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Transcript
Mother of Green
Phylogenomics of the P. falciparum Apicoplast
Indiana Center for Insect Genomics
An International Center of Excellence
University of Notre Dame
Purdue University
Indiana University
Mother of Green
• Malaria causes 1.5 - 2.7 million deaths every year
• 3,000 children under age five die of malaria every day
•Plasmodium falciparum causes human malaria
• Drug resistance a world-wide problem
• Targeted drug design through phylogenomics
P. falciparum
Mother of Green
• P. falciparum has three genomes
Nuclear, mitochondrial, plastid
• Animals and insects have only two
• Target the third genome
• No harm to animals
• New antimalarial drug
• High risk, high tech, high payoff
J. Romero-Severson
Department of Biological Sciences
Greg Madey
Department of Computer Science
Mother of Green
•Plastids are the third genome
•Intracellular organelles
•Terrestrial plants, algae, apicomplexans
•Functions in plants and algae
Photosynthesis
Oxidation of water
Reduction of NADP
Synthesis of ATP
Fatty acid biosynthesis
Aromatic amino acid biosynthesis
•Functions in apicomplexans ?
Chloroplast in plant cell
plastid
Apicoplast in P. falciparum
Plastid in Toxoplasma sp.
Mother of Green
•The apicoplast appears to code for <30 proteins.
• Repair, replication and transcription proteins
•Why is the apicoplast essential?
Mother of Green
Phylogenomics
• Find the ancestors of the apicoplast
• Identify genes in the ancestors
• Determine gene function
• Look for these genes in the P. falciparum nucleus
• Then study regulatory mechanisms in candidate genes
Phylogenomics of plastids
• Very old lineage (> 2.5 billion years)
• Cyanobacterial ancestor
• Three main plastid lineages
Glaucophytes
Group of freshwater algae
Chloroplast resembles intact cyanobacteria
Chlorophytes
Green plant lineage
Chloroplast genome reduced
Many chloroplast genes now in nuclear genome
Rhodophytes
Red algal lineage
Chloroplast genome bigger than in green plants
Oomycetes
Apicomplexans
One plastid origin
Phylogenomics of plastids
• One cyanobacterial ancestor ?
• Many?
• Lineages are not linear
Multiple plastid origins
Nucleus
Primitive eukaryote
Endosymbiont
plastid
Cyanobacteria
Nucleus
Second
eukaryote
Nucleomorph
Secondary
endosymbionts
Secondary
nonphotosynthetic
endosymbiont
Plastid
disappears
The process of
endosymbiosis.
Horizontal Gene
Transfer (arrows)
from the plastid to
the nucleus.
The nucleomorph is a
remnant of the
original endosymbiont
nucleus.
Secondary
endosymbiont
Tertiary endosymbiosis.
Horizontal Gene Transfer
Third eukaryote
Tertiary
endosymbionts
Plastid disappears
Tertiary
nonphotosynthetic
endosymbiont
P. falciparum
The information gathering problem
• Rapid accumulation of raw sequence information
~100 sequenced chloroplast genomes
~55 sequenced cyanobacterial genomes
Rate of accumulation is increasing
Information accumulates faster than analyses finish
Information in forms not readily accessible
•
Solution
Semi-automated web-services
“Smart” web-services
The computational problem
•Phylogenetic trees
NP-hard
Poisoned by information conflict
•Phylogenies based on individual genes
Maximum likelihood models exist
Processes are parallelizable
Access to compute farms inadequate
RAW number-crunching power
Greedy
• Similar genealogies may be merged
Convergence not possible for all
Makes computational problem more daunting
Candidate genes for deep phylogeny
The synthesis of ATP
Light-dependent ATP synthesis (photophosphorylation)
Hypothesis:
Evolution of ATP synthase
severely constrained
Candidate for ascertainment of
deep phylogeny
1st: Individual subunit genealogy
2nd: Merge the data, reanalyze
ATP synthase
The wheel that powers life
Phylogenomics of the P. falciparum Apicoplast
•
•
•
•
•
•
•
•
Extract data from public and private databases
Web services
Choose a metric for sequence comparison
Megablast and others
Choose a method to infer genealogy
Maximum Likelihood (ML)
Develop a strategy to use ML that is feasible
fastDNAml and others
Create a computational infrastructure
Compute farms
Dedicated chunks of compute farms
Deal with management issues
Solve band width problems
Convince someone to fund this!
Indiana Center for Insect Genomics
Mission
Create genomics tools for high impact arthropods lacking such tools
Develop integrated bioinformatics programs for arthropod genomics
Develop specific projects with potential practical application
Foster high risk ideas with mini-grants
Jeanne Romero-Severson, Director
Frank Collins, Co-PI at University of Notre Dame
Peter Cherbas, Co-PI at Indiana University
Jeff Stuart, Co-PI at Purdue University