Phylogenomics and the diversification of microbes: JA Eisen at UCSF 2/17/11
Download as KEY, PDF4 likes1,733 views
This document summarizes a talk on phylogenomics and the diversity and diversification of microbes. The talk discussed several topics: 1) It introduced phylogenomics and described how limited sampling of microbial diversity has been from rRNA studies. 2) It discussed examples of mechanisms of novelty originating from within genomes, such as UV repair mechanisms in H. volcanii compared to E. coli. 3) It outlined how phylogenomic methods can be used to infer the likely functions of genes of interest by identifying homologs, aligning sequences, constructing gene trees, and overlaying known functions onto the tree. However, these methods may not work as well for very recently evolved functions. 4) It
Phylogenomics and the diversification of microbes: JA Eisen at UCSF 2/17/11
- 1. Phylogenomics and the Diversity and Diversification of Microbes Jonathan A. Eisen UC Davis UCSF Talk February 17, 2011
- 3. Phylogenomics of Novelty Mechanisms of Origin of New Functions
- 4. Phylogenomics of Novelty Mechanisms of Variation in Origin of New Mechanisms: Functions Patterns, Causes and Effects
- 5. Phylogenomics of Novelty Mechanisms of Variation in Origin of New Mechanisms: Functions Patterns, Causes and Effects Species Evolution
- 6. Phylogenomics of Novelty Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 7. Outline • Introduction • Phylogenomic Stories – Within genome invention of novelty – Stealing novelty – Communities of microbes – Community service and knowing what we don’t know
- 8. Introduction
- 9. rRNA Tree of Life FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 10. Limited Sampling of RRR Studies FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 11. Limited Sampling of RRR Studies Haloferax Methanococcus Chlorobium Deinococcus Thermotoga FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 12. UV Survival E.coli vs H.volcanii 1 Ecoli vs. Hvolcanii 0.1 0.01 Relative 0.001 Survival 0.0001 1E-05 1E-06 1E-07 0 50 100 150 200 250 300 350 400 UV J/m2 E.coli NR10121 mfd- E.coli NR10125 mfd+ TIGR H.volcanii WFD11
- 13. H. volcanii UV Repair Label 7 - 45J / m2) 0.6 Label5#2 0 J/m2 t0 45 J/m2 t0 45 J/m2 Photoreac. 45 J/m2 Dark 24 Hours 0.4 0.2 0 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 Avg. Mol. Wt.(Base Pairs)
- 15. TIGR Genome Projects Haloferax Methanococcus Chlorobium Deinococcus Thermotoga FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 20. Human commensals
- 22. Phylogenomics of Novelty I Origin of Functions from Within
- 23. From Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 24. Blast Search of H. pylori “MutS” • Blast search pulls up Syn. sp MutS#2 with much higher p value than other MutS homologs • Based on this TIGR predicted this species had mismatch repair • Assumes functional constancy Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 25. Predicting Function • Identification of motifs – Short regions of sequence similarity that are indicative of general activity – e.g., ATP binding • Homology/similarity based methods – Gene sequence is searched against a databases of other sequences – If significant similar genes are found, their functional information is used • Problem – Genes frequently have similarity to hundreds of motifs and multiple genes, not all with the same function
- 26. MutL?? Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.
- 27. Overlaying Functions onto Tree MutS2 Aquae MSH5 Strpy Bacsu Synsp Deira Helpy Yeast Human Borbu Metth Celeg MSH6 mSaco Yeast Human Mouse Arath Yeast MSH4 Celeg Human Arath Human MSH3 Mouse Fly Spombe Yeast Xenla Rat Mouse Yeast Human MSH1 Spombe Yeast MSH2 Neucr Arath Aquae Trepa Chltr DeiraTheaq BacsuBorbu Thema SynspStrpy Based on Eisen, Ecoli Neigo 1998 Nucl Acids MutS1 Res 26: 4291-4300.
- 29. Evolutionary Functional Prediction EXAMPLE A METHOD EXAMPLE B 2A CHOOSE GENE(S) OF INTEREST 5 3A 1 3 4 2B 2 IDENTIFY HOMOLOGS 5 1A 2A 1B 3B 6 ALIGN SEQUENCES 1A 2A 3A 1B 2B 3B 1 2 3 4 5 6 CALCULATE GENE TREE Duplication? 1A 2A 3A 1B 2B 3B 1 2 3 4 5 6 OVERLAY KNOWN FUNCTIONS ONTO TREE Duplication? 1 2 3 4 5 6 1A 2A 3A 1B 2B 3B INFER LIKELY FUNCTION OF GENE(S) OF INTEREST Ambiguous Duplication? Species 1 Species 2 Species 3 1A 1B 2A 2B 3A 3B 1 2 3 4 5 6 ACTUAL EVOLUTION (ASSUMED TO BE UNKNOWN) Based on Eisen, 1998 Genome Duplication Res 8: 163-167.
- 30. Example 2: Recent Changes • Phylogenomic functional prediction NJ * ** V.cholerae VC V.cholerae VC 0512 A1034 V.cholerae VC V.cholerae VC V.cholerae VC A0974 A0068 V.cholerae VC0825 0282 may not work well for very newly V.cholerae VCA0906 V.cholerae VC A0979 V.cholerae VCA1056 V.cholerae VC1643 V.cholerae VC 2161 V.cholerae VCA0923 ** ** V.cholerae VC0514 V.cholerae VC1868 V.cholerae VCA0773 V.cholerae VC1313 evolved functions V.cholerae VC1859 V.cholerae VC 1413 V.cholerae VCA0268 V.cholerae VC A0658 ** V.cholerae VC1405 V.cholerae VC 1298 * V.cholerae V.cholerae VCA0864 VC 1248 V.cholerae VCA0176 V.cholerae VCA0220 ** V.cholerae VC1289 V.cholerae VC1069 A ** V.cholerae VC2439 • Can use understanding of origin of V.cholerae VC967 1 V.cholerae VCA0031 V.cholerae VC 1898 V.cholerae VCA0663 V.cholerae VC0988 A V.cholerae VC0216 V.cholerae VC0449 * V.cholerae VCA0008 V.cholerae VC1406 V.cholerae VC 1535 novelty to better interpret these cases? V.cholerae VC 0840 B.subtilis gi2633766 Synechocystis sp. gi1001299 Synechocystis sp.gi1001300 * Synechocystis sp. gi1652276 * Synechocystis * H.pylori sp. gi1652103 gi2313716 H.pylori 99 gi4155097 **C.jejuni ** C.jejuniCj1190c Cj1110c A.fulgidus gi2649560 A.fulgidus gi2649548 ** B.subtilis gi2634254 • Screen genomes for genes that have B.subtilis gi2632630 B.subtilis gi2635607 B.subtilis gi2635608 B.subtilis ** ** B.subtilis gi2635609 ** gi2635610 B.subtilis E.coli gi2635882 E.coligi1788195 gi2367378 * ** E.coligi1788194 E.coli A1092 gi1787690 V.cholerae VC changed recently V.cholerae VC0098 E.coli gi1789453 H.pylori gi2313186 H.pylori 99 gi4154603 C.jejuni ** C.jejuni Cj0144 Cj1564 C.jejuni ** C.jejuniCj0262c ** Cj1506c H.pylori gi2313163 * H.pylori 99 gi4154575 **H.pylori gi2313179 ** H.pylori 99 gi4154599 – Pseudogenes and gene loss ** C.jejuni Cj0019c C.jejuni C.jejuni Cj0951c Cj0246c B.subtilis gi2633374 T.maritima TM0014 V.cholerae VC V.cholerae VC 1403 A1088 T.pallidum gi3322777 T.pallidum ** T.pallidum gi3322939 gi3322938 ** B.burgdorferi gi2688522 – Contingency Loci T.pallidum gi3322296 B.burgdorferi * T.maritima gi2688521 TM0429 T.maritima **T.maritima TM0918 ** TM1428 T.maritima TM0023 * T.maritima TM1143 T.maritima TM1146 P.abyssi PAB1308 P.horikoshii gi3256846 ** P.horikoshii P.abyssi PAB1336 – Acquisition (e.g., LGT) ** gi3256896 ** **P.abyssi PAB2066 ** P.horikoshii gi3258290 * ** P.abyssi PAB1026 P.horikoshii gi3256884 ** D.radiodurans DRA00354 D.radiodurans DRA0353 ** D.radiodurans ** ** VC DRA0352 V.cholerae 1394 P.abyssi PAB1189 P.horikoshii gi3258414 – Unusual dS/dN ratios ** B.burgdorferi gi2688621 M.tuberculosis gi1666149 V.cholerae VC 0622 – Rapid evolutionary rates – Recent duplications
- 31. RIPPING CATGTACAGCA GTACATGTCGT Galagan et al. Genome CATGTACAGCA GTACATGTCGT sequence reveals CATGTACAGCA significant S GTACATGTCGT underrepresentation of F TATGTATAG ATACATATC recently duplicated genes. TATATATAG A O ATATATATC TATGTATAGTA ATACATATCAT O CH3 CH3 CH3 TATATATAGCA R ATATATATCGT CH3 AU: Fig. 12.30. leg- P FIGURE 12.30. RIPPING. “The repeat-induced point mutation (RIP) process in Neurospora crassa. end from Duplications that occur during the vegetative phase are detected by RIP during the sexual cycle source; re- after fertilization but before the DNA synthesis and nuclear fusion (karyogamy). Duplicated se- place with quences that are longer than ~400 bp (or ~1 kb for unlinked duplications as shown) and sharing an original greater than ~80% nucleotide identity are detected. Numerous C-G to T-A point mutations are in- legend. troduced into both copies (unmutated C-G pairs are shown in blue; mutations are shown in red letters; only a small number of base pairs are shown for clarity). RIP-mutated sequences are fre- quent targets for methylation, which results in transcriptional silencing in Neurospora. In contrast to mammals and plants, methylation is not limited to symmetric sites.”
- 32. Tetrahymena thermophila macronuclear genome project
- 33. Tetrahymena’s two nuclear genomes Micronucleus (MIC) Germline Genome (Silent) 5 pairs of chromosomes Macronucleus (MAC) Somatic genome (Expressed) 250-300 chromosomes @ ~45 copies each
- 35. Tetrahymena Genome Processing • Analogous to RIPPING and heterochromatin silencing • Targets new/foreign DNA not duplicated DNA • Does not limit diversification by duplication Eisen et al. 2006. PLoS Biology.
- 36. Phylogenomics of Novelty II Sometimes, it is easier to steal, borrow, or coopt functions rather than evolve them anew
- 37. rRNA Tree of Life Bacteria Archaea Eukaryotes FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 38. Perna et al. 2003
- 39. Network of Life Bacteria Archaea Eukaryotes Figure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 40. articles Arabidopsis thaliana * * Authorship of this paper should be cited as `The Arabidopsis Genome Iniative'. A full list of contributors appears at the end of this paper .......................................................................................................................................................................................................................................................................... . . The ¯owering plant Arabidopsis thaliana is an important model system for identifying genes and determining their functions. Here we report the analysis of the genomic sequence of Arabidopsis. The sequenced regions cover 115.4 megabases of the 125-megabase genome and extend into centromeric regions. The evolution of Arabidopsis involved a whole-genome duplication, followed by subsequent gene loss and extensive local gene duplications, giving rise to a dynamic genome enriched by lateral gene transfer from a cyanobacterial-like ancestor of the plastid. The genome contains 25,498 genes encoding proteins from 11,000 families, similar to the functional diversity of Drosophila and Caenorhabditis elegansÐ the other sequenced multicellular eukaryotes. Arabidopsis has many families of new proteins but also lacks several common protein families, indicating that the sets of common proteins have undergone differential expansion and contraction in the three multicellular eukaryotes. This is the ®rst complete genome sequence of a plant and provides the foundations for more comprehensive comparison of conserved processes in all eukaryotes, identifying a wide range of plant-speci®c gene functions and establishing rapid systematic ways to identify genes for crop improvement. The plant and animal kingdoms evolved independently from biologists, but will also affect agricultural science, evolutionary unicellular eukaryotes and represent highly contrasting life forms. biology, bioinformatics, combinatorial chemistry, functional and The genome sequences of C. elegans1 and Drosophila2 reveal that comparative genomics, and molecular medicine. metazoans share a great deal of genetic information required for developmental and physiological processes, but these genome Overview of sequencing strategy sequences represent a limited survey of multicellular organisms. We used large-insert bacterial arti®cial chromosome (BAC), phage Flowering plants have unique organizational and physiological (P1) and transformation-competent arti®cial chromosome (TAC) properties in addition to ancestral features conserved between libraries9±12 as the primary substrates for sequencing. Early stages of plants and animals. The genome sequence of a plant provides a genome sequencing used 79 cosmid clones. Physical maps of the means for understanding the genetic basis of differences between genome of accession Columbia were assembled by restriction plants and other eukaryotes, and provides the foundation for fragment `®ngerprint' analysis of BAC clones13, by hybridization14 detailed functional characterization of plant genes. or polymerase chain reaction (PCR)15 of sequence-tagged sites and Arabidopsis thaliana has many advantages for genome analysis, by hybridization and Southern blotting16. The resulting maps were including a short generation time, small size, large number of integrated (http://nucleus/cshl.org/arabmaps/) with the genetic offspring, and a relatively small nuclear genome. These advantages map and provided a foundation for assembling sets of contigs promoted the growth of a scienti®c community that has investi- into sequence-ready tiling paths. End sequence (http://www. gated the biological processes of Arabidopsis and has characterized tigr.org/tdb/at/abe/bac_end_search.html) of 47,788 BAC clones many genes3. To support these activities, an international collabora- was used to extend contigs from BACS anchored by marker content tion (the Arabidopsis Genome Initiative, AGI) began sequencing and to integrate contigs. the genome in 1996. The sequences of chromosomes 2 and 4 have Ten contigs representing the chromosome arms and centromeric been reported4,5, and the accompanying Letters describe the heterochromatin were assembled from 1,569 BAC, TAC, cosmid and sequences of chromosomes 1 (ref. 6), 3 (ref. 7) and 5 (ref. 8). P1 clones (average insert size 100 kilobases (kb)). Twenty-two PCR Here we report analysis of the completed Arabidopsis genome products were ampli®ed directly from genomic DNA and
- 41. Correlated gain/loss of genes • Microbial genes are lost rapidly when not maintained by selection • Genes can be acquired by lateral transfer • Frequently gain and loss occurs for entire pathways/processes • Thus might be able to use correlated presence/absence information to identify genes with similar functions
- 42. Non-Homology Predictions: Phylogenetic Profiling • Step 1: Search all genes in organisms of interest against all other genomes • Ask: Yes or No, is each gene found in each other species • Cluster genes by distribution patterns (profiles)
- 43. Carboxydothermus hydrogenoformans • Isolated from a Russian hotspring • Thermophile (grows at 80°C) • Anaerobic • Grows very efficiently on CO (Carbon Monoxide) • Produces hydrogen gas • Low GC Gram positive (Firmicute) • Genome Determined (Wu et al. 2005 PLoS Genetics 1: e65. )
- 44. Homologs of Sporulation Genes Wu et al. 2005 PLoS Genetics 1: e65.
- 45. Carboxydothermus sporulates Wu et al. 2005 PLoS Genetics 1: e65.
- 46. Wu et al. 2005 PLoS Genetics 1: e65.
- 48. Mutualistic Genome Evolution • Compare and contrast different types of mutualistic symbioses • Diverse hosts, symbionts, biology, ages • Organelles, chemosymbioses, photosynthetic symbioses, nutritional symbioses • What are the rules & patterns?
- 49. Glassy Winged Sharpshooter • Obligate xylem feeder • Can transmit Pierce’s Disease agent • Potential bioterror agent • Needs to get amino- acids and other nutrients from symbionts like aphids
- 50. Sharpshooter Shotgun Sequencing shotgun Collaboration with Nancy Wu et al. 2006 PLoS Biology 4: e188. Moran’s lab
- 54. Higher Evolutionary Rates in Endosymbionts Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab
- 55. Variation in Evolution Rates MutS MutL + + + + + + + + _ _ _ _ Wu et al. 2006 PLoS Biology 4: e188. Collaboration with Nancy Moran’ s Lab
- 56. Baumannia is a Vitamin and Cofactor Producing Machine Wu et al. 2006 PLoS Biology 4: e188.
- 60. Great Plate Count Anomaly Culturing Microscope Count Count
- 61. Great Plate Count Anomaly Culturing Microscope Count <<<< Count
- 62. Great Plate Count Anomaly DNA Culturing Microscope Count <<<< Count
- 63. rRNA PCR The Hidden Majority Richness estimates Hugenholtz 2002 Bohannan and Hughes 2003
- 64. rRNA data increasing exponentially too
- 65. Perna et al. 2003
- 66. Metagenomics shotgun clone
- 67. How can we best use metagenomic data? • Many possible uses including: – Improvements on rRNA based phylotyping and species diversity measurements – Adding functional information on top of phylogenetic/species diversity information • Most/all possible uses either require or are improved with phylogenetic analysis
- 68. Example I: Phylotyping with rRNA and other genes
- 69. Functional Diversity of Proteorhodopsins? Venter et al., 2004
- 70. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi C FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 73. Binning challenge A T B U C V D W E X F Y G Z
- 74. Binning challenge A T B U C V D W E X F Y G Best binning method: reference genomes Z
- 75. Binning challenge A T B U C V D W E X F Y G Best binning method: reference genomes Z
- 76. Binning challenge A T B U C V D W E X F Y G No reference genome? What do you do? Z
- 80. ???????
- 81. CFB Phyla
- 82. Sulcia makes amino acids Baumannia makes vitamins and cofactors Wu et al. 2006 PLoS Biology 4: e188.
- 83. Phylogenomics of Novelty III Knowing What We Don’t Know
- 84. Research Topics Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 85. Research Topics Variation in Mechanisms of Mechanisms: Origin of New Patterns, Causes Functions and Effects Species Evolution
- 86. As of 2002
- 87. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA WS3 Gemmimonas Firmicutes Fusobacteria Actinobacteria OP9 Cyanobacteria Synergistes Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 88. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 89. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 90. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 91. Need for Tree Guidance Well Established • Common approach within some eukaryotic groups • Many small projects funded to fill in some bacterial or archaeal gaps • Phylogenetic gaps in bacterial and archaeal projects commonly lamented in literature
- 92. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of OP8 Project Nitrospira Bacteroides bacteria Chlorobi • A genome Fibrobacteres Marine GroupA • Genome WS3 from each of Gemmimonas sequences are Firmicutes eight phyla Fusobacteria mostly from Actinobacteria OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are only Planctomycetes Spriochaetes sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus • Solution I: Dictyoglomus Eisen, Ward, Aquificae Thermudesulfobacteria sequence more Robb, Nelson, et Thermotogae phyla OP1 al OP11
- 94. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Still highly OP10 Thermomicrobia Chloroflexi biased in terms TM7 Deinococcus-Thermus Dictyoglomus of the tree Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 95. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Same trend in OP10 Thermomicrobia Chloroflexi Archaea TM7 Deinococcus-Thermus Dictyoglomus Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 96. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Same trend in OP10 Thermomicrobia Chloroflexi Eukaryotes TM7 Deinococcus-Thermus Dictyoglomus Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 97. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Same trend in OP10 Thermomicrobia Chloroflexi Viruses TM7 Deinococcus-Thermus Dictyoglomus Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 98. Proteobacteria • GEBA TM6 OS-K • At least 40 Acidobacteria • A genomic Termite Group OP8 phyla of bacteria encyclopedia Nitrospira Bacteroides • Genome Chlorobi of bacteria Fibrobacteres Marine GroupA sequences are and archaea WS3 Gemmimonas mostly from Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter OP10 • Solution: Really Thermomicrobia Chloroflexi Fill in the Tree TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Eisen & Ward, PIs Thermotogae OP1 OP11
- 100. GEBA Pilot Project: Components • Project overview (Phil Hugenholtz, Nikos Kyrpides, Jonathan Eisen, Eddy Rubin, Jim Bristow) • Project management (David Bruce, Eileen Dalin, Lynne Goodwin) • Culture collection and DNA prep (DSMZ, Hans-Peter Klenk) • Sequencing and closure (Eileen Dalin, Susan Lucas, Alla Lapidus, Mat Nolan, Alex Copeland, Cliff Han, Feng Chen, Jan-Fang Cheng) • Annotation and data release (Nikos Kyrpides, Victor Markowitz, et al) • Analysis (Dongying Wu, Kostas Mavrommatis, Martin Wu, Victor Kunin, Neil Rawlings, Ian Paulsen, Patrick Chain, Patrik D’Haeseleer, Sean Hooper, Iain Anderson, Amrita Pati, Natalia N. Ivanova, Athanasios Lykidis, Adam Zemla) • Adopt a microbe education project (Cheryl Kerfeld) • Outreach (David Gilbert) • $$$ (DOE, Eddy Rubin, Jim Bristow)
- 101. GEBA Pilot Project Overview • Identify major branches in rRNA tree for which no genomes are available • Identify those with a cultured representative in DSMZ • DSMZ grew > 200 of these and prepped DNA • Sequence and finish 100+ (covering breadth of bacterial/archaea diversity) • Annotate, analyze, release data • Assess benefits of tree guided sequencing • 1st paper Wu et al in Nature Dec 2009
- 102. Network of Life Bacteria Archaea Eukaryotes Figure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 103. GEBA Lesson 1: The rRNA Tree of Life is a Useful Tool for Identifying Phylogenetically Novel From Wu et al. 2009 Nature 462, 1056-1060
- 104. GEBA Lesson 2: The rRNA Tree of Life is not perfect ... 16s WGT, 23S Badger et al. 2005 Int J System Evol Microbiol 55: 1021-1026.
- 105. GEBA Lesson 3: Phylogeny driven genome selection (and phylogenetics) improves genome annotation • Took 56 GEBA genomes and compared results vs. 56 randomly sampled new genomes • Better definition of protein family sequence “patterns” • Greatly improves “comparative” and “evolutionary” based predictions • Conversion of hypothetical into conserved hypotheticals • Linking distantly related members of protein families • Improved non-homology prediction
- 106. GEBA Lesson 4: Metadata Important
- 107. GEBA Phylogenomic Lesson 5 Phylogeny-driven genome selection helps discover new genetic diversity
- 108. Phylogenetic Distribution Novelty: Bacterial Actin Related Protein 2"#3)&4&*&& !"#*)$*),+% 5"#$-.-6&0&1- !"#$%,$-%)( 7"#0(1.8-9& !"#$''+-+,',! 5"#:1,)*&$/0 !"#&$,%+)+-+ !"#$% !"#$%&'()*&& !"#$%&'(%() (( +"#,-.(/01 !"#*+,**'+( ;"#01,&-*0 !"#%*+$--( <"#$-.-3.1%&0 !"#%',&'-+) ') 2"#$&*-.-1 !"#$'(-%%+&$ ="#$.1001 !"#-*$+$(&( !&'( $++ >"#0$1,/%1.&0 !"#&$**+),)-! *$ $++ ;"#01,&-*0 !"#*+,$*'( '* 5"#:1,)*&$/0 !"#&$,%+%-%% $++ 5"#$-.-6&0&1- !"#',&+$)* !&') ?"#@-%1*)A10(-. !"#&%'%&*%* $++ B"#A1%%/0# "#%*,-&*'( )* 2"#*-)').@1*0 !"#*-&'''(+ 5"#$-.-6&0&1- !"#',&&*&* !&'* $++ ?"#@-%1*)A10(-. !"#$)),)*%, $++ ;"#01,&-*0 !"#*+,$*),! ;"#)$C.1$-/@ !"#&&),(*((- +!&' 5"#$-.-6&0&1- !"#$++-&%%! ), ."#,1(-*0 !"#$'-+*$((&! !&', (( !"#(C1%&1*1 !"#$-,(%'+-! (% 5"#$-.-6&0&1- !"#$,+$(,& $++ 5"#:1,)*&$/0 !"#&$,%+-,(,! !&'- -) ?"#4&0$)&4-/@ !"#''-+&%$- )% ?"#@-%1*)A10(-. !"#$)),),%) () 5"#$-.-6&0&1- !"#',&,$$% $++ ?"#C1*0-*&&!"#&$-*$ $(&$ !&'. $++ D"#01(&61 !"#$-&'*)%&+! !"#(C1%&1*1!"#$-%$ $),) !&'/ ?"#@-%1*)A1(-. !"#$((&+,*- $++ <"#@/0$/%/0 !"#&&'&%'*(, !&'(0 +/*! Haliangium ochraceum DSM 14365 Patrik D’haeseleer, Adam Zemla, Victor Kunin Wu et al. 2009 Nature 462, 1056-1060 See also Guljamow et al. 2007 Current Biology.
- 109. Network of Life Bacteria Archaea Eukaryotes FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 110. Protein Family Rarefaction Curves • Take data set of multiple complete genomes • Identify all protein families using MCL • Plot # of genomes vs. # of protein families
- 111. Wu et al. 2009 Nature 462, 1056-1060
- 112. Wu et al. 2009 Nature 462, 1056-1060
- 113. Wu et al. 2009 Nature 462, 1056-1060
- 114. Wu et al. 2009 Nature 462, 1056-1060
- 115. Wu et al. 2009 Nature 462, 1056-1060
- 116. Synapomorphies exist Wu et al. 2009 Nature 462, 1056-1060
- 117. Families/PD not uniform +,%-./&#(%)"* !"#$%"&'(%)"* ! !
- 118. Structural Novelty • Of the 17000 protein families in the GEBA56, 1800 are novel in sequence (Wu) • Structural modeling suggests many are structurally novel too (D'haeseleer) • 372 being crystallized by the PSI (Kerfeld)
- 119. GEBA Phylogenomic Lesson 6 Improves analysis of genome data from uncultured organisms
- 120. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi C FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 121. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi without good C FB Major Phylogenetic Group Sargasso Phylotypes C Cannot be done hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c ia sampling of genomes oc cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 122. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi C FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch Phylogenetic Binning ae Fu te so s D ba ei ct no er c oc ia cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 123. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut Ac e s tin ob ac te C ria hl o ro bi without good C FB Major Phylogenetic Group Sargasso Phylotypes C Cannot be done hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c ia sampling of genomes oc cu s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 124. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut e improves Ac s tin ob ac te C ria hl o ro bi C GEBA Project FB Major Phylogenetic Group Sargasso Phylotypes C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu metagenomic analysis s- Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 125. GEBA Cyano Sequencing status (as of 01/14): Awaiting Material 11 Library 12 Production 22 Finishing 5 Grand Total 50 On-going/ Planed Activities: - Building Cyanobacterial Metadatabase (IMG-GOLD) - 10th Cyanobacterial Molecular Biology Workshop, Lake Arrowhead, CA (06/10) --> Cheryl will host: Workshop training as prep for virtual Jamboree 117
- 126. GEBA RNB Plan: Sequence multiple Root Nodule Bacteria (RNBs) across the planet. Pilot: 100 RNBs. Beta RNB Cupriavidis Burkholderia Goal: • Understand BioGeographical effects on species Alpha RNB Azorhizobium evolution and understand host-specificity. Allorhizobium Bradyrhizobium Mesorhizobium Rationale: Rhizobium Sinorhizobium • N2 fixation by legume pastures and crops provides 65% of Devosia Ochrobactrum the N currently utilized in agricultural production. Phyllobacterium Balneimonas-like • Contributes 25 to 90 million metric tones N pa. • Symbioses save $US 6-10 billion annually on N fertilizer. • Grain and animal production enhanced by fixed nitrogen supplied by the symbiosis. 118 Nikos Kyrpides
- 127. 119
- 128. Proteobacteria • NSF-funded TM6 OS-K • At least 40 Tree of Life Acidobacteria Termite Group phyla of bacteria OP8 Project Nitrospira • Genome Bacteroides • A genome Chlorobi Fibrobacteres sequences are Marine GroupA from each of WS3 Gemmimonas mostly from eight phyla Firmicutes Fusobacteria three phyla Actinobacteria OP9 Cyanobacteria • Some other Synergistes Deferribacteres Chrysiogenetes phyla are only NKB19 Verrucomicrobia sparsely Chlamydia OP3 Planctomycetes sampled Spriochaetes Coprothmermobacter • Still not happy OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Eisen & Ward, PIs Thermudesulfobacteria Thermotogae OP1 OP11
- 129. Weighted % of Clones 0 0.1250 0.2500 0.3750 0.5000 Al ph ap ro te Be ob ta ac pr te ot ria G eo am ba m ct ap er ro ia Ep te si ob lo ac np te ro ria D te el ob ta ac pr te ot ria eo C ba ya ct no er b ia ac te Fi ria rm ic ut e improves Ac s tin ob ac te C ria hl o ro bi C GEBA Project FB Major Phylogenetic Group Sargasso Phylotypes but only a little C hl o ro fle Sp xi iro ch ae Fu te so s D ba ei ct no er c oc ia cu s- metagenomic analysis, Eu Th ry erm ar ch us C ae re ot na a rc ha eo ta Shotgun Sequencing Allows Use of Other Markers EFG Venter et al., Science 304: 66-74. 2004 EFTu rRNA RecA RpoB HSP70
- 130. Phylogenomics Future 1 Need to adapt genomic and metagenomic methods to make better use of data
- 131. iSEEM Project
- 132. Ways to Make Better Use of GEBA Data • Better phylogenetic methods for short reads • Rebuild protein family models • New phylogenetic markers • Need better phylogenies, including HGT • Improved tools for using distantly related genomes in metagenomic analysis
- 133. PhylOTU: A High-Throughput Procedure Quantifies Microbial Community Diversity and Resolves Novel Taxa from Metagenomic Data Thomas J. Sharpton1*, Samantha J. Riesenfeld1, Steven W. Kembel2, Joshua Ladau1, James P. O’Dwyer2,3, Jessica L. Green2, Jonathan A. Eisen4, Katherine S. Pollard1,5 1 The J. David Gladstone Institutes, University of California San Francisco, San Francisco, California, United States of America, 2 Center for Ecology and Evolutionary Biology, University of Oregon, Eugene, Oregon, United States of America, 3 Institute of Integrative and Comparative Biology, University of Leeds, Leeds, United Kingdom, 4 Department of Evolution and Ecology, University of California Davis, Davis, California, United States of America, 5 Institute for Human Genetics & Division of Biostatistics, Finding Metagenomic OTUs University of California San Francisco, San Francisco, California, United States of America Abstract Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU- finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity? Citation: Sharpton TJ, Riesenfeld SJ, Kembel SW, Ladau J, O’Dwyer JP, et al. (2011) PhylOTU: A High-Throughput Procedure Quantifies Microbial Community Diversity and Resolves Novel Taxa from Metagenomic Data. PLoS Comput Biol 7(1): e1001061. doi:10.1371/journal.pcbi.1001061 Editor: Oded Be ` , Technion-Israel Institute of Technology, Israel ´ja Received July 22, 2010; Accepted December 17, 2010; Published January 20, 2011 Copyright: ß 2011 Sharpton et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
- 134. Distances between gene trees and the AMPHORA concatenated genome tree rpmA coaE coaE rpmA trmD rplL rpsS rpsQ radA rplR rplD rplQ tsf rpsH frr smpB ttf rpsO rplR rplP rplM rpsS rplI rplV rpsB rplT rpsO rplO mraW rpsP rpsH rpsK rplQ rplU rplL tsf rplT trmD rplE rplS rpsP ttf rplC rpsI rplV mraW rplS rpsL infC rpsG rpsM rplM rplO rplI rplU pyrH rpsL rpsM rpsQ ruvA guaA radA rpsG purA smpB rplK priA rplD rpsK infC rplK rplC serS rplE rplA rplA rplF frr ruvA rplF rpsC serS rplN rplN rplP guaA rpsE ruvB pyrH rpsB rpsI rpsJ secY rRNA16S rpsJ secY purA rplB rplB priA nusA rpsE ruvB rpsC rRNA16S nusA 0 1 2 3 4 5 6 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 NODAL distance SPLIT distance AMPHORA marker Ribosomal protein Transcrip1on/transla1on related protein DNA repair protein Protein of other func1on Distance between the genome tree and 100 random trees (average ± standard devia1on)
- 135. Screen gene markers for any given taxonomic group Phylogene8c group Genome Number Gene Number Maker Candidates Archaea 62 145415 106 Ac1nobacteria 63 267783 136 Alphaproteobacteria 94 347287 121 Betaproteobacteria 56 266362 311 Gammaproteobacteria 126 483632 118 Deltaproteobacteria 25 102115 206 Epislonproteobacteria 18 33416 455 Bacteriodes 25 71531 286 Chlamydae 13 13823 560 Chloroflexi 10 33577 323 Cyanobacteria 36 124080 590 Firmicutes 106 312309 87 Spirochaetes 18 38832 176 Thermi 5 14160 974 Thermotogae 9 17037 684
- 139. Phylogenomics Future 2 We have still only scratched the surface of microbial diversity
- 140. rRNA Tree of Life FIgure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003.
- 141. Phylogenetic Diversity: Sequenced Bacteria & Archaea From Wu et al. 2009 Nature 462, 1056-1060
- 142. Phylogenetic Diversity with GEBA From Wu et al. 2009 Nature 462, 1056-1060
- 143. Phylogenetic Diversity: Isolates From Wu et al. 2009 Nature 462, 1056-1060
- 144. Phylogenetic Diversity: All From Wu et al. 2009 Nature 462, 1056-1060
- 145. Proteobacteria TM6 OS-K • At least 40 phyla of Acidobacteria Termite Group OP8 bacteria Nitrospira Bacteroides Chlorobi • Genome sequences are Fibrobacteres Marine GroupA mostly from three phyla WS3 Gemmimonas Firmicutes • Most phyla with cultured Fusobacteria Actinobacteria species are sparsely OP9 Cyanobacteria Synergistes sampled Deferribacteres Chrysiogenetes NKB19 • Lineages with no cultured Verrucomicrobia Chlamydia OP3 taxa even more poorly Planctomycetes Spriochaetes sampled Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Well sampled phyla Thermudesulfobacteria Thermotogae Poorly sampled OP1 OP11 No cultured taxa
- 146. Uncultured Lineages: Technical Approaches • Get into culture • Enrichment cultures • If abundant in low diversity ecosystems • Flow sorting • Microbeads • Microfluidic sorting • Single cell amplification
- 147. GEBA uncultured Number of SAGs from Candidate Phyla 406 1 OD1 OP1 OP3 SAR Site A: Hydrothermal vent 4 1 - - Site B: Gold Mine 6 13 2 - Site C: Tropical gyres (Mesopelagic) - - - 2 Site D: Tropical gyres (Photic zone) 1 - - - Sample collections at 4 additional sites are underway. Phil Hugenholtz 139
- 148. Phylogenomics Future 3 Need Experiments from Across the Tree of Life too
- 149. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA WS3 Gemmimonas Firmicutes Fusobacteria Actinobacteria OP9 Cyanobacteria Synergistes Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 150. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Experimental WS3 Gemmimonas Firmicutes studies are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 151. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Experimental WS3 Gemmimonas Firmicutes studies are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some studies Verrucomicrobia Chlamydia OP3 in other phyla Planctomycetes Spriochaetes Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Thermudesulfobacteria Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 152. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus • Same trend in Dictyoglomus Aquificae Thermudesulfobacteria Eukaryotes Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 153. As of 2002 Proteobacteria TM6 OS-K • At least 40 Acidobacteria Termite Group OP8 phyla of Nitrospira Bacteroides bacteria Chlorobi Fibrobacteres Marine GroupA • Genome WS3 Gemmimonas Firmicutes sequences are Fusobacteria Actinobacteria mostly from OP9 Cyanobacteria Synergistes three phyla Deferribacteres Chrysiogenetes NKB19 • Some other Verrucomicrobia Chlamydia OP3 phyla are Planctomycetes Spriochaetes only sparsely Coprothmermobacter OP10 Thermomicrobia sampled Chloroflexi TM7 Deinococcus-Thermus • Same trend in Dictyoglomus Aquificae Thermudesulfobacteria Viruses Thermotogae OP1 Based on OP11 Hugenholtz, 2002
- 154. Proteobacteria TM6 OS-K Need Acidobacteria Termite Group OP8 experimental Nitrospira Bacteroides Chlorobi studies from Fibrobacteres Marine GroupA WS3 across the tree Gemmimonas Firmicutes too Fusobacteria Actinobacteria OP9 Cyanobacteria Synergistes Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes 0.1 Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Tree based on Thermudesulfobacteria Thermotogae Hugenholtz (2002) OP1 with some OP11 modifications.
- 155. Proteobacteria TM6 OS-K Adopt a Acidobacteria Termite Group OP8 Microbe Nitrospira Bacteroides Chlorobi Fibrobacteres Marine GroupA WS3 Gemmimonas Firmicutes Fusobacteria Actinobacteria OP9 Cyanobacteria Synergistes Deferribacteres Chrysiogenetes NKB19 Verrucomicrobia Chlamydia OP3 Planctomycetes Spriochaetes 0.1 Coprothmermobacter OP10 Thermomicrobia Chloroflexi TM7 Deinococcus-Thermus Dictyoglomus Aquificae Tree based on Thermudesulfobacteria Thermotogae Hugenholtz (2002) OP1 with some OP11 modifications.
- 156. Conclusion • Phylogenetic sampling of genomes improves our understanding of microbial diversity in many ways • Still need – More biogeography – More phenotypic/experimental data – Deeper phylogenetic sampling
- 158. MICROBES
- 159. A Happy Tree of Life
- 160. Acknowledgements • GEBA: DOE-JGI, DSMZ • GWSS: Nancy Moran & lab, Dongying Wu • iSEEM: Katie Pollard, Jessica Green, Martin Wu • RecA: Dongying Wu, Craig Venter, Doug Rusch, et al.
Editor's Notes
- #2: \n
- #3: \n
- #4: \n
- #5: \n
- #6: \n
- #7: \n
- #8: \n
- #9: \n
- #10: \n
- #11: \n
- #12: \n
- #13: \n
- #14: \n
- #15: \n
- #16: \n
- #17: \n
- #18: It has been less than 10 years since the first genome was determined\n
- #19: \n
- #20: \n
- #21: \n
- #22: \n
- #23: \n
- #24: \n
- #25: \n
- #26: \n
- #27: \n
- #28: \n
- #29: \n
- #30: \n
- #31: \n
- #32: \n
- #33: \n
- #34: \n
- #35: \n
- #36: \n
- #37: \n
- #38: \n
- #39: \n
- #40: \n
- #41: \n
- #42: \n
- #43: \n
- #44: \n
- #45: \n
- #46: \n
- #47: \n
- #48: \n
- #49: Genome sizes estimated from careful cytospectrophotometry in the 1970&#x2019;s. 180 Mb = Drosophila size.\nMAC chromosome copy # exception: rDNA @ ~9,000 copies per MAC (by quantitative DNA hybridization)\nChromosome #s:\n MIC: Direct microscopic observations (1950s)\n Quantitative measurements in stained pulsed-field gels (1980s)\n
- #50: Cbs = chromosome breakage site\nIES = internally eliminated segment\n
- #51: \n
- #52: \n
- #53: \n
- #54: \n
- #55: \n
- #56: \n
- #57: \n
- #58: \n
- #59: \n
- #60: \n
- #61: \n
- #62: \n
- #63: \n
- #64: \n
- #65: \n
- #66: \n
- #67: \n
- #68: \n
- #69: \n
- #70: \n
- #71: \n
- #72: \n
- #73: \n
- #74: \n
- #75: \n
- #76: \n
- #77: \n
- #78: \n
- #79: \n
- #80: \n
- #81: \n
- #82: \n
- #83: \n
- #84: \n
- #85: \n
- #86: \n
- #87: \n
- #88: \n
- #89: \n
- #90: \n
- #91: \n
- #92: \n
- #93: Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- #94: Extension of rRNA analysis to uncultured organisms using PCR\n
- #95: \n
- #96: \n
- #97: \n
- #98: Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- #99: Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- #100: Functional prediction using a gene tree is just like predicting the biology of a species using a species tree\n
- #101: \n
- #102: \n
- #103: \n
- #104: \n
- #105: This is a tree of a rRNA gene that was found on a large DNA fragment isolated from the Monterey Bay. This rRNA gene groups in a tree with genes from members of the gamma Proteobacteria a group that includes E. coli as well as many environmental bacteria. This rRNA phylotype has been found to be a dominant species in many ocean ecosystems.\n
- #106: \n
- #107: \n
- #108: \n
- #109: Phylogenetic analysis of rRNAs led to the discovery of archaea\n
- #110: This is a tree of a rRNA gene that was found on a large DNA fragment isolated from the Monterey Bay. This rRNA gene groups in a tree with genes from members of the gamma Proteobacteria a group that includes E. coli as well as many environmental bacteria. This rRNA phylotype has been found to be a dominant species in many ocean ecosystems.\n\n clone from the Sargasso Sea. This shows that this \n
- #111: \n
- #112: \n
- #113: \n
- #114: \n
- #115: \n
- #116: \n
- #117: \n
- #118: \n
- #119: \n
- #120: \n
- #121: \n
- #122: \n
- #123: \n
- #124: \n
- #125: \n
- #126: \n
- #127: \n
- #128: \n
- #129: \n
- #130: \n
- #131: \n
- #132: \n
- #133: \n
- #134: \n
- #135: \n
- #136: \n
- #137: \n
- #138: \n
- #139: \n
- #140: \n
- #141: \n
- #142: \n
- #143: \n
- #144: \n
- #145: \n
- #146: \n
- #147: \n
- #148: \n
- #149: \n
- #150: \n
- #151: \n
- #152: \n
- #153: \n
- #154: \n
- #155: \n
- #156: \n
- #157: \n
- #158: \n
- #159: \n
- #160: \n
- #161: \n
- #162: \n
- #163: \n
- #164: \n
- #165: \n
- #166: \n
- #167: \n
- #168: \n
- #169: \n
- #170: \n
- #171: \n
- #172: \n
- #173: \n
- #174: \n
- #175: \n
- #176: \n
- #177: \n
- #178: \n
- #179: \n
- #180: \n
- #181: \n
- #182: \n
- #183: \n
- #184: \n
- #185: \n
- #186: \n
- #187: \n
- #188: \n
- #189: \n
- #190: \n
- #191: \n
- #192: \n
- #193: \n
- #194: \n
- #195: \n
- #196: \n
- #197: \n
- #198: \n
- #199: \n
- #200: \n
- #201: \n
- #202: \n
- #203: \n
- #204: \n
- #205: \n
- #206: \n
- #207: \n
- #208: \n
- #209: \n
- #210: \n
- #211: \n
- #212: \n
- #213: \n
- #214: \n
- #215: \n
- #216: It has been less than 10 years since the first genome was determined\n