1. Introducing DOTUR, a Computer Program for Defining Operational Taxonomic Units and Estimating Species Richness Patric D. Schloss and Jo Handelsman Department of Plant Pathology, University of Wisconsin-Madison APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Mar. 2005 Presenter: Mingjie Wang

2. The Schloss Lab http://schloss.micro.umass.edu/

3. What is in there Statistical approaches for quantifying and comparing the number and composition of lineages in microbial communities are lacking. (species richness)

4. Species richness estimation Based on 16S rRNA gene sequences Grouped as Operational taxonomic units (OTUs)/(Phylotypes) Defined by Electrophoretic pattern DNA sequence Nucleotide sequence: 97%, 95%, 80%

5. Phlip L. Bond. et al. Bacterial Community Structures of Phosphate-Removing and Non- Phosphate-Removing Activated Sludges from Sequencing Batch Reactors. Applied and Environment Microbiology, 1995 OTU determined by DNA sequence

6. Electrophoretic pattern Larry J. Forney et al. Characterization of Microbial Diversity by Determining Terminal Restriction Fragment Length Polymorphisms of Genes Encoding 16S rRNA. Applied and Environment Microbiology, 1997 Restriction fragment length polymorphism (RFLP) analysis of 16S rDNA of a six-member bacterial model community corresponding to HhaI digestion

7. General flowchart ClustalWPHYLIP DOTUR Sequence Alignment Sequence assignment at every possible distance. etc. Distance matrix generated (input for DOTUR)

8. Clustering algorithms Nearest neighbor (NN): Each of the sequences within an OTU are at most X% distant from the most similar sequence in the OTU Furthest neighbor (FN): All of the sequences within an OTU are at most X% distant from all of the other sequences within the OTU Average neighbor (AN): A middle ground between the other two algorithms

9. DOTUR makes appropriate sequence assignment NN: nearest neighbor assignment algorithm AN: average neighbor assignment algorithm FN: furthest neighbor assignment algorithm n1: no. of singletons; n2: no. of doubletons; etc.

10. Lineage-through-time plots by DOTUR

11. Application of DOTUR Construction of rarefaction and collector’s curves, Shannon’s and Simpson’s diversity index, ACE, and Chao1, Jackknife, and Bootstrap richness estimators

12. Rarefaction curves

13. Richness comparison between two Soil samples using DOTUR Scottish soilAmazonian soil

14. Richness comparison between two soil samples using DOTUR Result: The number of observed OTUs from the Amazonian soil falls within the 95 confidence interval (CI) of the Scottish soil with 98 sequences sampled Conclusion: The two samples have the same level of richness.

15. Application of DOTUR to the Sargasso Sea metagenome sequence 16S rDNArpoB gene

16. Question What is the expected number of OTUs in a microbial community? How to determine the minimum number of sequences to estimate the overall OTUs?

17. Chao1 richness estimation DOTUR could give the full bias corrected Chao1 richness estimates as described by Chao and modified by Colwell (http://viceroy.eeb.uconn.edu/estimates)http://viceroy.eeb.uconn.edu/estimates

18. Construction of collector’s curves using Chao1 richness estimator 16S rDNArpoB gene

19. Summary DOTUR assigns sequences accurately and consistently to OTUs for every distance level. DOTUR can be used to tell the relative richness between two communities by generating rarefaction curves. DOTUR can be used to compare different phylogenetic anchors for measuring richness.

20. Summary (cont.) DOTUR can generate collector’s curves that help determine the minimum number of sequences to estimate the overall OTUs.