Phylogenomic Case Studies: The Benefits (and Occasional Drawbacks) of Integra...
Eisen Lecture for Ian Korf genomics course
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
1
Monday, January 28, 13
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
2
Monday, January 28, 13
3. Era I: rRNA Tree of Life
Era I:
rRNA Tree of Life
3
Monday, January 28, 13
4. Ernst Haeckel 1866
Plantae
Protista
Animalia
4
www.mblwhoilibrary.org
Monday, January 28, 13
5. Whittaker – Five Kingdoms 1969
Monera
Protista
Plantae
Fungi
Animalia
5
Monday, January 28, 13
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. Woese and Fox
• Propose “three aboriginal lines of descent”
Eubacteria
Archaebacteria
Urkaryotes
Monday, January 28, 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
13
Monday, January 28, 13
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
14
Monday, January 28, 13
15. The Tree of Life
2006
adapted from Baldauf, et al., in Assembling the Tree of Life, 2004 15
Monday, January 28, 13
16. The Tree of Life
2006
adapted from Baldauf, et al., in Assembling the Tree of Life, 2004
Monday, January 28, 13
17. Era II: rRNA in the Environment
Era II:
rRNA in the Environment
17
Monday, January 28, 13
34. Great Plate Count Anomaly
Culturing Microscopy
22
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35. Great Plate Count Anomaly
Culturing Microscopy
Count Count
23
Monday, January 28, 13
36. Great Plate Count Anomaly
Culturing Microscopy
Count <<<< Count
24
Monday, January 28, 13
37. Great Plate Count Anomaly
Problem because
appearance not
effective for “who
is out there?” or
“what are they
doing?”
Culturing Microscopy
Count <<<< Count
25
Monday, January 28, 13
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
26
Monday, January 28, 13
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
27
Monday, January 28, 13
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
29
Monday, January 28, 13
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
30
Monday, January 28, 13
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
31
Monday, January 28, 13
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
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 or
un 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’s
of 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
Mouth
om 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.0028132
ours 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
40
ortion 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 on
hanically 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 techniques
had 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 deposited
bility 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 community
rtions 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 gene
pathogens. 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 filters
hat 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, the
dence 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. Era III: Genome Sequencing
Era III:
Genome Sequencing
42
Monday, January 28, 13
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
44
Monday, January 28, 13
60. Network of Life
Bacteria
Archaea
Eukaryotes
Figure from Barton, Eisen et al.
“Evolution”, CSHL Press.
Based on tree from Pace NR, 2003.
48
Monday, January 28, 13
68. GEBA Lesson 1: rRNA utility in IDing novel genomes
From Wu et al. 2009 Nature 462, 1056-1060 56
Monday, January 28, 13
69. GEBA Lesson 2: rRNA Tree is not perfect
16s WGT, 23S
Badger et al. 2005 Int J System Evol Microbiol 55: 1021-1026. 57
Monday, January 28, 13
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
58
Monday, January 28, 13
71. GEBA Lesson 4 : Metadata Important
59
Monday, January 28, 13
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
61
Monday, January 28, 13
74. Wu et al. 2009 Nature 462, 1056-1060
62
Monday, January 28, 13
75. Wu et al. 2009 Nature 462, 1056-1060
62
Monday, January 28, 13
76. Wu et al. 2009 Nature 462, 1056-1060
62
Monday, January 28, 13
77. Wu et al. 2009 Nature 462, 1056-1060
62
Monday, January 28, 13
78. Wu et al. 2009 Nature 462, 1056-1060
62
Monday, January 28, 13
81. Era IV: Genomes in the environment
Era IV:
Genomes in the Environment
65
Monday, January 28, 13
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
66
Monday, January 28, 13
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
68
Monday, January 28, 13 diverged into e
85. Delong GENOMIC FRAGMENTS FROM PLANKTONIC MARINE ARCHAEA
Lab 593
ments 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 the
e. The partially digested DNA was
s described above except using a 1-
he sizes of the separated fragments
n standards. The distances of the
d 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 SP6
eled 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 C
ng pairwise evolutionary distances,
to account for empirical base fre-
tained from the RDP, version 4.0
u rRNA sequences were performed
the RDP. For distance analyses of
lutionary distances were estimated
d tree topology was inferred by the
n 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. The
and EF2 have been submitted to
and U41261. 69
Recombinant fosmids, each containing ca. 40 kb of pico-
Monday, January 28, 13
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.
70
Monday, January 28, 13
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-
from
opsins
ferent.
hereas
philes
r than
rmine
l, we
a coli
pres-
rotein
3A).
nes of
popro-
m was
(Fig.
at 520
band-
erated
odop-
nce of
dth is 71
rption January 28, 13
Monday,
88. generated
D ownloaded from w
Delong Lab
eorhodop-
resence of
ndwidth is
absorption
. The red-
nm in the
ated Schiff
ably to the
on was de-
s in a cell
ward trans-
in proteor-
nd only in
(Fig. 4A).
edium was
ce of a 10
re carbonyl
19). Illumi-
ical poten-
right-side-
nce of reti-
light onset
hat 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
90. Figure 3. Phylogenetic tree based on the amino acid sequences of 25 archaeal rhodopsins. (a) NJ-tree. The numbers at each node are clustering
probabilities generated by bootstrap resampling 1000 times. D1 and D2 represent gene duplication points. The four shaded rectangles indicate the
speciation dates when halobacteria speciation occurred at the genus level. (b) ML-tree. Log likelihood value for ML-tree was −6579.02 (best
score) and that for topology of the NJ-tree was −6583.43. The stippled bars indicate the 95% confidence limits. Both trees were tentatively rooted
at the mid-point of the longest distance, although true root positions are unknown.
From Ihara et al. 1999 74
Monday, January 28, 13
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.
75
Monday, January 28, 13
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
76
Monday, January 28, 13 this