This document summarizes a talk given by Jonathan Eisen on his research areas related to microbial evolution and phylogenomics. His research focuses on 3 main areas: 1) studying the mechanisms by which new functions originate in genomes, 2) analyzing patterns, causes, and effects of variation in these mechanisms, and 3) investigating species evolution. His goal is to better understand differences in evolvability and improve predictions from genomic analysis.
Eisen JA (2007) Environmental Shotgun Sequencing: Its Potential and Challenges for Studying the Hidden World of Microbes. PLoS Biol 5(3): e82. doi:10.1371/journal.pbio.0050082
Experimenting with posting OpenAccess papers on Slideshare
The Toronto Region is a global leader in stem cell research. The region has a large concentration of research centres conducting high-impact, high-value research. More than 70 scientists and principal investigators focuson five broad areas: cancer stem cells, adult stem cells, embryonic stem cells, regenerative medicine, and bioengineering/tissue engineering.
Pressure BioSciences, Inc. Launches the Barocycler HUB440 A State-of-the-Art, High Pressure Generator (up to 56K psi) for Multiple Bioscience Applications
Find out more at: www.pressurebiosciences.com
Biotechnology Industry has changed a lot during last decade , which means moving ahead from traditional ways to more advanced technological developments
2012 Biotechnology Industry is not the same as it was in 2001
Eisen JA (2007) Environmental Shotgun Sequencing: Its Potential and Challenges for Studying the Hidden World of Microbes. PLoS Biol 5(3): e82. doi:10.1371/journal.pbio.0050082
Experimenting with posting OpenAccess papers on Slideshare
The Toronto Region is a global leader in stem cell research. The region has a large concentration of research centres conducting high-impact, high-value research. More than 70 scientists and principal investigators focuson five broad areas: cancer stem cells, adult stem cells, embryonic stem cells, regenerative medicine, and bioengineering/tissue engineering.
Pressure BioSciences, Inc. Launches the Barocycler HUB440 A State-of-the-Art, High Pressure Generator (up to 56K psi) for Multiple Bioscience Applications
Find out more at: www.pressurebiosciences.com
Biotechnology Industry has changed a lot during last decade , which means moving ahead from traditional ways to more advanced technological developments
2012 Biotechnology Industry is not the same as it was in 2001
Why is Evolution so hard to understand? Insights from implementing a human evolution case study in a technology-enhanced learning environment.
Abstract :: Many students leave school with a fragmented understanding of biology, which prohibits them from connecting scientific ideas to their everyday lives. Especially one of the core ideas of biology, the theory of evolution, has been found difficult to understand as it incorporates a wide range of ideas from different areas and often gets in conflict with existing contradictory ideas learners' bring to the classroom. Dr. Schwendimann developed an evolution curriculum, "Gene Pool Explorer", using the web-based inquiry science environment (WISE) that combines concept mapping and guided inquiry activities. The WISE curriculum used an example from human evolution as a case study. This talk will discuss the challenges of teaching and learning the theory of evolution and present findings from implementing the WISE "Gene Pool Explorer" curriculum in authentic science classroom environments.
Evolutionary Genetics by: Kim Jim F. Raborar, RN, MAEd(ue)Kim Jim Raborar
This presentation was created as a partial fulfillment of the requirements in the subject Advanced Genetics. Everything that was here were kinda symbolic. I mean, you could recognize that this was a product of so much data interpretation. I therefore suggest you read and read a lot first before you go back to this presentation. Or you could just contact me so i could send you the key-pointers.
Have a super nice day.
Kimy
Molecular pathology in microbiology and metagenomicsCharithRanatunga
INTRODUCTION
HISTORY
Steps
Analysis
Metagenomic Process
Sequence-based analysis
Function-based analysis
Application of metagenomics
Future Directions of metagenomics
Examples for metagenomics projects
Molecular evolution, four class of chromosomal mutation, Negative Selection and Positive Selection, Mutations in DNA and protein, Neutral Theory of Molecular Evolution, Evidence supporting neutral evolution, Phylogenetic trees, Methods of Tree reconstruction
Innovations in Sequencing & Bioinformatics
Talk for
Healthy Central Valley Together Research Workshop
Jonathan A. Eisen University of California, Davis
January 31, 2024 linktr.ee/jonathaneisen
Why is Evolution so hard to understand? Insights from implementing a human evolution case study in a technology-enhanced learning environment.
Abstract :: Many students leave school with a fragmented understanding of biology, which prohibits them from connecting scientific ideas to their everyday lives. Especially one of the core ideas of biology, the theory of evolution, has been found difficult to understand as it incorporates a wide range of ideas from different areas and often gets in conflict with existing contradictory ideas learners' bring to the classroom. Dr. Schwendimann developed an evolution curriculum, "Gene Pool Explorer", using the web-based inquiry science environment (WISE) that combines concept mapping and guided inquiry activities. The WISE curriculum used an example from human evolution as a case study. This talk will discuss the challenges of teaching and learning the theory of evolution and present findings from implementing the WISE "Gene Pool Explorer" curriculum in authentic science classroom environments.
Evolutionary Genetics by: Kim Jim F. Raborar, RN, MAEd(ue)Kim Jim Raborar
This presentation was created as a partial fulfillment of the requirements in the subject Advanced Genetics. Everything that was here were kinda symbolic. I mean, you could recognize that this was a product of so much data interpretation. I therefore suggest you read and read a lot first before you go back to this presentation. Or you could just contact me so i could send you the key-pointers.
Have a super nice day.
Kimy
Molecular pathology in microbiology and metagenomicsCharithRanatunga
INTRODUCTION
HISTORY
Steps
Analysis
Metagenomic Process
Sequence-based analysis
Function-based analysis
Application of metagenomics
Future Directions of metagenomics
Examples for metagenomics projects
Molecular evolution, four class of chromosomal mutation, Negative Selection and Positive Selection, Mutations in DNA and protein, Neutral Theory of Molecular Evolution, Evidence supporting neutral evolution, Phylogenetic trees, Methods of Tree reconstruction
Innovations in Sequencing & Bioinformatics
Talk for
Healthy Central Valley Together Research Workshop
Jonathan A. Eisen University of California, Davis
January 31, 2024 linktr.ee/jonathaneisen
Thoughts on UC Davis' COVID Current ActionsJonathan Eisen
Slides I used for a presentation to Chancellor May's leadership council about the current state of UC Davis' response to COVID and how it could be improved
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
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Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
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Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
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Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
4. Social Networking in Science
HOME PAGE MY TIMES TODAY'S PAPER VIDEO MOST POPULAR TIMES TOPICS Welcome, fcollins Member Center Log Out
Sunday, April 1, 2007 Health
WORLD U.S. N.Y. / REGION BUSINESS TECHNOLOGY SCIENCE HEALTH SPORTS OPINION ARTS STYLE TRAVEL JOBS REAL ESTATE AUTOS
FITNESS & NUTRITION HEALTH CARE POLICY MENTAL HEALTH & BEHAVIOR
Scientist Reveals Secret of the Ocean: It's Him
By NICHOLAS WADE
Published: April 1, 2007
PRINT nytimes.com/sports
Maverick scientist J. Craig Venter has done it again. It was just a few years SINGLE-PAGE
ago that Dr. Venter announced that the human genome sequenced by Celera
SAVE
Genomics was in fact, mostly his own. And now, Venter has revealed a second
SHARE
twist in his genomic self-examination. Venter was discussing his Global
SHARE
Ocean Voyage, in which he used his personal yacht to collect ocean water
samples from around the world. He then used large filtration units to collect How good is your bracket? Compare your tournament picks
to choices from members of The New York Times sports
microbes from the water samples which were then brought back to his high desk and other players.
tech lab in Rockville, MD where he used the same methods that were used to Also in Sports:
The Bracket Blog - all the news leading up to the Final
sequence the human genome to study the genomes of the 1000s of ocean Four
dwelling microbes found in each sample. In discussing the sampling methods, Venter let slip his Bats Blog: Spring training updates
Play Magazine: How to build a super athlete
latest attack on the standards of science – some of the samples were in fact not from the ocean, but
were from microbial habitats in and on his body.
“The human microbiome is the next frontier,” Dr. Venter said. “The ocean voyage was just a cover.
My main goal has always been to work on the microbes that live in and on people. And now that my
genome is nearly complete, why not use myself as the model for human microbiome studies as well.
”
It is certainly true that in the last few years, the microbes that live in and on people have become a
hot research topic. So hot that the same people who were involved in the race to sequence the human
genome have been involved in this race too. Francis Collins, Venter main competitor and still the
Friday, January 28, 2011
director of the National Human Genome Research Institute (NHGRI), recently testified before
7. Research Areas
Mechanisms of
Origin of New
Functions
Friday, January 28, 2011
8. Research Areas
Mechanisms of Variation in
Origin of New Mechanisms:
Functions Patterns, Causes
and Effects
Friday, January 28, 2011
9. Research Areas
Mechanisms of Variation in
Origin of New Mechanisms:
Functions Patterns, Causes
and Effects
Species Evolution
Friday, January 28, 2011
10. Research Areas
• Study the evolution of function
• Make extensive use of genome
sequence data
• Requires integration of
experimental information and
genome analysis
• Categorize and classify ways
that novelty originates (examples)
• Duplication and divergence
• Recombination
• Simple substitutions
• Gene transfer
Friday, January 28, 2011
11. Research Areas
• Study the evolution of function
• Make extensive use of genome
Mechanisms of sequence data
Origin of New • Requires integration of
Functions experimental information and
genome analysis
• Categorize and classify ways
that novelty originates (examples)
• Duplication and divergence
• Recombination
• Simple substitutions
• Gene transfer
Friday, January 28, 2011
12. Research Areas
• Patterns of variation
• Within species
• Between species
• Comparative genomics plays
important role
• Causes
• Variation in RRR
• Regulatory complexity
• Effects
• Differences in evolvability
• Ecological niche
• Short and long term genome
evolution
Friday, January 28, 2011
13. Research Areas
• Patterns of variation
• Within species Variation in
• Between species Mechanisms:
• Comparative genomics plays Patterns, Causes
important role and Effects
• Causes
• Variation in RRR
• Regulatory complexity
• Effects
• Differences in evolvability
• Ecological niche
• Short and long term genome
evolution
Friday, January 28, 2011
14. Research Areas
• Information needed to distinguish convergence from
homology
• Allows inference of rates and patterns of change
• Allows one to determine if something is a “one time” event
or a common theme in many lineages
Friday, January 28, 2011
15. Research Areas
• Information needed to distinguish convergence from
homology
• Allows inference of rates and patterns of change
• Allows one to determine if something is a “one time” event
or a common theme in many lineages
Species Evolution
Friday, January 28, 2011
16. Phylogenomics of Novelty
Variation in
Mechanisms of
Mechanisms:
Origin of New
Patterns, Causes
Functions
and Effects
Species Evolution
Friday, January 28, 2011
17. Why do this?
• Discover causes and effects of differences in
evolvability
• Improve predictions from genome analysis
• Guide interpretation of biological dat
Friday, January 28, 2011
18. My microbial evolution obsessions
• Introduction
• Phylogenomic Stories
– Within genome invention of novelty
– Stealing novelty
– Community service
Friday, January 28, 2011
19. Introduction
Genome Sequencing
Friday, January 28, 2011
28. Origin of New Functions
• Many different processes
contribute to the origin of novelty
• Denovo invention of new
genes
• Simple substitutions within
existing genes
• Duplication and divergence
• Domain swapping
• Genome rearrangements
• Regulatory changes
Friday, January 28, 2011
29. Origin of New Functions
• Many different processes
contribute to the origin of novelty
Mechanisms of • Denovo invention of new
Origin of New genes
Functions • Simple substitutions within
existing genes
• Duplication and divergence
• Domain swapping
• Genome rearrangements
• Regulatory changes
Friday, January 28, 2011
30. Phylogenomics of Novelty
Variation in
Mechanisms of
Mechanisms:
Origin of New
Patterns, Causes
Functions
and Effects
Species Evolution
Friday, January 28, 2011
31. Example I:
Mutation Rates and Functional
Predictions
Friday, January 28, 2011
32. From Eisen et al.
1997 Nature
Medicine 3:
1076-1078.
Friday, January 28, 2011
33. 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.
Friday, January 28, 2011
34. MutL??
Based on Eisen et al. 1997 Nature Medicine 3: 1076-1078.
Friday, January 28, 2011
35. Phylogenetic Tree of MutS Family
Aquae
Strpy
Bacsu
Synsp
Deira Helpy
Yeast
Human Borbu Metth
Celeg
mSaco
Yeast
Human Yeast
Mouse
Arath Celeg
Human
Arath
Human
Mouse
Spombe Fly
Yeast Xenla
Rat
Mouse
Yeast Human
Spombe Yeast
Neucr
Arath
Aquae Trepa
Chltr
DeiraTheaq
Thema BacsuBorbu Based on Eisen,
SynspStrpy 1998 Nucl Acids
Ecoli
Neigo Res 26: 4291-4300.
Friday, January 28, 2011
36. MutS Subfamilies
MSH5 MutS2
Aquae
Strpy
Bacsu
Synsp
Deira Helpy
Yeast
Human Borbu Metth
Celeg
mSaco
MSH6 Yeast
Human
Mouse
Arath
Yeast MSH4
Celeg
Human
Arath
Human
MSH3 Mouse
Fly
Spombe
Yeast Xenla
Rat
Mouse
Yeast
MSH1 Spombe
Human
Yeast
MSH2
Neucr
Arath
Aquae Trepa
Chltr
DeiraTheaq
BacsuBorbu
Thema
SynspStrpy
Ecoli
Neigo Based on Eisen,
1998 Nucl Acids
MutS1
Res 26: 4291-4300.
Friday, January 28, 2011
37. MutS Subfamilies
• MutS1
Bacterial MMR
• MSH1
Euk - mitochondrial MMR
• MSH2
Euk - all MMR in nucleus
• MSH3
Euk - loop MMR in nucleus
• MSH6
Euk - base:base MMR in nucleus
• MutS2
Bacterial - function unknown
• MSH4
Euk - meiotic crossing-over
• MSH5
Euk - meiotic crossing-over
Friday, January 28, 2011
38. 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.
Friday, January 28, 2011
39. Functional Prediction Using Tree
MSH5 - Meiotic Crossing Over MutS2 - Unknown Functions
Aquae
Strpy
Bacsu
Synsp
Deira Helpy
Yeast
Human Borbu Metth
Celeg
MSH6 - Nuclear mSaco
Repair
Of Mismatches Yeast
Human MSH4 - Meiotic Crossing
Mouse Yeast Over
Arath Celeg
Human
Arath
MSH3 - Nuclear Human
Mouse
RepairOf Loops Spombe Fly
Yeast Xenla
Rat
Mouse MSH2 - Eukaryotic Nuclear
Yeast Human Mismatch and Loop Repair
MSH1 Spombe Yeast
Mitochondrial Neucr
Arath
Repair
Aquae Trepa
Chltr
DeiraTheaq
BacsuBorbu
Thema
SynspStrpy
Ecoli Based on Eisen,
Neigo
1998 Nucl Acids
MutS1 - Bacterial Mismatch and Loop Repair Res 26: 4291-4300.
Friday, January 28, 2011
46. Tetrahymena Genome Processing
• Probably exists as a defense mechanism
• Analogous to RIPPING and
heterochromatin silencing
• Presence of repetitive DNA in MAC but
not TEs suggests the mechanism involves
targeting foreign DNA
• Thus unlike RIPPING ciliate processing
does not limit diversification by duplication
Eisen et al. 2006. PLoS Biology.
Friday, January 28, 2011
47. Phylogenomics of Novelty II
Sometimes, it is easier to steal, borrow, or
coopt functions rather than evolve them
anew
Friday, January 28, 2011
49. rRNA Tree of Life
Bacteria
Archaea
Eukaryotes
FIgure from Barton, Eisen et al.
“Evolution”, CSHL Press.
Based on tree from Pace NR, 2003.
Friday, January 28, 2011
51. Network of Life
Bacteria
Archaea
Eukaryotes
Figure from Barton, Eisen et al.
“Evolution”, CSHL Press.
Based on tree from Pace NR, 2003.
Friday, January 28, 2011
52. Non homology functional prediction
methods
• Many genes have homologs in other species
but no homologs have ever been studied
experimentally
• Non-homology methods can make
functional predictions for these
• Example: phylogenetic profiling
Friday, January 28, 2011
53. Phylogenetic profiling basis
• 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
Friday, January 28, 2011
54. 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)
Friday, January 28, 2011
55. 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. )
Friday, January 28, 2011
83. rRNA phylotyping issues
• Massive amounts of data
– 1 x 10^6 new partial sequences with new 454
– 2 x 10^6 full length sequences in DB
• Alignments of new sequences not always
straightforward
• Solutions:
– Reliance on similarity scores (bad)
– High throughput automated phylogenetic tools
• STAP
• WATERs
Friday, January 28, 2011
84. rRNA: A Phylogenetic Anchor to
Determine Who’s Out There
Eisen et
al. 1992
Friday, January 28, 2011
85. rRNA: A Phylogenetic Anchor to
Determine Who’s Out There
Eisen et
al. 1992
Friday, January 28, 2011
86. rRNA: A Phylogenetic Anchor to
Determine Who’s Out There
Eisen et
al. 1992
Friday, January 28, 2011
87. rRNA: A Phylogenetic Anchor to
Determine Who’s Out There
Biology not Eisen et
similar enough al. 1992
Friday, January 28, 2011
91. 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
Friday, January 28, 2011
93. Weighted % of Clones
0
0.1250
0.2500
0.3750
0.5000
Al
ph
ap
ro
t eo
Be b ac
ta
pr t er
ot
e ia
G ob
am ac
Friday, January 28, 2011
m t er
ap ia
ro
Ep te
si ob
lo ac
np t er
ro ia
De t eo
lta b ac
pr te
ot ria
eo
b
C ac
ya ter
n ob ia
ac
t er
Fi ia
rm
ic
u te
Ac s
tin
ob
ac
t er
C ia
hl
or
ob
i
C
FB
Major Phylogenetic Group
Sargasso Phylotypes
C
hl
or
ofl
xi e
Sp
iro
ch
ae
te
Fu
so s
De ba
in ct
er
oc ia
oc
cu
s-
Eu The
ry r
ar mu
ch s
ae
C ot
re a
na
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
106. Commonly Used Binning Methods
Did not Work Well
• Assembly
– Only Baumannia generated good contigs
• Depth of coverage
– Everything else 0-1X coverage
• Nucleotide composition
– No detectible peaks in any vector we looked at
Friday, January 28, 2011
108. Binning by Phylogeny
• Four main “phylotypes”
– Gamma proteobacteria (Baumannia)
– Arthropoda (sharpshooter)
– Bacteroidetes (Sulcia)
– Alpha-proteobacteria (Wolbachia)
Friday, January 28, 2011
109. Binning by Phylogeny
• Four main “phylotypes”
– Gamma proteobacteria (Baumannia)
– Arthropoda (sharpshooter)
– Bacteroidetes (Sulcia) - only a.a. genes here
– Alpha-proteobacteria (Wolbachia)
Friday, January 28, 2011
110. Wu et al. 2006 PLoS Biology 4: e188.
Friday, January 28, 2011
111. Essential Amino Acid Synthesis
Wu et al. 2006 PLoS
Biology 4: e188.
Friday, January 28, 2011
112. Sulcia makes amino acids
Baumannia makes vitamins and cofactors
Wu et al. 2006 PLoS Biology 4: e188.
Friday, January 28, 2011