peter carr 2/2/2013 bioinformatics challenge day this work is sponsored by the defense threat...
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Peter Carr
2/2/2013
Bioinformatics Challenge Day
This work is sponsored by the Defense Threat Reduction Agency under Air Force Contract #FA8721-05-C-0002. Opinions, interpretations, recommendations and conclusions are those of the authors and are not necessarily endorsed by the United States Government.
Bioinformatics Challenge Day -2Peter Carr 2/2/2013
Sponsor: Defense Threat Reduction Agency (DTRA)Organizer: MIT Lincoln Laboratory (MIT LL)
• Approach: A one day hack-a-thon– Innovate: tackle huge challenges in bioinformatics– Educate: bring in specialists from diverse fields,
participants in DoD bioinformatics interests– Investigate: what this short format can accomplish– Aggregate: bring people together
• The Challenges:– Can you determine the cause of an infection?– Can you invent a new way to visualize complex
bioinformatics data?– Can you spot the signs of genetic engineering? Can
you figure out what an engineered organism does?
Bioinformatics Challenge Days
The problem: drowning in complex data, very hard to make sense of it all
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Bioinformatics Challenge Day -3Peter Carr 2/2/2013
Cast of Characters
Darrell Ricke (MIT Lincoln Laboratory)– Bioinformatics
Peter Carr (MIT Lincoln Laboratory)– Synthetic Biology, Biochemistry
Anna Shcherbina (MIT Lincoln Laboratory)– Bioengineering, Electrical Engineering
Nancy Burgess (Defense Threat Reduction Agency)– Chemical and Biological Defense
Bioinformatics Challenge Day -4Peter Carr 2/2/2013
• Sequencing– Complete genome sequences– Mixed populations– Expression (RNA species)– Interaction (ChIP-seq)
• Mass spectroscopy– Protein/peptide fingerprinting– Metabolites– Interaction (cross-linking)
• Other tools– Microarrays– High-throughput screening
(e.g. fluorescence)
Some Big Hammers
Bioinformatics Challenge Day -5Peter Carr 2/2/2013
• Data galore: Omics approaches are generating massive amounts of increasingly complex measurement data
• How do we best make sense of this information?
• Some fundamental development areas– Processing
– Visualizing/analyzing
– Storing/accessing
Now and Future
Bioinformatics Challenge Day -6Peter Carr 2/2/2013
The Challenges
1. Metagenomic VisualDeveloping visualization methods to facilitate analysis of metagenomic data with unknown numbers of genomes at varying concentrations
2. Genome Assembly for the ClinicPerforming de novo assembly from clinical samples with an emphasis on pathogen identification
3. Genetic EngineeringID and interpret the signatures of genetic engineering
Bioinformatics Challenge Day -7Peter Carr 2/2/2013
What can your efforts today produce?
• Analysis, answers to questions
• Heuristics, algorithms
• Specific software tools
• Roadmap for future work
Bioinformatics Challenge Day -8Peter Carr 2/2/2013
What to get out of this?
• A deeper understanding of the field– Tools– Approaches– Concerns/challenges
• Ideas and experiences that may motivate future work
• Connection to others with similar interests
Bioinformatics Challenge Day -9Peter Carr 2/2/2013
Creativity (innovative ideas and efforts)
Energy(intensity and focus)
Communication(results, feedback)
What We Hope to See From You
Bioinformatics Challenge Day -10Peter Carr 2/2/2013
• You can work alone, come with a team, or team up on-site
• You can use any of the resources we have provided, any you have access to (including tools you code yourself ahead of time or today)
• You keep what you make (DTRA and MIT LL make no claims to what you produce)
Theme: Flexibility
Bioinformatics Challenge Day -11Peter Carr 2/2/2013
Schedule
8:00 AM Breakfast/check-in
9:00 AM Welcome (Pete)
9:15 AM Overview and logistics (Pete)
9:45 AM The Challenges:
1. Metagenomic Visual (Anna) 2. Genome Assembly for the Clinic (Darrell) 3. Genetic Engineering (Pete)
10:45 AM Coffee/Break into project groups
12:30 PM Lunch served (groups can continue to work)
3:30 PM Snack (groups can continue to work)
6:30 PM Progress updates ready by dinnertime
6:30 PM Dinner and progress reports
8:00 PM+ Groups can continue to work
Bioinformatics Challenge Day -12Peter Carr 2/2/2013
• On the USB sticks:– Data for the three challenges (FASTA, FASTQ, CSV)
– Software (Mac, Windows, Linux)
• Local wifi access
• Teaming
Getting Started
Bioinformatics Challenge Day -13Peter Carr 2/2/2013
Questions?
Bioinformatics Challenge Day -14Peter Carr 2/2/2013
• Background: a sample has been dug from the back of a lab freezer, and subjected to Ion Torrent sequencing
• We would like to know what it is:– Simple or complex?– Natural or engineered?– If engineered, how? (what techniques)– For what purpose?– Will the design work?
• [No surprise: yes, there is an (in silico) engineered component. Find it! And figure out as much as you can about it.]
• We have a lot of great questions, but may not have all the answers
Challenge 3: Genetic Engineering
Bioinformatics Challenge Day -15Peter Carr 2/2/2013
• Investigation (answer a biological question)
• Production (make a drug, a fuel)
• Serve a specialized role– Protect against infection– Detect dangerous chemicals– Environmental remediation
• Creatively explore an interesting design space
What Do We Design For?
Bioinformatics Challenge Day -16Peter Carr 2/2/2013
How Do We Produce These?
Bioinformatics Challenge Day -17Peter Carr 2/2/2013
• Transformation/transfection can be via natural, chemical, or electrical methods
Getting DNA In
Bioinformatics Challenge Day -18Peter Carr 2/2/2013
• Transfer “in vivo” protects fragile DNA
• An entire genome can be transferred
• Transfer to other species
• Requires an origin of replication, pilus protein
Old School: Conjugation
donor(sender)
recipient(receiver)
Bioinformatics Challenge Day -19Peter Carr 2/2/2013
Old School: Phage Transduction
• Phage/virus can replicate independently, or integrate into genome
• DNA or RNA, single- or double-stranded
• Examples:– Lentivirus (mammalian)– Lambda, T4, T7, P1, M13 (E. coli)
Bioinformatics Challenge Day -20Peter Carr 2/2/2013
• Natural mutation rates (mutations accumulate slowly over time)
• Exposure to damaging effects (chemicals, radiation)
• Mutator strains: cells defective for one or more natural repair mechanisms
Old School: Mutagenesis
Bioinformatics Challenge Day -21Peter Carr 2/2/2013
• Specific sites: often 6 bp, but can be longer or shorter
• “Outside cutters” cut some distance away from recognition site
• Homing nucleases (longer ~30 bp sites, can be unique in a genome)
• Multiple Cloning Site (MCS) often engineered into cloning vector
Revolution 1: Restriction Enzymes
Bioinformatics Challenge Day -22Peter Carr 2/2/2013
• Circular
• Contain origin of replication– Single copy– Low to high copy (hundreds)
• Selection gene (1 or more)
• MCS and other features common
• Extension: BACs and YACs
Plasmids
Bioinformatics Challenge Day -23Peter Carr 2/2/2013
• Almost all approaches give a mix of successes and failures
• Screening searches for what you want
• Selection kills off what you don’t want
Selection and Screening
Bioinformatics Challenge Day -24Peter Carr 2/2/2013
Polymerase Chain Reaction
• Simple scheme made it possible to manipulate DNA in new ways
• Used not just to make more DNA, but to modify it
• Dependent on oligonucleotide synthesis and enzyme (DNA polymerase)
Revolution 2: PCR
Bioinformatics Challenge Day -25Peter Carr 2/2/2013
• Perform on DNA in vitro (higher background error rates than in vivo)
• Employs a synthetic oligo and an enzyme (polymerase)
• Users typically screen clones with PCR or restriction, then sequencing
• Rest of the plasmid typically not re-sequenced
Site-Directed Mutagenesis
Bioinformatics Challenge Day -26Peter Carr 2/2/2013
• Can bring together many pieces of DNA at once
• Based on identical sequence overlaps
• 3-enyzme reaction
• Intrinsically scar-less
• Often relies on PCR (& thus oligos) to produce each segment
Gibson Assembly
http://www.youtube.com/watch?v=WCWjJFU1be8
Bioinformatics Challenge Day -27Peter Carr 2/2/2013
• “Outside cutter” restriction enzymes
• Little or no scar at joining point
• Segments may or may not be produced by PCR
Golden Gate Assembly
Bioinformatics Challenge Day -28Peter Carr 2/2/2013
Recombination
• Site-specific– attB (Gateway)– Cre/lox
• Homologous– Natural (B. Subtilis, RecA)– Engineered (lambda red)
• Directed by double-stranded break repair– Zn finger nucleases– TALENs– CRISPRs
Bioinformatics Challenge Day -29Peter Carr 2/2/2013
• Oligo synthesis (building blocks) using organic chemistry
• Assemble to genes using biochemistry (in vitro)
• Assemble to genomes (small ones for starters) using biology (in vivo)
• Each of these processes can carry their own error signature, but can also be counteracted by sequencing-based screening, post-repair, etc.
DNA Synthesis to Genome Assembly
Bioinformatics Challenge Day -30Peter Carr 2/2/2013
MAGE: Multiplexed Automatable Genome Engineering
Wang, Isaacs, Carr et al. (2009) Nature 460(7257):894-8
Generation of genome edits at many targeted chromosomal locations
Much like site-directed mutagenesis, but on a chromosome
Bioinformatics Challenge Day -31Peter Carr 2/2/2013
• A lot like site-directed mutagenesis—but on the genome of living cells
• Uses long oligos
• Does not require selection markers (but can use them)
• Other than the desired change (as small as a DNA base, as large as a multi-gene deletion) there is no obvious sign
• BUT there can be secondary signs:– Oligo-mediated defects within 50-100 bp of the edited site– Higher background mutation rates (mismatch repair deactivated)
MAGE
Bioinformatics Challenge Day -32Peter Carr 2/2/2013
• Conjugation now employed with controlled precision
• But DNA crossover points not always perfectly defined
CAGE: Conjugative Assembly Genome Engineering
Isaacs, Carr, Wang, ... (2011) Science
Bioinformatics Challenge Day -33Peter Carr 2/2/2013
• Make use of DNA “parts” libraries for constructing more advanced genetic designs
• Fundamental concept in synthetic biology, inspired by electrical engineering
• Basis of the iGEM competetion (International Genetically Engineered Machines)
Genetic Circuits: DNA Parts
Bioinformatics Challenge Day -34Peter Carr 2/2/2013
• Repressilator an early example of synthetic biology circuits
• Three inverters in series (circular) made a ring oscillator)
Genetic Circuits: Bacteria
Elowitz and Liebler (2000) Nature
Bioinformatics Challenge Day -35Peter Carr 2/2/2013
• Adapted a signaling system from plants
• Used to engineer communication between yeast cells
• Basic features can be installed in a variety of organisms
Genetic Circuits: Yeast
Chen and Weiss (2005) Nature Biotechnology
Bioinformatics Challenge Day -36Peter Carr 2/2/2013
Genetic Circuits: Mammalian
Xie et al. (2011) Science (Weiss, Benenson labs)
Genetic CircuitsOverview
DNA for classifier circuit
match
cell death
no match
no effect
cancer cellnormal
cell
Concept: insert DNA circuit into cells ID cancer and/or kill it
Bioinformatics Challenge Day -37Peter Carr 2/2/2013
• Codon usage– Adapt how often codons are used to match target organism– New amino acids (Tirrell, Schultz)– New genetic codes (Church, Carr)
• Minimal life– Engineering by subtraction (Blattner)– Compose from the ground up (Forster/Church)
• New DNA bases– Alternate hydrogen-bonding (Benner)– Hydrophobic bases (Schultz)
• Mirror-image life
Increasingly Alien
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