Accurate estimation of microbial communities using 16S tags

Julien Tremblay, PhDjtremblay@lbl.gov

16S rRNA as phylogenetic marker gene

Escherichia coli 16S rRNA

Primary and Secondary Structure

70S Ribosome

subunits

30S

50S

34 proteins

21 proteins

5S rRNA

23S rRNA

16S rRNA

Falk Warneckehighly conserved between different species of bacteria and archaea

16S rRNA in environmental microbiology(Sanger clone libraries)

Falk Warnecke

900-1100 bp length

Next generation sequencing (NGS)Illumina454

10-350M 150bp reads/lane$

0.5M 450bp reads$$

Rea

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eng

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Throughput and cost

Illumina tags (itags)

• 454 = “1” read• Illumina = “2” reads => have to be assembled

• Both reads need to be of good quality

ACGTGGTACTACGTGAT….

~400 bp

AC

GT

GG

TA

CT

AC

GT

GA

TA

GT

GT

AT

~250 bp

454 Illumina

Game plan to survey microbial diversity

V1 V2 V3 V4 V5 V6 V7 V8 V916S rRNA

Reduce dataset bydereplication/clustering

X 10,000X 800X 1,200X 200

X 2,000X 1,000X 1X 10

Identification(BLAST, RDP classifier)

Generate amplicons of agiven variable regionfrom bacterial community(many millions of sequences) Why amplicon tags ?

Deeper, cheaper, faster

Rare biosphere

Rank

Abun

danc

e

Rare biosphere

Sequencing error? Chimeras? Background noise?High abundance

Low abundance

High sequencing depth of NGS reveals “rare” OTUs

Lots of reads only present once in sample…

Rare bias sphere?

Control experiment: estimate rare biospherein a single strain of E.coli

27F 342R 1114F 1392R

Is rare biosphere an artifact of the NGS error?

V1 & V2 V8

Kunin et al., (2009), Environ. Microbiol.

Should not be a sequencing artifact, if relatively stringent clustering parameters are applied

Subject to controversy – Is rare always real?

Quince et al., (2009), Nat. Methods

Illumina tags (itags)

• Typical 454 run 450,000 – 500,000 reads• “Typical” Illumina run:

• GAIIx 10,000,000 – 40,000,000 reads/lane• Hiseq ~ 350,000,000 reads/lane• Miseq (new) ~8,000,000 reads/lane

• Move 16S tags sequencing to Illumina platform• HiSeq = huge output compared to 454 (suitable for big

projects 1000+ indexes(barcodes)/libraries• MiSeq = moderatly high throughput (More suitable)

• throughput more efficient clustering algorithm (SeqObs).

16S tags clustering

Edward Kirton, JGI

Number of reads >> number of clusters

I llumina rRNA Amplicon Sequencing

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RAW BARCODE OVERLAP ASSEM CLUSTERS

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Edward Kirton, JGI

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Validation of 16S tags on MiSeq • Quality is superior in MiSeq

454 MiSeq reads 1 and 2 separately

MiSeq reads 1 and 2 assembled

MiSeq validation

• Exploratory experiments using 11 wetlands samples.

• Validate reproducibility between runs

MiSeq validation

• Beta diversity (UniFrac Distances)Run 1 Run 2

MiSeq validation• What are the gains using MiSeq assembled paired-end reads

over 454 reads?

• Average bootstrap value for all clusters at every tax level.

Aver

age

boot

stra

p va

lue

Taxonomic level

454 clusters shows higher confidence than MiSeq clusters

Better quality in MiSeq reads, but lower read lengths

Comparing 454 with MiSeq• What are the gains using MiSeq assembled paired-

end reads over 454?Clusters having > 0.50 bootstrap value

For instance, ~310,000 reads made it to the class level

MiSeq outperforms 454 in terms of read depth

itags – rare OTUs

Low abundant reads consistently shows low confidence inClassification.Low abundant reads = errors, artifacts?Low abundant reads are underrepresented in databases?

MiSeq wetlands test samples

Comparing 454 with illumina

• Compare runs of 454 and MiSeq of same sample• Although challenge to compare V4 with V6-8 region.

~291 bp

515 806 926 1392

~466 bp

Comparing 454 with illumina

• Primer pair of variable region is likely to affect outcome of results.

In silico PCR on 16S Greengenes database.

PyroTagger (for 454 amplicons)

Unzip, validate

Remove low-quality reads

Redundancy removal

PyroClust & Uclust

Remove chimeras

Samples comparison,post-processing

pyrotagger.jgi-psf.org

Classification and barcode separation

• Sequences of cluster (OTU) representatives

• Blast vs GreenGenes and Silva databases, dereplicated at 99.5%

• Distribution of microbial phyla in the dataset

• Also see the Qiime pipeline

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10GP1 1PS1 1PS2 2A?1

Proteobacteria Metazoa Firmicutes Bacteroidetes Spirochaetes

1 2 3 4 5 6 % identityAlignment LengthMismatches Gaps Query StartQuery EndHit StartHit End E-value Score ID Full Name TaxonomyCluster1 6732 1 267 7 14532 97.7 345 8 0 1 345 1336 992 1.00E-176 620 among geographically regions central Tibet geothermal spring mat clone DTM42210319 Bacteria Firmicutes Clostridia ClostridialesCluster2 1 3464 322 1981 1 9372 98.8 345 4 0 1 345 1247 903 0 652 Microbial consortia fermentor methanogenic bioreactor clone EBR-02E-0436134800 Bacteria Firmicutes Clostridia Clostridiales CoprococcusCluster3 6303 1 2330 7 726 100 345 0 0 1 345 1345 1001 0 684 Bacteroides sp. str. 253c73683 Bacteria Bacteroidetes Bacteroidetes (class)Bacteroidales BacteroidaceaeBacteroidesCluster4 4464 58 2750 2153 97.7 345 8 0 1 345 1338 994 1.00E-176 620 Geobacillus sp. D195366419 Bacteria Firmicutes Bacillales Bacillaceae GeobacillusCluster5 8836 4 5052 7 266 99.7 345 1 0 1 345 1382 1038 0 676 Electricigen Enrichment MFC full-scale anaerobic bioreactor sludge treating brewery waste clone 31f06226581 Bacteria Bacteroidetes Bacteroidales BacteroidaceaeCluster7 4218 530 2304 1 4690 99.1 345 1 1 1 345 1273 931 0 654 Thermoanaerobacterium saccharolyticum str. B6A356922 Bacteria Firmicutes Clostridia ThermoanaerobacteralesThermoanaerobacterales Family III. Incertae SedisCluster8 2628 55 7769 99.7 345 1 0 1 345 1151 807 0 676 Portuguese dry smoked sausages (chouricos) type Ribatejano isolate str. Te16R100979 BacteriaCluster9 1111 88 8102 13 96.5 345 10 2 1 345 1365 1023 3.00E-162 573 Clostridium stercorarium str. DSM 8532T31278 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae ClostridiumCluster10 1 648 12 1358 2837 93.3 345 23 0 1 345 1288 944 8.00E-141 502 packed-bed reactor clone CFB-4204245 Bacteria Firmicutes ClostridiaCluster13 1737 1 128 115 3971 11 100 345 0 0 1 345 1388 1044 0 684 Bacillus circulans str. X3345413 Bacteria Firmicutes Bacillales Bacillaceae BacillusCluster15 2676 1 467 2885 2 98.8 345 4 0 1 345 1277 933 0 652 mesophilic anaerobic BSA digester clone BSA1B-05107466 Bacteria Firmicutes ClostridiaCluster17 4706 663 104 153 100 345 0 0 1 345 1326 982 0 684 Bacillus sp. str. SL177336159 Bacteria Firmicutes Bacillales Bacillaceae BacillusCluster18 828 1 1629 29 118 96.8 347 9 1 1 345 1359 1013 8.00E-169 595 Actinobaculum sp. P1 str. P2P_1983011 Bacteria ActinobacteriaActinobacteridaeActinomycetalesActinomycineaeActinomycetaceaeCluster19 1353 23 388 960 99.4 345 2 0 1 345 1245 901 0 668 Guguan hot spring isolate str. K1L1103882 Bacteria Firmicutes ClostridiaCluster20 2303 2 378 3214 100 345 0 0 1 345 1351 1007 0 684 Clostridium cellulosi16059 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae ClostridiumCluster21 1446 147 2777 97.7 345 7 1 1 345 1362 1019 3.00E-174 613 Clostridiaceae bacterium SN021217060 Bacteria Firmicutes Clostridia ClostridialesCluster22 4062 138 8319 99.1 345 3 0 1 345 1261 917 0 660 Clostridiaceae str. 80Wc28479 Bacteria Firmicutes Clostridia ClostridialesCluster23 2593 722 3 5204 98.3 345 6 0 1 345 1375 1031 0 636 intestinal that activate dietary lignan secoisolariciresinol diglucoside human feces isolate ED-Mt61/PYG-s6anaerobic str. ED-Mt61/PYG-s6142216 BacteriaCluster24 1098 1 1354 43 1065 100 345 0 0 1 345 1356 1012 0 684 Klebsiella pneumoniae str. FIUMS1358763 Bacteria ProteobacteriaGammaproteobacteriaEnterobacterialesEnterobacteriaceaeKlebsiellaCluster29 150 1321 12 1 100 345 0 0 1 345 1378 1034 0 684 Pseudomonas indica38217 Bacteria ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaeCluster31 1203 479 4 28 97.1 345 10 0 1 345 1274 930 8.00E-172 605 Clostridium sp. str. IMSNU 40011102328 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae ClostridiumCluster33 86 247 98 1680 28 86 96.8 345 11 0 1 345 1347 1003 2.00E-169 597 Symbiobacterium sp. str. KA13344098 Bacteria Firmicutes Clostridia Clostridiales Clostridiales Family XVIII. Incertae SedisCluster34 1079 322 7 139 100 345 0 0 1 345 1376 1032 0 684 human fecal clone SJTU_G_05_26204458 Bacteria ProteobacteriaGammaproteobacteriaBetaproteobacteriaCluster35 625 165 1 2470 1 96.8 345 11 0 1 345 1366 1022 3.00E-159 563 on -Arctic peninsula Svalbard Norway determined genes and rumen isolates reindeer fed pelleted concentrates (RF-80) clone AF11153291 Bacteria Firmicutes Clostridia Clostridiales RF30 RF6Cluster41 772 378 19 96.8 345 11 0 1 345 1379 1035 2.00E-169 597 human fecal clone SJTU_C_03_72204117 Bacteria Bacteroidetes BacteroidalesCluster44 353 6 1436 98.8 346 3 1 1 345 1348 1003 0 646 Clostridium jejuense str. HY-35-12T104447 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae ClostridiumCluster50 347 4 64 17 592 3 100 345 0 0 1 345 1382 1038 0 684 Enterococcus casseliflavus str. eS852312359 Bacteria Firmicutes LactobacillalesEnterococcaceaeEnterococcusCluster53 354 33 1 543 100 345 0 0 1 345 1334 990 0 684 Clostridium sp. str. BG-C66357585 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae ClostridiumCluster67 490 2 758 97.7 345 8 0 1 345 1372 1028 1.00E-176 620 mesophilic anaerobic digester clone G35_D8_H_B_E11222733 Bacteria Firmicutes Clostridia Clostridiales

Clostridiaceae

PrevotellaceaeThermoanaerobacterium

Peptostreptococcaceae

ActinobaculumThermoanaerobacteriales

ClostridiaceaeClostridiaceae

Pseudomonas

SymbiobacteriumSJTU_B_02_45

Bacteroidaceae

Challenges

• Short size of amplicon• What filtering parameters to use (stringency level)?

• balance between stringency filter and keeping as much data as we can

• Whole new dimension for rare biosphere?• Handling large numbers of sample (tens of

thousand magnitude)• Sequencing run is fast, but library preparation time

is long.• Cost of barcoded primers (will need lots of

barcodes), handling. • Huge ammount of samples statistics models…

Acknowledgments

• Susannah Tringe• Edward Kirton• Feng Chen• Kanwar Singh• Alison Fern• And many others!

Thanks!

16S rRNA

Dangl lab, UNC