DNA based Studies of Microbial Diversity        DNA based Studies of Microbial Diversity                               Jon...
Sequencing and Microbes     • Four major “ERAs” in use of sequencing for       microbial diversity studies     • Each area...
Era I: rRNA Tree of Life                              Era I:                         rRNA Tree of Life                    ...
Ernst Haeckel 1866     Plantae     Protista     Animalia                                         4                        ...
Whittaker – Five Kingdoms 1969    Monera    Protista    Plantae     Fungi    Animalia                                 5Mon...
Woese                         6Monday, January 28, 13
WoeseMonday, January 28, 13
WoeseMonday, January 28, 13
WoeseMonday, January 28, 13
Woese and Fox      • Abstract: A phylogenetic analysis based upon ribosomal        RNA sequence characterization reveals t...
Woese and Fox      • Propose “three aboriginal lines of descent”          Eubacteria          Archaebacteria          U...
WoeseWoese 1987 - rRNA                         Microbiological Reviews 51:221                                             ...
• Appearance of                                                            microbes not                                   ...
Tree of Life      • Three main kinds of organisms          Bacteria          Archaea          Eukaryotes      • Viruses...
The Tree of Life                         2006                                            adapted from Baldauf, et al., in ...
The Tree of Life                                                                 2006                         adapted from...
Era II: rRNA in the Environment                        Era II:               rRNA in the Environment                      ...
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Plant/Animal Field Studies                              18Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Microbial Field Studies                          19Monday, January 28, 13
Culturing Microbes                         20Monday, January 28, 13
Great Plate Count Anomaly                            21Monday, January 28, 13
Great Plate Count Anomaly                         Culturing   Microscopy                                                  ...
Great Plate Count Anomaly                         Culturing   Microscopy                          Count       Count       ...
Great Plate Count Anomaly                         Culturing          Microscopy                          Count      <<<<  ...
Great Plate Count Anomaly   Problem because    appearance not  effective for “who   is out there?” or    “what are they   ...
Great Plate Count Anomaly                                                     Solution?   Problem because    appearance no...
Great Plate Count Anomaly                                                     Solution?   Problem because    appearance no...
Analysis of uncultured microbes                         Collect from                         environment                  ...
PCR and phylogenetic analysis of rRNA genes                     DNA                     extraction                        ...
PCR and phylogenetic analysis of rRNA genes                     DNA                     extraction                        ...
PCR and phylogenetic analysis of rRNA genes                     DNA                     extraction                        ...
PCR and phylogenetic analysis of rRNA genes                         PCR                                              32Mon...
Major phyla of bacteria & archaea (as of 2002)                                                  No cultures               ...
The Hidden Majority                   Richness estimates                         Hugenholtz 2002         Bohannan and Hugh...
Human microbiome example                           35Monday, January 28, 13
A: Human biogeography                         Censored                         Censored                                   ...
A: Human biogeography                         37Monday, January 28, 13
A: Human biogeography                          Naris (R)             Forehead                            Hair             ...
Vertebrate Microbiomes                                          100                                                       ...
40Monday, January 28, 13
The Built Environment                                                                                                     ...
Era III: Genome Sequencing                          Era III:                     Genome Sequencing                        ...
1st Genome Sequence                         Fleischmann                         et al. 1995 43Monday, January 28, 13
Genomes Revolutionized Microbiology      • Predictions of metabolic processes      • Better vaccine and drug design      •...
45Monday, January 28, 13
Metabolic Predictions                         46Monday, January 28, 13
Lateral Gene Transfer   Perna et al. 2003                         47Monday, January 28, 13
Network of Life                         Bacteria                                                                Archaea   ...
Using the Core                         49Monday, January 28, 13
Whole Genome Phylogeny  Whole genome tree  built using  AMPHORA  by Martin Wu and  Dongying Wu                         50M...
Microbial genomes                         From http://genomesonline.org   51Monday, January 28, 13
GEBA as example                         52Monday, January 28, 13
Phylogenetic Diversity    • Phylogenetic diversity poorly      sampled    • GEBA project at DOE-JGI      correcting this  ...
54Monday, January 28, 13
http://www.jgi.doe.gov/programs/GEBA/pilot.html   55Monday, January 28, 13
GEBA Lesson 1: rRNA utility in IDing novel genomes   From Wu et al. 2009 Nature 462, 1056-1060         56Monday, January 2...
GEBA Lesson 2: rRNA Tree is not perfect                     16s                           WGT, 23S  Badger et al. 2005 Int...
GEBA Lesson 3: Phylogenetic sampling improves annotation        • Took 56 GEBA genomes and compared results vs. 56        ...
GEBA Lesson 4 : Metadata Important                                     59Monday, January 28, 13
GEBA Lesson 5:Improves discovering new genetic diversity                                                           60Monda...
Protein Family Rarefaction Curves      • Take data set of multiple complete genomes      • Identify all protein families u...
Wu et al. 2009 Nature 462, 1056-1060                                       62Monday, January 28, 13
Wu et al. 2009 Nature 462, 1056-1060                                       62Monday, January 28, 13
Wu et al. 2009 Nature 462, 1056-1060                                       62Monday, January 28, 13
Wu et al. 2009 Nature 462, 1056-1060                                       62Monday, January 28, 13
Wu et al. 2009 Nature 462, 1056-1060                                       62Monday, January 28, 13
Synapomorphies existWu et al. 2009 Nature 462, 1056-1060                                                63Monday, January ...
III: Epidemiology & Forensics                                64Monday, January 28, 13
Era IV: Genomes in the environment                Era IV:       Genomes in the Environment                                ...
Marine Microbe Background      • rRNA PCR studies of marine microbes have been        extensive      • Comparative analysi...
%&())%#*+,-###./*/!0##*1""#23##4(56#,!                                                                                    ...
facts17. They concluded that most sequence variation was clustered                                      many microbia     ...
Delong GENOMIC FRAGMENTS FROM PLANKTONIC MARINE ARCHAEA          Lab                                                      ...
Delong Lab                                                                    J. BACTERIOL.                FIG. 4. High-de...
l gene  own transducer of light stimuli [for example,   the kinetics of its photochemical reaction cy- leDelong Lab    ge-...
generated                                                                                                                 ...
73Monday, January 28, 13
Figure 3. Phylogenetic tree based on the amino acid sequences of 25 archaeal rhodopsins. (a) NJ-tree. The numbers at each ...
RESEARCH ARTICLES    Fig. 2. Secondary    structure of proteo-    rhodopsin. Single-    letter amino acid    codes are use...
duce                                                                                                                  in t...
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
Eisen Lecture for Ian Korf genomics course
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Eisen Lecture for Ian Korf genomics course

  1. 1. DNA based Studies of Microbial Diversity DNA based Studies of Microbial Diversity Jonathan A. Eisen Jonathan A. Eisen University of California, Davis University of California, Davis 1Monday, January 28, 13
  2. 2. Sequencing and Microbes • Four major “ERAs” in use of sequencing for microbial diversity studies • Each area represented by the Eras is being revolutionized by new sequencing methods 2Monday, January 28, 13
  3. 3. Era I: rRNA Tree of Life Era I: rRNA Tree of Life 3Monday, January 28, 13
  4. 4. Ernst Haeckel 1866 Plantae Protista Animalia 4 www.mblwhoilibrary.orgMonday, January 28, 13
  5. 5. Whittaker – Five Kingdoms 1969 Monera Protista Plantae Fungi Animalia 5Monday, January 28, 13
  6. 6. Woese 6Monday, January 28, 13
  7. 7. WoeseMonday, January 28, 13
  8. 8. WoeseMonday, January 28, 13
  9. 9. WoeseMonday, January 28, 13
  10. 10. Woese and Fox • Abstract: A phylogenetic analysis based upon ribosomal RNA sequence characterization reveals that living systems represent one of three aboriginal lines of descent: (i) the eubacteria, comprising all typical bacteria; (ii) the archaebacteria, containing methanogenic bacteria; and (iii) the urkaryotes, now represented in the cytoplasmic component of eukaryotic cells.Monday, January 28, 13
  11. 11. Woese and Fox • Propose “three aboriginal lines of descent”  Eubacteria  Archaebacteria  UrkaryotesMonday, January 28, 13
  12. 12. WoeseWoese 1987 - rRNA Microbiological Reviews 51:221 12Monday, January 28, 13
  13. 13. • Appearance of microbes not informative (enough) • rRNA Tree of Life identified two major groups of organisms w/o nuclei • rRNA powerful for many reasons, though not perfect Barton, Eisen et al. “Evolution”, CSHL Press. 2007. Based on tree from Pace 1997 Science 276:734-740 13Monday, January 28, 13
  14. 14. Tree of Life • Three main kinds of organisms  Bacteria  Archaea  Eukaryotes • Viruses not alive, but some call them microbes • Many misclassifications occurred before the use of molecular methods 14Monday, January 28, 13
  15. 15. The Tree of Life 2006 adapted from Baldauf, et al., in Assembling the Tree of Life, 2004 15Monday, January 28, 13
  16. 16. The Tree of Life 2006 adapted from Baldauf, et al., in Assembling the Tree of Life, 2004Monday, January 28, 13
  17. 17. Era II: rRNA in the Environment Era II: rRNA in the Environment 17Monday, January 28, 13
  18. 18. Plant/Animal Field Studies 18Monday, January 28, 13
  19. 19. Plant/Animal Field Studies 18Monday, January 28, 13
  20. 20. Plant/Animal Field Studies 18Monday, January 28, 13
  21. 21. Plant/Animal Field Studies 18Monday, January 28, 13
  22. 22. Plant/Animal Field Studies 18Monday, January 28, 13
  23. 23. Plant/Animal Field Studies 18Monday, January 28, 13
  24. 24. Plant/Animal Field Studies 18Monday, January 28, 13
  25. 25. Microbial Field Studies 19Monday, January 28, 13
  26. 26. Microbial Field Studies 19Monday, January 28, 13
  27. 27. Microbial Field Studies 19Monday, January 28, 13
  28. 28. Microbial Field Studies 19Monday, January 28, 13
  29. 29. Microbial Field Studies 19Monday, January 28, 13
  30. 30. Microbial Field Studies 19Monday, January 28, 13
  31. 31. Microbial Field Studies 19Monday, January 28, 13
  32. 32. Culturing Microbes 20Monday, January 28, 13
  33. 33. Great Plate Count Anomaly 21Monday, January 28, 13
  34. 34. Great Plate Count Anomaly Culturing Microscopy 22Monday, January 28, 13
  35. 35. Great Plate Count Anomaly Culturing Microscopy Count Count 23Monday, January 28, 13
  36. 36. Great Plate Count Anomaly Culturing Microscopy Count <<<< Count 24Monday, January 28, 13
  37. 37. Great Plate Count Anomaly Problem because appearance not effective for “who is out there?” or “what are they doing?” Culturing Microscopy Count <<<< Count 25Monday, January 28, 13
  38. 38. Great Plate Count Anomaly Solution? Problem because appearance not effective for “who is out there?” or “what are they doing?” Culturing Microscopy Count <<<< Count 26Monday, January 28, 13
  39. 39. Great Plate Count Anomaly Solution? Problem because appearance not effective for “who is out there?” or DNA “what are they doing?” Culturing Microscopy Count <<<< Count 27Monday, January 28, 13
  40. 40. Analysis of uncultured microbes Collect from environment 28Monday, January 28, 13
  41. 41. PCR and phylogenetic analysis of rRNA genes DNA extraction PCR Makes lots Sequence PCR of copies of rRNA genes the rRNA genes in sample rRNA1 5’ ...TACAGTATAGGT Phylogenetic tree Sequence alignment = Data matrix GGAGCTAGCGATC GATCGA... 3’ rRNA1 Yeast rRNA1 A C A C A C Yeast T A C A G T E. coli A G A C A G E. coli Humans Humans T A T A G T 29Monday, January 28, 13
  42. 42. PCR and phylogenetic analysis of rRNA genes DNA extraction PCR Makes lots Sequence PCR of copies of rRNA genes the rRNA genes in sample rRNA1 5’ ...ACACACATAGGT Phylogenetic tree Sequence alignment = Data matrix GGAGCTAGCGATC GATCGA... 3’ rRNA1 rRNA2 rRNA1 A C A C A C rRNA2 T A C A G T rRNA2 5’ E. coli A G A C A G ...TACAGTATAGGT E. coli Humans Humans T A T A G T GGAGCTAGCGATC GATCGA... 3’ Yeast Yeast T A C A G T 30Monday, January 28, 13
  43. 43. PCR and phylogenetic analysis of rRNA genes DNA extraction PCR Makes lots Sequence PCR of copies of rRNA genes the rRNA genes in sample rRNA1 5’...ACACACATAGGTGGAGC TAGCGATCGATCGA... 3’ Phylogenetic tree Sequence alignment = Data matrix rRNA2 rRNA1 rRNA2 rRNA1 A C A C A C 5’..TACAGTATAGGTGGAGCT rRNA4 AGCGACGATCGA... 3’rRNA3 rRNA2 T A C A G T rRNA3 rRNA3 C A C T G T 5’...ACGGCAAAATAGGTGGA E. coli Humans rRNA4 C A C A G T TTCTAGCGATATAGA... 3’ Yeast E. coli A G A C A G rRNA4 5’...ACGGCCCGATAGGTGG Humans T A T A G T ATTCTAGCGCCATAGA... 3’ Yeast T A C A G T 31Monday, January 28, 13
  44. 44. PCR and phylogenetic analysis of rRNA genes PCR 32Monday, January 28, 13
  45. 45. Major phyla of bacteria & archaea (as of 2002) No cultures Some cultures 33Monday, January 28, 13
  46. 46. The Hidden Majority Richness estimates Hugenholtz 2002 Bohannan and Hughes 2003 34Monday, January 28, 13
  47. 47. Human microbiome example 35Monday, January 28, 13
  48. 48. A: Human biogeography Censored Censored 36Monday, January 28, 13
  49. 49. A: Human biogeography 37Monday, January 28, 13
  50. 50. A: Human biogeography Naris (R) Forehead Hair External nose Naris (L) Ext. auditory Ext. auditory canal (R) Lat. pinna (R) Lat. pinna (L) canal (L) Axilla (R) Dorsal tongue Oral cavity Axilla (L) Volar Volar forearm (R) Palm (R) Palm (L) forearm (L) Palmar index Palmar index finger (R) Gut Umbilicus finger (L) Popliteal Plantar Glans Labia Plantar Popliteal fossa (R) foot (R) penis minora foot (L) fossa (L) Acinetobacter Actinomycetales Actinomycineae Alistipes Anaerococcus Bacteroidales Bacteroides Bifidobacteriales Branhamella Campylobacter Capnocytophaga Carnobacteriaceae1 Carnobacteriaceae2 Clostridiales Coriobacterineae Corynebacterineae Faecalibacterium Finegoldia Fusobacterium Gemella Lachnospiraceae Lachnospiraceae (inc. sed.) Lactobacillus Leptotrichia Micrococcineae Neisseria Oribacterium Parabacteroides Pasteurella Pasteurellaceae 38 Peptoniphilus Prevotella Prevotellaceae Propionibacterineae Ruminococcaceae Staphylococcus Streptococcus Veillonella OtherMonday, January 28, 13
  51. 51. Vertebrate Microbiomes 100 Bacteroidetes (red) 80 16S ribosomal RNA sequences (%) 60 40 20 ANALYSIS Firmicutes (blue) 0 r s ts n r e t t ate ured rm en um a ate t fac gu gu d wcultthwo im rh t w men surrmite ate xe Mi aliner ea r sed he Sal di r ate Te br ter Ot se -w Ve rte Worlds within worlds: evolution of n-s ts o hw a ic o r Sal t No sec In rf res n ox the vertebrate gut microbiota so e, a S oil r fac Ruth E. Ley*‡¶, Catherine A. Lozupone*§¶, Micah Hamady||, Rob Knight § and bsu Jeffrey I. Gordon* Su Abstract | In this Analysis we use published 16S ribosomal RNA gene sequences to c Figure 3 | Relative abundance of phyla in samples. Bar graph showing the proportion of sequences from eachassemblages that are associated withrange of environments. The comp the bacterial sample and free-living microbial communities that span a humans and other mammals, me that could be classified at the phylum level. The colour codes for the dominant Firmicutes and Bacteroidetes phyla are microbiota is influenced by diet, host morphology and phyloge of the vertebrate gut shown. Nature Reviews | Microbiology For a complete description of the colour codes see Supplementary information S2 (figure). ‘Other humans’ refersvertebrate gut microbiotacommunity is typical of an omnivorous prima in this respect the human gut bacterial However, the to body is different from free-living communities th habitats other than the gut; for example, the mouth, ear, skin, vagina and vulva (see Supplementary information S1 (table)). habitats. We propose that the recently initiated not associated with animal body international Human Microbiome Project should strive to include a broad represent humans, as well as other mammalian and environmental samples, as comparative an of microbiotas and their microbiomes are a powerful way to explore the evolutionar history of the biosphere. 39 Genera that cross the divide. Another way to visualize family of the gammaproteobacteria class. This fam-Monday, January 28, 13 the vertebrate gut–environment dichotomy is by using a ily contained OTUs from both theDiverse microorganisms and microbial communities are vertebrate gut and Microbiota host energy metabolism8–11. Host responses to
  52. 52. 40Monday, January 28, 13
  53. 53. The Built Environment Microbial Biogeography of Public Restroom Surfaces Gilberto E. Flores1, Scott T. Bates1, Dan Knights2, Christian L. Lauber1, Jesse Stombaugh3, Rob Knight3,4, Noah Fierer1,5* Bacteria of Public Restrooms 1 Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, Colorado, United States of America, 2 Department of Computer Science, University of Colorado, Boulder, Colorado, United States of America, 3 Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado, United States of America, 4 Howard Hughes Medical Institute, University of Colorado, Boulder, Colorado, United States of America, 5 Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, United States of America Abstract We spend the majority of our lives indoors where we are constantly exposed to bacteria residing on surfaces. However, the diversity of these surface-associated communities is largely unknown. We explored the biogeographical patterns exhibited by bacteria across ten surfaces within each of twelve public restrooms. Using high-throughput barcoded pyrosequencing of The ISME Journal (2012), 1–11 the 16 S rRNA gene, we identified 19 bacterial phyla across all surfaces. Most sequences belonged to four phyla: & 2012 International Society for Microbial Ecology All rights reserved 1751-7362/12 Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria. The communities clustered into three general categories: those www.nature.com/ismej found on surfaces associated with toilets, those on the restroom floor, and those found on surfaces routinely touched with Figure 3. Cartoon toilet surfaces, gut-associated taxa were more prevalent, suggesting fecal contamination of Light blue indicates low hands. On illustrations of the relative abundance of discriminating taxa on public restroom surfaces. these surfaces. Floor ORIGINAL ARTICLE abundance while were the most diverse of all communities and contained several taxa commonly found in soils. Skin-associated surfaces dark blue indicates high abundance of taxa. (A) Although skin-associated taxa (Propionibacteriaceae, Corynebacteriaceae, Staphylococcaceae especially the Propionibacteriaceae, on all surfaces, they were relatively more abundant on surfaces routinely touched with bacteria, and Streptococcaceae) were abundant dominated surfaces routinely touched with our hands. Certain taxa were more Architectural design influences the diversity and hands. (B) Gut-associated taxa (Clostridiales, Clostridiales group XI,vagina-associated Lactobacillaceae were widely Bacteroidaceae)in female common in female than in male restrooms as Ruminococcaceae, Lachnospiraceae, Prevotellaceae and distributed were most abundant on toilet surfaces. from urine contamination. Use of the SourceTracker algorithm confirmed Nocardioidaceae) taxonomic restrooms, likely (C) Although soil-associated taxa (Rhodobacteraceae, Rhizobiales, Microbacteriaceae and many of our were in low abundance on all restroom surfaces, they were relatively more abundant on the floor of the surfaces. Overall, theseFigure not drawn to scale. observations as human skin was the primary source of bacteria on restroom restrooms we surveyed. results demonstrate that structure of the built environment microbiome doi:10.1371/journal.pone.0028132.g003 restroom surfaces host relatively diverse microbial communities dominated by human-associated bacteria with clear linkages between communities on or in different body sites and those communities found on restroom surfaces.Bacteria of P More 1 1 1,2 Steven W Kembel , Evan Jones , Jeff Kline , Dale Northcutt , Jason Stenson , 1,2 1,2 the stallgenerally,were likely dispersed manuallypublicwomen used as we Results of human-associated microbes are commonly found in), they this work is relevant to the after health field show that SourceTracker analysis support the taxonomic 1 on restroom surfaces suggesting that bacterial pathogens could readily be transmitted between individuals by the touching the toilet. Coupling these observations with those of the patterns highlighted above, indicating that human skin was the time, the M Womack , Brendan JM 100 Ann Bohannan1, G Z Brown1,2 and Jessica L Green1,3 1 SOURCES distribution of gut-associated bacteria demonstrate that we use use high-throughput analyses of bacterial communities to determine of surfaces. Furthermore, we indicate that routine can Bathroom biogeography. By on indoor surfaces, an approach of primary source of bacteria on all public restroom surfaces Biology and the Built Environment Center, Institute of Ecology and Evolution, Department of sources the dispersal of urine- and fecal-associated bacteria of bacteria whichexamined, while the track pathogen transmission and test the could be used to human gut was an important source on orun to take Biology, University of Oregon, Eugene, OR, USA; 2Energy Studies in Buildings Laboratory, Soil swabbing toilets results in restroom. While these results are not unexpected, different surfaces in throughout the of hygiene practices. efficacy around the toilet, and urine was an important source in women’sof outside 80of Oregon, Eugene, OR, USA and 3Santa Fe Institute, Water Average contribution (%) Department of Architecture, University public restrooms,highlight the importance of hand-hygiene when using they do researchers restrooms (Figure 4, Table S4). Contrary to expectations (see Mouthom plants Fe, NM, USA Santa determined thatCitation: Floressince these Knights D, Lauber CL, Stombaugh J, et al. (2011)above), soil was not identified by the Surfaces. PLoS ONEalgorithm as public microbes vary in ST, surfaces could also be potential restrooms GE, Bates Microbial Biogeography of Public Restroom SourceTracker 6(11): e28132. Urine doi:10.1371/journal.pone.0028132ours after 60 where they come from depend- vehicles for the transmission of human pathogens. Unfortunately, being a major source of bacteria on any of the surfaces, including Gut Editor: Mark R. Liles, Auburn University, United States of America ere shut ing on the previous (chart).have documented that college students (who are November 23, 2011 4). Although the floor samples contained family-level surface studies floors (Figure Buildings are complex ecosystems that house trillions of microorganisms interactingSkin each with likely Received September 12, 2011; of the studied restrooms) Published the most frequent users Accepted November 1, 2011; are not taxa that are common in soil, the SourceTracker algorithm 40ortion of other, with humans and with their environment. Understanding the ecological and evolutionary Copyright: diligent of hand-washers open-access article distributed under the terms of the Creative Commons Attribution License, sources, like always the most ß 2011 Flores et al. This is an[42,43]. probably underestimates the relative importance of which permits processes that determine the diversity and composition of the built environment microbiome—the unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. e human community of microorganisms that live indoors—is important for understanding the relationship pant in indoor microbial 20 Funding: This work was supported with funding from the Alfred P. Sloan Foundation and their Indoor Environment program, and in part by the National ck to pre- between building design, biodiversity and human health. In this study, we used high-throughputecology research,ofPeccia the Howard Hughes Medical Institute. The funders had no role in study design, data collection and analysis, decision to publish, or Institutes Health and sequencing of the bacterial 16S rRNA gene to quantify relationships between building attributes and airborne bacterial communities at 0 health-care facility. We quantified airborne bacterial community a thinks that the fieldthe manuscript. preparation of has wh i c h structure and environmental conditions in patient rooms exposed to mechanical or window yet to gel. And the Sloan The authors have declared that no competing interests exist. Competing Interests: Do in t in So han t dis les ile oile r hh t To ndle Si or or ou et ll ou lus t sea e * E-mail: noah.fierer@colorado.edu ns lo flo ventilation and in outdoor air. The phylogenetic diversity of airborne bacterial communities was or all d 26 Janu- lower indoors than outdoors, and mechanically ventilated rooms contained less diverse microbialFoundation’s Olsiewski or tf a Do pe St Fa Sta nk ile T Journal, communities than did window-ventilated rooms. Bacterial communities in indoor environments shares some of his con- uc ap tf contained many taxa that are absent or rare outdoors, including taxa closely related to potential Introduction communities and revealed a greater diversity of bacteria onhanically cern. “Everybody’s gen- To human pathogens. Building attributes, specifically the source of ventilation air, airflow rates, relative indoor surfaces than captured using cultivation-based techniqueshad lower humidity and temperature, were correlated with the diversity and composition of indoor bacterial erating vastMore than ever, individuals across the globe spend a large [10–13]. Most of the organisms identified in these studies are amounts of communities. The relative abundance of bacteria closely related to human pathogens was higher y than ones with openthan outdoors, and higher in rooms withquantify those con- lower relative humidity. looking acrossofdata lives of indooryet relatively littleOf known aboutthat related to human commensals suggesting that the organisms are indoors win- they move around. But to lower airflow rates and data,” she says, but portion their microbial diversity setsindoors, environments. is the studies the Figure 2. Relationship between bacterial communities associated with tenon the surfaces but rather Communities were not actively growing public restroom surfaces. were depositedbility of fresh air translated tributions, Peccia’s team has had to develop diversity suggests that The observed relationship between building design and airborne bacterial can be difficult because groups choose dif- of the unweighted UniFrac distance matrix. Each point represents a single sample. Note that the floor (triangles) and toilet (as rg on February 9, 2012 PCoA have examined microorganisms associated with indoor environ- directly (i.e. touching) or indirectly (e.g. shedding of skin cells) by we can manage indoor environments, altering through building design and operation the communityrtions of microbes associ- new methods to collect airborne bacteria and our timeanalytical tools. With Sloan support, of microbial species that potentially colonize the human microbiome during ferent indoors. ments, most have relied upon cultivation-based techniques hands. humans. Despite these efforts, we still have an incomplete form clusters distinct from surfaces touched with to doi:10.1371/journal.pone.0028132.g002 The ISME Journal advance online publication, 26the microbes are much detect organisms residing on a variety of household surfaces [1–5]. January 2012; doi:10.1038/ismej.2011.211 a data archive and integrated analyt- understanding of bacterial communities associated with indoor an body, and consequently, microbial their DNA, as Subject Category: extract population and community ecology though, Not surprisingly, these studies have identified surfaces in kitchens environments because limitations of traditional 16 S rRNA genepathogens. Although this less abundant in air than on surfaces. Keywords: aeromicrobiology; bacteria; built environment microbiome; community ecology; are in the works. and restrooms as being hot of floorof bacterial contamination. the frequency of sequencing differences in themade replicate samplings ical tools dispersal; high diversity spots communities is likely due to cloning and related techniques have relative abundances of environmental filtering In one recent study, they used air filtershat having natural airflow To foster collaborations between micro- with the bottom aofvariety ofto survive on inanddiversity characterizations of the communities Most surfaces Because several contact pathogenic bacteria are known which would track a in-depth some surfaces (Figure 1B, Table S2). prohibitive. of microorganisms from shoes, sources including soil, which is were clearly more abundant on certain notably surfaces for extended periods of time [6–8], these studies are of With the advent of high-throughput restrooms (Figure 1B). Some sequencing techniques, we Green says answering that to sample airborne particles and microbes biologists, architects, and building scientists,in preventing the spread of human habitat [27,39]. Indeed, restrooms than male known to be a highly-diverse microbial disease. obvious importance 41 can now investigate are family indoor microbial communitiesmost abu often at an Introduction clinical data; she’s hoping in a classroom during 4 days during which human pathogensalso sponsored a symposium widely recognized that the majority of Rhodobacteraceae, depth and the most common, andthe relationship microbiome—includes the foundation and com- However, it is bacteria commonly associated with soil (e.g. now unprecedented found in the vagina of healthy reproductive age w begin to understand mensals interacting with each other and with their microorganisms Rhizobiales, Microbacteriaceae and[9] and thus, the cannot be readily cultivated Nocardioidaceae) were, on average, ital to participate in a study 90% of theirwere present and 4 days during et on the microbiome of the built environment abundant on floor surfaces (Figure 3C, Table S2). and are relatively less abundant in male urine Humans spend up to students lives indoors environment (Eames al., 2009). There have been between humans, microbes and the built environment. overall diversitymore microorganisms associated with indoor of Monday,etJanuary which 13 the was vacant. They measured at the 2011 Indoor Air conference in Austin, largelysome of the Recentflush handles harbored In order to begin to of female urine samples collected as part 28, thedence of hospital-acquired Consequently,roomway we few attempts to comprehensively survey the built (Klepeis al., 2001). design and operate the indoor environment has a Interestingly, unknown. toilet use of cultiva- environments remains bacterial analysis comprehensively describe the microbial communities similar to those found on the floor diversity of indoor environments, 1A), characterized the bacterial environment microbiome (Rintala et al., 2008; (Figure 2, study [26] (Figure we found that Lactobacillaceae we
  54. 54. Era III: Genome Sequencing Era III: Genome Sequencing 42Monday, January 28, 13
  55. 55. 1st Genome Sequence Fleischmann et al. 1995 43Monday, January 28, 13
  56. 56. Genomes Revolutionized Microbiology • Predictions of metabolic processes • Better vaccine and drug design • New insights into mechanisms of evolution • Genomes serve as template for functional studies • New enzymes and materials for engineering and synthetic biology 44Monday, January 28, 13
  57. 57. 45Monday, January 28, 13
  58. 58. Metabolic Predictions 46Monday, January 28, 13
  59. 59. Lateral Gene Transfer Perna et al. 2003 47Monday, January 28, 13
  60. 60. Network of Life Bacteria Archaea Eukaryotes Figure from Barton, Eisen et al. “Evolution”, CSHL Press. Based on tree from Pace NR, 2003. 48Monday, January 28, 13
  61. 61. Using the Core 49Monday, January 28, 13
  62. 62. Whole Genome Phylogeny Whole genome tree built using AMPHORA by Martin Wu and Dongying Wu 50Monday, January 28, 13
  63. 63. Microbial genomes From http://genomesonline.org 51Monday, January 28, 13
  64. 64. GEBA as example 52Monday, January 28, 13
  65. 65. Phylogenetic Diversity • Phylogenetic diversity poorly sampled • GEBA project at DOE-JGI correcting this 53Monday, January 28, 13
  66. 66. 54Monday, January 28, 13
  67. 67. http://www.jgi.doe.gov/programs/GEBA/pilot.html 55Monday, January 28, 13
  68. 68. GEBA Lesson 1: rRNA utility in IDing novel genomes From Wu et al. 2009 Nature 462, 1056-1060 56Monday, January 28, 13
  69. 69. GEBA Lesson 2: rRNA Tree is not perfect 16s WGT, 23S Badger et al. 2005 Int J System Evol Microbiol 55: 1021-1026. 57Monday, January 28, 13
  70. 70. GEBA Lesson 3: Phylogenetic sampling improves 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 58Monday, January 28, 13
  71. 71. GEBA Lesson 4 : Metadata Important 59Monday, January 28, 13
  72. 72. GEBA Lesson 5:Improves discovering new genetic diversity 60Monday, January 28, 13
  73. 73. Protein Family Rarefaction Curves • Take data set of multiple complete genomes • Identify all protein families using MCL • Plot # of genomes vs. # of protein families 61Monday, January 28, 13
  74. 74. Wu et al. 2009 Nature 462, 1056-1060 62Monday, January 28, 13
  75. 75. Wu et al. 2009 Nature 462, 1056-1060 62Monday, January 28, 13
  76. 76. Wu et al. 2009 Nature 462, 1056-1060 62Monday, January 28, 13
  77. 77. Wu et al. 2009 Nature 462, 1056-1060 62Monday, January 28, 13
  78. 78. Wu et al. 2009 Nature 462, 1056-1060 62Monday, January 28, 13
  79. 79. Synapomorphies existWu et al. 2009 Nature 462, 1056-1060 63Monday, January 28, 13
  80. 80. III: Epidemiology & Forensics 64Monday, January 28, 13
  81. 81. Era IV: Genomes in the environment Era IV: Genomes in the Environment 65Monday, January 28, 13
  82. 82. Marine Microbe Background • rRNA PCR studies of marine microbes have been extensive • Comparative analysis had revealed many lineages, some very novel, some less so, that were dominant in many, if not all, open ocean samples • Lineages given names based on specific clones: e.g., SAR11, SAR86, etc 66Monday, January 28, 13
  83. 83. %&())%#*+,-###./*/!0##*1""#23##4(56#,! Molecular diversity and ecology of microbial plankton Stephen J. Giovannoni1 & Ulrich Stingl1 The history of microbial evolution in the oceans is probably as old as the history of life itself. In contrast to terrestrial ecosystems, microorganisms are the main form of biomass in the oceans, and form some of the INSIGHT REVIEW largest populations on the planet. Theory predicts that selection should act437|15 September 2005 NATURE|Vol more efficiently in large populations. But whether microbial plankton populations harbour organisms that are models of adaptive sophistication remains to be seen. Genome sequence data are piling up, but most of the key microbial plankton clades have no cultivated representatives, and information about their ecological activities is sparse. Archaea Certain characteristics of the ocean environment — the prevailing cultivation of key organisms, metagenomics and ongoing biogeo- low-nutrient state of the ocean surface, in particular — mean it is chemical studies. It seems very likely that the biology of the dominant Crenarchaeota Euryarchaeota sometimes regarded as an extreme ecosystem. Fixed forms of nitrogen, microbial plankton groups will be unravelled in the years ahead. Group I Archaea Group II Archaea phosphorus and iron are often at very low or undetectable levels in the Here we review current knowledge about marine bacterial and ocean’s circulatory gyres, which occur in about 70% of the oceans1. archaeal diversity, as inferred from phylogenies of genes recovered Group III Archaea Photosynthesis is the main source of metabolic energy and the basis of from the ocean water column, and consider the implications of micro- Group IV Archaea the food chain; ocean phytoplankton account for nearly 50% of global bial diversity for understanding the ecology of the oceans. Although carbon fixation, and half of the carbon fixed into organic matter is we leave protists out of the discussion, many of the same issues apply rapidly respired by heterotrophic microorganisms. Most cells are freely to them. Some of the studies we refer to extend to the abyssal ocean, suspended in the mainly oxic water column, but some attach to aggre- but we focus principally on the surface layer (0–300 m) — the region gates. In general, these cells survive either by photosynthesizing or by of highest biological activity. oxidizing dissolved organic matter (DOM) or inorganic compounds, α-Proteobacteria as an electron acceptor. using oxygen Phylogenetic diversity in the ocean 5 * SAR11 - theMicrobial cell concentrations are thymidine uptake into microbial Pelagibacterlayer (0–300 m) — typically about 10 cells ml in Small-subunit ribosomal (RNA) genes have become universal phylo- ǁ1 ocean surface ubique genetic markers and are the main criteria by which microbial plank- * Roseobacterindicates average growth rates of about 0.15 divisions per day DNA clade ton groups are identified and named9. Most of the marine microbial Chloroflexi OCS116 (ref. 2). Efficient nutrient recycling, in which there is intense competi- groups were first identified by sequencing rRNA genes cloned from tion for scarce resources, sustains this growth, with predation by seawater10–14, and remain uncultured today. Soon after the first reports SAR202 ß-Proteobacteria viruses and protozoa keeping populations in check and driving high came in, it became apparent that less than 20 microbial clades * OM43 turnover rates3. Despite this competition, steady-state dissolved accounted for most of the genes recovered15. Figure 1 is a schematic organic carbon (DOC) concentrations are many times higher than illustration of the phylogeny of these major plankton clades. The taxon µ-Proteobacteria carbon sequestered in living microbial biomass4. However, the average names marked with asterisks represent groups for which cultured iso- Planctobacteria SAR86 age of the DOC pool in the deep ocean, of about 5,000 years5 (deter- lates are available. * OMG Clade by isotopic dating), suggests thatismuch of the DOM is refrac- mined tory to degradation. Although DOM a huge resource, rivalling The recent large-scale shotgun sequencing of seawater DNA is pro- viding much higher resolution 16S rRNA gene phylogenies and bio- * Vibrionaeceae CO2 as a carbon pool6 , chemists have been thwarted by atmospheric geographical distributions for marine microbial plankton. Although * Pseudoalteromonas DOM and have characterized it only in broad terms7. the complexity of the main purpose of Venter’s Sorcerer II expedition is to gather whole- Fibrobacter * Marinomonas The paragraphs above capture prominent features of the ocean genome shotgun sequence (WGS) data from planktonic microorgan- SAR406 * Halomonadacae but leave out the complex patternsand diversification of environment, of physical, chemical isms16, thousands of water-column rRNA genes are part of the and biological variation that drive the evolution by-catch. The first set of collections, from the Sargasso Sea, have Bacteroidetes * Colwellia microorganisms. For example, members of the genus Vibrio — which Figure 1 | Schematic illustration of the phylogeny of yielded 1,184 16S rRNA gene fragments. These data are shown in * Oceanospirillum of the most common planktonic bacteria that can be iso- include some Fig. 2, organized by clade structure. Such data are a rich scientific Marine Actinobacteria the major plankton clades. Black letters indicate lated on nutrient agar plates — readily grow anaerobically by fermen- resource for two reasons. First, they are not tainted by polymerase δ-Proteobacterialife cycles of some Vibrio species have been shown to tation. The microbial groups that seem to be ubiquitous in include anoxic stages in association with animal hosts, but the broad chain reaction (PCR) artefacts; PCR artefacts rarely interfere with the correct placement of genes in phylogenetic categories, but they are a Cyanobacteria seawater. Gold indicates groups found in the photic picture of their ecology in the oceans has barely been characterized8. major problem for reconstructing evolutionary patterns at the popu- Lentisphaerae * Marine Cluster A The story is similar for most of the microbial groups described below: lation level17. Second, the enormous number of genes provided by the * Lentisphaera araneosa (Synechococcus) zone. Blue indicates groups confined to the the phylogenetic map is detailed, but the ecological panorama is thinly Sorcerer II expedition is revealing the distribution patterns and abun- sketched. New information is rapidly flowing into the field from the dance of microbial groups that compose only a small fraction of the * Prochlorococcus sp. mesopelagic and surface waters during polar winters. Department of Microbiology, Oregon State University, Corvallis, Oregon 97331,indicates microbial groups associated with Green USA. Bacteria 1 coastal ocean ecosystems. ©2005 Nature Publishing Group 343 67 community. As discussed below, some opportunistic strains that cyanobacteria. As obligate phototrophs, these cyanobacteria are con- ! ! © !""# Nature Publishing Group! Monday, January 28, 13
  84. 84. facts17. They concluded that most sequence variation was clustered many microbia tions in the wat best example. T 35 entiated by the 30 adapted (high-b % of 16S rRNA sequences Phylogenetic e 25 gests that the h cally distinct lin 20 Cluster A Syne of which can b 15 characteristics urobilin)37,38. S 10 ample support teristics that aff 5 SS120 has a mu 0 ammonium an ) II Ib n e r) tes ia) ria nas ia) era de xi) extreme, Synec ria up kto lad cte + e r e r la e Ia acte gro lan a C ba id cte act mo cte eim r c rofl nitrate, cyanate s i o ro a b o a h e o oup eob sub ytop cter ibr cte eob tino lter eob ein act Chl interesting to n r t bg Pro AR1 op ob 1 h a (F Ba rot Ac doa rot Rh eob 2 ( u - c e 0 6 P δ- rine seu (α- P s Ro R2 0 seem to prospe 1 1 s (γ S Pi rot R4 ( a AR R8 6 e P SA 4 M /P 6 SA whereby nutrie S A a rin α- 32 as R11 S M red AR on SA conditions. Th tu S om c ul ter seasonal specia Un Al lular cyanobact Phylogenetic clade The observa 68Monday, January 28, 13 diverged into e
  85. 85. Delong GENOMIC FRAGMENTS FROM PLANKTONIC MARINE ARCHAEA Lab 593ments isolated from fosmid clones with various restriction endonucle-10 kb, the F-factor-based vector the fosmid subfragments. Partial of restriction enzyme to 1 ⇥g of mixture. The reaction mixture was removed at 10, 40, and 60 min.dding 1 ⇥l of 0.5 M EDTA to thee. The partially digested DNA was s described above except using a 1-he sizes of the separated fragmentsn standards. The distances of thed SP6 promoter sites on the excised pmol of T7- or SP6-specific oligo- l) and hybridizing with Southern fosmid and pBAC clones digested probed with labeled T7 and SP6eled subclones and PCR fragments otgun sequencing described above.e estimates from the partial diges-of the fosmids and their subclones. and DeSoete distance (9) analyses n using GDE 2.2 and Treetool 1.0, (RDP) (23). DeSoete least squares D ownloaded from jb.asm .org at U N IV O F Cng pairwise evolutionary distances, to account for empirical base fre- tained from the RDP, version 4.0u rRNA sequences were performed the RDP. For distance analyses of lutionary distances were estimatedd tree topology was inferred by then addition and global branch swap-protein sequences, the Phylip pro- addition and ordinary parsimony FIG. 1. Flowchart depicting the construction and screening of an environ- artial sequences reported in Table mental library from a mixed picoplankton sample. MW, molecular weight; the following accession numbers: PFGE, pulsed-field gel electrophoresis.U40243, U40244, and U40245. Theand EF2 have been submitted toand U41261. 69 Recombinant fosmids, each containing ca. 40 kb of pico- Monday, January 28, 13
  86. 86. Delong Lab J. BACTERIOL. FIG. 4. High-density filter replica of 2,304 fosmid clones containing approx- imately 92 million bp of DNA cloned from the mixed picoplankton community. The filter was probed with the labeled insert from clone 4B7 (dark spot). The lack of other hybridizing clones suggests that contigs of 4B7 are absent from this D ownloaded f portion of the library. Similar experiments with the remainder of the library yielded similar results. 70Monday, January 28, 13
  87. 87. l gene own transducer of light stimuli [for example, the kinetics of its photochemical reaction cy- leDelong Lab ge- Htr (22, 23)]. Although sequence analysis of cle. The transport rhodopsins (bacteriorho- iden- proteorhodopsin shows moderate statistical dopsins and halorhodopsins) are character- roteo- support for a specific relationship with sen- ized by cyclic photochemical reaction se- fromopsinsferent.hereas philes r than rmine l, wea coli pres- rotein 3A). nes ofpopro-m was (Fig.at 520 band- erated odop-nce of dth is 71 rption January 28, 13 Monday,
  88. 88. generated D ownloaded from w Delong Lab eorhodop-resence ofndwidth isabsorption. The red- nm in theated Schiffably to the on was de-s in a cellward trans- in proteor-nd only in (Fig. 4A).edium wasce of a 10re carbonyl19). Illumi-ical poten- right-side-nce of reti-light onsethat proteo- capable of Fig. 1. (A) Phylogenetic tree of bacterial 16S rRNA gene sequences, including that encoded on the physiolog- 130-kb bacterioplankton BAC clone (EBAC31A08) (16). (B) Phylogenetic analysis of proteorhodop- sin with archaeal (BR, HR, and SR prefixes) and Neurospora crassa (NOP1 prefix) rhodopsins (16).e activities Nomenclature: Name_Species.abbreviation_Genbank.gi (HR, halorhodopsin; SR, sensory rhodopsin; containing BR, bacteriorhodopsin). Halsod, Halorubrum sodomense; Halhal, Halobacterium salinarum (halo- proteorho- bium); Halval, Haloarcula vallismortis; Natpha, Natronomonas pharaonis; Halsp, Halobacterium sp;main to be Neucra, Neurospora crassa. 72 www.sciencemag.org Monday, January 28, 13 SCIENCE VOL 289 15 SEPTEMBER 2000 1903
  89. 89. 73Monday, January 28, 13
  90. 90. Figure 3. Phylogenetic tree based on the amino acid sequences of 25 archaeal rhodopsins. (a) NJ-tree. The numbers at each node are clusteringprobabilities generated by bootstrap resampling 1000 times. D1 and D2 represent gene duplication points. The four shaded rectangles indicate thespeciation dates when halobacteria speciation occurred at the genus level. (b) ML-tree. Log likelihood value for ML-tree was −6579.02 (bestscore) and that for topology of the NJ-tree was −6583.43. The stippled bars indicate the 95% confidence limits. Both trees were tentatively rootedat the mid-point of the longest distance, although true root positions are unknown.From Ihara et al. 1999 74Monday, January 28, 13
  91. 91. RESEARCH ARTICLES Fig. 2. Secondary structure of proteo- rhodopsin. Single- letter amino acid codes are used (33), and the numbering is as in bacteriorho- dopsin. Predicted retinal binding pock- et residues are marked in red. 75Monday, January 28, 13
  92. 92. duce in th occu pigm and t ed at tiona sorpt in 0. sorpt botto nated retin ms d deca shift appe term cay o step singl upwa Fig. 3. (A) Proteorhodopsin-expressing E. coli cell suspension (ϩ) compared to control cells (Ϫ), both with all-trans retinal. (B) Absorption spectra of retinal-reconstituted proteorhodopsin in E. coli ampl membranes (17). A time series of spectra is shown for reconstituted proteorhodopsin membranes gene (red) and a negative control (black). Time points for spectra after retinal addition, progressing from with low to high absorbance values, are 10, 20, 30, and 40 min. ms p recov phot prod 76Monday, January 28, 13 this

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