming and clipping A. Belay-Tedla, M. Elshahed,
Elucidating factors behind pair wise distances discrepancies between short and near full-length sequences. We hypothesized that since the 16S rRNA molecule.
Analyzing Time Course Data: How can we pick the disappearing needle across multiple haystacks? IEEE-HPEC Bioinformatics Challenge Day Dr. C. Nicole Rosenzweig.
Aim The aim of this study was to gain insight into the microbial diversity of the stool of infants with intestinal failure due to surgical resection from.
The Microbiome and Metagenomics
Compositionality and Sparseness in 16S rRNA data Anthony Fodor Associate Professor Bioinformatics and Genomics UNC Charlotte.
Accurate estimation of microbial communities using 16S tags
No reference available
Statistical Analysis for Expression Experiments Heather Adams BeeSpace Doctoral Forum Thursday May 21, 2009.
The microbial world S. Cerevisiae (yeast) Mycobacterium tuberculosis.
Canadian Bioinformatics Workshops
Canadian Bioinformatics Workshops
Canadian Bioinformatics Workshops
Presented by Samuel Chapman. Pyrosequencing-Intro The core idea behind pyrosequencing is that it utilizes the process of complementary DNA extension on.
Date of download: 6/23/2016 Copyright © 2016 McGraw-Hill Education. All rights reserved. Pipeline for culture-independent studies of a microbiota. (A)
Discussion on Genomic/Metagenomic Data for ANGUS Course Adina Howe.
Date of download: 7/7/2016 Copyright © 2016 McGraw-Hill Education. All rights reserved. Pipeline for culture-independent studies of a microbiota. (A) DNA.
Soil Microbiome of Native and Invasive Marsh Grasses in Blackbird Creek, Delaware Lathadevi K.Chintapenta 1#, Gulnihal Ozbay 1#, Venu Kalavacharla 1* Figure.
Robert Edgar Independent scientist
16S rRNA Experimental Design
Simon v RNA-Seq Analysis Simon v
Quantitative Phylogenetic Assessment of Microbial Communities in Diverse Environments Xinjun Zhang.
454 GS FLX Ion Torrent PGM Illumina MiSeq DNA Input
Metagenomics: From Bench to Data Analysis 19-23rd September S rRNA-based surveys for Community Analysis: How Quantitative are they? Dr.
Microbiome 16S analysis Morgan G. I. Langille, PhD Assistant Professor
Micelle PCR reduces artifact formation in 16S microbiota profiling
MGmapper A tool to map MetaGenomics data
Peter Sterk EBI Metagenomics Course 2014
Environmental Biochemistry University of Oldenburg Fremantle, 2013
Microbiome: 16S rRNA Sequencing
VISUALIZING COMPLEX BACTERIAL POPULATIONS IN ANIMAL MODELS
H = -Σpi log2 pi.
Experimental design for high‐throughput characterization of synthetic human gut microbiome consortia Experimental design for high‐throughput characterization.
Volume 137, Issue 2, Pages (August 2009)
Mukoye B., Mangeni B. C., Ndong’a M. F. O. and Were H. K.
Volume 21, Issue 8, Pages (August 2014)
Inference of Environmental Factor-Microbe and Microbe-Microbe Associations from Metagenomic Data Using a Hierarchical Bayesian Statistical Model  Yuqing.
Genetic Determinants of the Gut Microbiome in UK Twins
(a) PCoA of the abundance of unique OTUs per sample from the 16S marker gene sequencing data from the AGP data repository (small spheres) and the San Diego.
Example usage of mockrobiota MC resource for marker gene and metagenome sequencing pipelines. Example usage of mockrobiota MC resource for marker gene.
by Peter J. Turnbaugh, Vanessa K. Ridaura, Jeremiah J
Beta-diversity analyses of microbial taxa recovered from ATM keypads.
Toward Accurate and Quantitative Comparative Metagenomics
Presentation transcript:

Convenience Sample of 4 Adults and 6 Infants. Adults 4 visits over 2 weeks; infants 2 visits over 2 weeks Adult specimens: 1) plaque (by method, teeth, and media) 2) saliva (by media & storage temperature) Infant Specimens: 1) plaque (by storage temperature & number of teeth) 2) saliva (by storage temperature) 3) gum (by storage temperature) Adult plaque have biological replicates Adult saliva are technical replicates All Infant specimens stored in Omnigene MethodsConclusions Contact & Support Supported by NIDCR R01-DE PIs: Marazita [U PITT]; McNeil [West Virginia U]; Foxman [U of Michigan] Validation of Specimen Collection Methods for 16S Oral Microbial Community Analysis Ting Luo 1, Usha Srinivasan 1, Kirtana Ramadugu 1, Kerby Shedden 1, Erika Trumble 1, Jiean Li 1, Katherine Neiswanger 2, Richard Crout 2, Daniel McNeil 2, Robert Weyant 3, Mary L. Marazita 3, Betsy Foxman 1 1 University of Michigan, 2 West Virginia University, 3 University of Pittsburgh Poster Presented at the International Association for Dental Research conference Boston, MA, USA; March, Introduction and Research Questions The effects of different specimen collection, media and storage conditions on the recovery of bacterial DNA for exploring the oral microbiome have not been examined in detail. 16S metagenomics requires recovery of high quality sequences in large abundances for accurate characterization of the oral microbiome. Our objective was to validate various specimen collection methods for adequate bacterial DNA recovery for Illumina sequencing and 16S metagenomic analyses. Results Introduction and Research Questions Study Population & Sample Collection Design Barcoded PCR Fastq files Preprocessing (remove barcodes, Primers and quality scores) Pick Open Reference OTUs (Uclust) Reference based clustering w/ CORE dataset (RDP Classifier) Sequence Alignment (PyNast) Beta Diversity & Normalized Counts (Weighted UniFrac, Euclidean & Nonmetric Distances) Variance Component Model (Linear mixed effects regression) Import Prune/Subset Data Inference Validation Graphics Library generation Sample DNA Extraction (Qiacube®) Illumina Sequencing QIIME Upstream Pipeline Alpha Diversity & Boostrapping (sequencing depth, Observed OTUs) Sample preparation, Sequencing and analysis pipeline Barcode to Sample Sample to Metadata Primers to Sample Relative Abundance & Unrarefied Data (Phyla Level, Wald Negative Binomial Testing) 1)16S rRNA amplified using 8 base pair error-correcting barcodes with conserved primers flanking the V6 region 2)Amplicons from each sample pooled and sequenced with Illumina HiSeq Platform (100-cycle paired end reads) 208,364,761 raw mate pairs generated 202,312,951 mate pairs successfully joined by FLASH 171,758,509 joined reads demultiplexed and passed quality filtering # of reads mapped to a sample ranged from 240 – 9,533, /152 samples have over 10,000 reads 3) Processed reads fed into QIIME pick open reference OTU workflow 217,308 OTUs picked, 749 above.005% relative abundance 4) Rare OTUs (<.005% relative abundance) filtered and resultant OTU table imported into Phyloseq with metadata OTU Table Taxonomy Table Phylogenetic Tree Reference Sequences Phyloseq Upstream Pipeline Adult PlaqueAdult Saliva VisitMediaMethodVisitMediaMethodStorage 1LDTMScaler (17, 26) molars1OmnigeneSubject Spitting-20C 1LDTMScaler (34, 45) premolars1OmnigeneSubject SpittingRT for 2 days 1OmnigeneScaler (36, 47) molars1OmnigeneSubject SpittingRT for 5 days 1OmnigeneScaler (15, 24) premolars1OmnigeneSubject SpittingRT for 7 days 1LDTMBrush (16, 27) molars1LDTMSubject Spitting-20C 1LDTMBrush (44, 35) premolars1LDTMSubject SpittingRT for 2 days 1OmnigeneBrush (46, 37) molars1LDTMSubject Spitting-80C for 2 days 1OmnigeneBrush (14, 25) premolarsInfant Saliva 2LDTMScaler (17, 26) molars1OmnigeneSwab-20C 2LDTMScaler (34, 45) premolars2OmnigeneSwabRT 2OmnigeneScaler (36, 47) molarsAdult Gum 2OmnigeneScaler (15, 24) premolars1OmnigeneSwab-20C 2LDTMBrush (16, 27) molars2OmnigeneSwabRT 2LDTMBrush (44, 35) premolarsInfant Plaque 2OmnigeneBrush (46, 37) molars1OmnigeneBrush (1 tooth)-20C 2OmnigeneBrush (14, 25) premolars2OmnigeneBrush (1 tooth)RT 3LDTMScaler (36, 37, 26, 27)1OmnigeneBrush (4 teeth)-20C 3LDTMBrush (17, 16, 46, 47)2OmnigeneBrush (4 teeth)RT 4OmnigeneScaler (36, 37, 26, 27) 4OmnigeneBrush (17, 16, 46, 47) Scaler vs. Cytobrush Omnigene vs. LDTM 3) Do different storage temperatures affect bacterial DNA recovery from saliva? 4) Are bacterial communities in plaque reflected in the saliva for adults? 5) Are bacterial communities in plaque reflected in the gum and/or saliva for infants? Omnigene recovered more taxa than LDTM Bacterial communities are similar for scalar and cytobrush Omnigene had advantages over LDTM in terms of convenience and sensitivity to storage conditions Recovery was similar by scaler or cytobrush The number of taxa recovered varies by specimen Adult Plaque Actinobacteria Bacteroidetes Firmicutes Fusobacteria OtherProteobacteria Spirochaetes TM7 Random EffectsVariance Replicate: Participant Replicate Residual Fixed Effects Estimate (t-value) Estimate Intercept12.7(3.9)7.8(3.1)38.5(21.0)1.4(3.1)2.2(2.4)37.2(14.1)0.052(3.117)0.151(3.159) Omnigene7.3(2.7)9.0(4.4)-7.7(-5.2)0.3(1.1)0.1(0.1)-9.2(-3.8)0.024(1.865)0.093(2.816) Scaler-2.8(-1.0)0.3(0.1)1.0(0.7)-0.3(-1.0)1.6(2.5)0.3(0.1)-0.008(-0.620)-.022(-.658) Pooled Plaque-0.9(-.3)2.7(1.0)1.5(.8)0.5(1.5)-1.0(-1.2)-2.8(-0.9)-0.017(-1.030)0.010(0.223) Premolar Plaque3.8(1.3)-1.4(-0.6)-1.6(-1.0)0.1(0.2)0.2(0.3)-0.9(-0.3)-0.030(-1.973)-.065(-1.771) Infant Samples Random EffectsVariance Participant Residual Fixed Effects Estimate (t-value) Estimate Intercept10.5(3.7)25.1(9.6)30.2(8.8)2.0(4.0)2.8(3.7)29.3(7.8)0.044(4.175)0.172(4.424) Plaque From 1 Tooth1.7(0.5)-7.2(-2.2)4.5(1.0)-0.3(-0.5)0.8(0.9)0.5(0.1)-0.002(-0.116)-.001(-.028) Plaque From 4 Teeth5.0(1.5)-7.8(-2.3)-3.4(-0.8)-0.1(-0.1)-1.5(-1.6)7.8(1.6)0.003(0.214)0.024(0.485) Infant Saliva1.0(0.3)-8.4(-2.5)5.4(1.2)-0.4(-0.7)-1.9(-2.1)4.4(0.9)-0.033(-2.461)-.104(-2.182) Storage at -20C -2.1(-0.9)-6.9(-2.8)6.0(1.9)-0.1(-0.2)-0.9(-1.3)4.0(1.2)-0.010(-1.048)-.072(-2.097) Bi-variate results confirmed after taking into account random and fixed effects 1) Do dental scalers recover different bacterial communities from plaque than cytobrushes? 2) Do the bacterial communities recovered differ by storage media? Bacterial communities recovered differ among plaque, saliva and gum, and media Omnigene was less sensitive to storage conditions Number of taxa recovered depended on specimen sampled