1. Sampling microbial diversity using fragment analysis: When is an OTU an ESU?

2. Patterns of microbial diversity and community composition What factors regulate community diversity and composition? How do humans influence microbial communities? Does microbial diversity change along environmental gradients? Do communities from different locations (treatments) differ? Are there patterns of community structure?

3. Sequence based diversity estimates which gene? how much to sequence? how to define OTUs? (95%, 97%, 99%--non transitive relationships) What are we measuring? Non-sequence based diversity estimates tRFLP, ARISA, SNPs, AFLP Often quick, cheap, easy Only a proxy for actual sequence diversity present For tRFLP, ARISA one peak = 1 OTU (or does it?) Operational Taxonomic Units? Species? Ecotypes?

4. Evolutionarily Significant Unit Compare OTUs to ESUs

5.  GGCC CCGG GGCC CCGG GGTC CCAG GGCC CCGG GG CC CC GG GG CC CC GG  GGTC CCAG GG CC CC GG Type AType B Separate by size Smaller fragments Type AType Bmarkers 1000 bp 500 bp 750 bp 250 bp Restriction Fragment Length Polymorphisms

6. MIT9303 SS120 MIT9211MIT9313 MIT9312 MIT9302 MIT9202MIT9201MIT9215 MED4 1500 bp 100 bp 1000 bp 500 bp high B/Alow B/A RsaI digests of the ITS-23S rRNA distinguish Prochlorococcus ecotypes RFLPs of individuals

7. t-RFLP= terminal Restriction Fragment Length Polymorphism Use 1 Fluorescently labeled primer in PCR Digest with restriction enzyme  Run fragments on gel—Visualize using fluorescence detector markers Type A Type B 1000 bp 500 bp 750 bp 250 bp Only bands containing fluorescent primer are seen

8. Relative Fluorescence Units DNA (bp) Each sequence in pool represented by single peak (barring incomplete digestion issues) Each peak treated as OTU What is the level of sequence diversity within a peak? DEPENDS…..

9. Based on length differences in rRNA intergenic spacer ARISA---Automated Ribosomal Intergenic Spacer Analysis Fisher and Triplett AEM 1999 16S rRNA23S rRNA

10. Rocap et al 2002 AEM Intergenic spacer lengths can be variable at fine phylogenetic scales

11. Strategy: Amplify intergenic spacer using primers (universal or group specific) targeted to conserved positions in rRNA genes ARISA---Automated Ribosomal Intergenic Spacer Analysis 16S rRNA23S rRNA Separate by size Smaller fragments markers 1000 bp 500 bp 750 bp 250 bp sample or DNA (base pairs) Relative fluorescence units (RFUs)

12. Community analyses Richness - how many? Does richness vary with the environment? Community A B C 0 10 20 30 40 50 60 0102030 Salinity (PSU) OTUs Regression R 2 = 0.96 p = 0.0019 What can we do with these OTUs? Treat each OTU as a “taxonomic unit of richness”

13. Community Analyses Community A B C Incidence matrixSimilarity matrix 2a 2a + b + c X 100 where a = # OTUs in both b = # OTUs in X only c = # OTUs in Y only Sorensen similarity coefficient

14. Community analyses Community composition - who? Does composition vary with the environment? Community A B C Pasture composition differed from forest & plantation composition (p<0.001). Analysis of Similarity (ANOSIM & NMDS) Carney et al. (2004) Ecology Letters

15. The sample set: active and inactive carbonate chimneys Young, hot, actively chimneys: 40-85ºC, pH 9-11 Old chimneys with little or no venting: <10ºC, pH 8 Chimney containing minerals exposed to both hot fluids and background SW Brazelton et al. 2006

16. Ecological succession of Lost City Archaea (WJ Brazelton, 2006)

17. 120 150 160 170 190 142 RFU’s DNA (BP) Fluorescent size standard Fluorescently labelled PCR product What size is a peak anyway?

18. 210.0 167.8 233.2 ?

19. Diffusive spread of larger peaks

20. Solutions? Thresholds for peak calling-- signal:noise cutoff % area or % peak height cutoff helps to standardize amount of DNA loaded onto gel (ie 10ng) Binning-- at minimum data must be binned in 1bp bins so 233.2 and 233.3 are counted as the same fragment typically 1-3 bp bins < 500 bp 3-5 bp 500-1000 bp 10 bp > 1000 bp

21. Hewson and Fuhrman 2006 Microbial Ecology Use maximal similarity between two samples to address null hypothesis that communities are different Iterative binning strategy

22. T-RFLP specific issues : which enzymes to pick? How many to use? Engebretson and Moyer, 2003 AEM In silico analysis of 4603 bacterial SSU rRNA sequences and 18 common REs

23. But what if……?  You already have a clone library from the same/related environment  You are using group specific primers to differentiate subtypes of interest  You are using a locus other than the SSU rRNA (functional gene, ITS etc….) Then how do you choose enzymes?

24. REPK: Restriction enzyme picker Collins and Rocap, 2007 NAR http://rocaplab.ocean.washington.edu/tools/repk Rationally chooses enzymes that discriminate user-defined sequence groups

25. REPK: Restriction enzyme picker http://rocaplab.ocean.washington.edu/tools/repk

26. REPK: Output Terminal fragment lengths of all sequences with all enzymes

27. REPK: Output http://rocaplab.ocean.washington.edu/tools/repk Visual view of which enzymes are capable of distinguishing each user-defined group

28. REPK: Output http://rocaplab.ocean.washington.edu/tools/repk Enzymes are binned together based on their ability to discriminate groups

29. REPK: Final Output http://rocaplab.ocean.washington.edu/tools/repk Sets of enzymes that together can distinguish all user defined sequence groups

30. Automated Ribosomal Intergenic Spacer in silico Analysis (ARISISA) 355 complete bacterial genomes in GenBank Wrabel and Rocap

31. Fragment lengths: predominant bacterial phyla Genera/species

32. A single ARISA peak can represent more than one group or species of bacteria. Some groups display minimal overlap. ARISA fragment lengths (bps) Actinobacteria Bacteroidetes/Chlorobi Chlamydiae Cyanobacteria Firmicutes Alpha- Proteobacteria Beta- Delta- Epsilon- Gamma- 70 0 Sequences

33. Intraspecific variability in ARISA peaks due to multiple operons Number of ribosomal operons: 1 – 15 Predicted ARISA peaks per strain: 1 - 9!!

34. Relative fluorescence units (RFUs) DNA (base pairs) Time to play ARISA detective … A B C 01500 A Photobacterium profundum B 2 Prochlorococcus strains, 3 Synechococcus strains. C Colwellia psychrerythraea

35. Intraspecific variability in ARISA peaks due to multiple operons Geobacillus kaustophilus, Photobacterium profundum Vibrio cholerae Colwellia psychrerythraea 7 Prochlorococcus, 7 Synechococcus Number of ribosomal operons: 1 – 15 Predicted ARISA peaks per strain: 1 - 9!!

36. Bacteria associated with the diatom Pseudo-nitzchia Kaczmarska et al. 2005 Harmful Algae

37. Automated Ribosomal Intergenic Spacer Analysis (ARISA) 2 ng 10 ng PCR product, purified gram + bacteria DNA extraction amplify ITS with fluorescent label ITS (variable) 16S 23S run on capillary sequencer with internal size standard DNA (base pairs) Relative fluorescence units (RFUs) 3 µm AB 0.2 µm FLB exponentialstationary

38. Are diatom-associated bacterial assemblages found among field data? P. delicatissima P. pungens Chaetoceros socialis Ditylum brightwellii Thalassiosira sp. Isolates + field filters from 3 stations: P1, P17, P38 YES

39. 19 Pseudo-nitzschia spp. 8 Ditylum brightwellii 2 Thalassiosira sp. 1 Chaetoceros socialis P. calliantha P. cuspidata (tentative ID) P. delicatissima P. multiseries P. pungens C. socialis D.brightwellii Thalassiosira sp. Origins of diatom isolates P. multiseries P. australis, P. fraudulenta

40. Bacterial assemblages differ with Pseudo-nitzschia species. Patterns related to Pseudo-nitzschia species? Null hypothesis: Bacterial assemblages are the same between Pseudo-nitzschia species. R = 1; p = 0.01 Michele Wrabel

41. Conclusions Fragment analysis methods offer a means to interrogate a large number of samples fairly rapidly and inexpensively Ability to ask (and answer!) ecological questions about microbial communities Important to be aware of both the strengths and limitations of the techniques to interpret data correctly

42. Thanks to the F.A.M.O.U.S. gang Billy Brazelton Eric Collins Colleen Evans Clara Fuchsman Claire Horner-Devine Kate Hubbard Andrew Opatkiewicz Jess Silver Michele Wrabel

43. ARISA---Automated Ribosomal Intergenic Spacer Analysis Fisher and Triplett AEM 1999 Partial ARISA profiles of the bacterial communities in Crystal Bog Lake (A), Lake Mendota (B), and Sparkling Lake (C) during the summer of 1998. In each panel, the red and black electropherograms represent duplicate PCRs that were performed on a single sample from each site.