Title: Biology Blended with Math and Computer Science
1Biology Blended with Math and Computer Science
Reed College March 7, 2008
2DNA Microarrays windows into a functional
genome Opportunities for Undergraduate
Research
3How do microarrays work?
See the animation
4Open Source and Free Software
www.bio.davidson.edu/MAGIC
5How Can Microarrays be Introduced?
Wet-lab microarray simulation kit - fast, cheap,
works every time.
6How Can Students Practice?
www.bio.davidson.edu/projects/GCAT/Spot_synthesize
r/Spot_synthesizer.html
7What Else Can Chips Do?
Jackie Ryan 05
8Comparative Genome Hybridizations
9Synthetic Biology
10What is Synthetic Biology?
11BioBrick Registry of Standard Parts
http//parts.mit.edu/registry/index.php/Main_Page
12What is iGEM?
Peking University
Imperial College
13Davidson College Malcolm Campbell (bio.) Laurie
Heyer (math) Lance Harden Sabriya Rosemond
(HU) Samantha Simpson Erin Zwack
SYNTHETIC BIOLOGY iGEM 2006
Missouri Western State U. Todd Eckdahl
(bio.) Jeff Poet (math) Marian Broderick Adam
Brown Trevor Butner Lane Heard (HS student) Eric
Jessen Kelley Malloy Brad Ogden
14Burnt Pancake Problem
15Burnt Pancake Problem
16Look familiar?
17(No Transcript)
18How to Make Flippable DNA Pancakes
19Flipping DNA with Hin/hixC
20Flipping DNA with Hin/hixC
21Flipping DNA with Hin/hixC
22How to Make Flippable DNA Pancakes
All on 1 Plasmid Two pancakes (Amp vector) Hin
23Hin Flips DNA of Different Sizes
24Hin Flips Individual Segments
-2
1
25No Equilibrium 11 hrs Post-transformation
26Hin Flips Paired Segments
mRFP off
1
-2
double-pancake flip
mRFP on
2
-1
u.v.
white light
27Modeling to Understand Flipping
(-2,1)
(-2,-1)
( 1, -2) (-1, 2) (-2, 1) ( 2, -1)
(1,2)
(-1,2)
(1,-2)
(-1,-2)
(-1, -2) ( 2, 1)
(2,-1)
(2,1)
28Modeling to Understand Flipping
(-2,1)
(-2,-1)
( 1, -2) (-1, 2) (-2, 1) ( 2, -1)
(1,2)
(-1,2)
(1,-2)
(-1,-2)
(-1, -2) ( 2, 1)
(2,-1)
(2,1)
1 flip 0 solved
29Modeling to Understand Flipping
(-2,1)
(-2,-1)
( 1, -2) (-1, 2) (-2, 1) ( 2, -1)
(1,2)
(-1,2)
(1,-2)
(-1,-2)
(-1, -2) ( 2, 1)
(2,-1)
(2,1)
2 flips 2/9 (22.2) solved
30Success at iGEM 2006
31Time for another story?
32Living Hardware to Solve the Hamiltonian Path
Problem, 2007
Students Oyinade Adefuye, Will DeLoache, Jim
Dickson, Andrew Martens, Amber Shoecraft, and
Mike Waters Jordan Baumgardner, Tom Crowley,
Lane Heard, Nick Morton, Michelle Ritter, Jessica
Treece, Matt Unzicker, Amanda Valencia
Faculty Malcolm Campbell, Todd Eckdahl, Karmella
Haynes, Laurie Heyer, Jeff Poet
33The Hamiltonian Path Problem
1
4
3
2
5
34The Hamiltonian Path Problem
1
4
3
2
5
35Advantages of Bacterial Computation
Software
Hardware
Computation
Computation
Computation
36Advantages of Bacterial Computation
Software
Hardware
Computation
Computation
Computation
37Advantages of Bacterial Computation
of Processors
Cell Division
38Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
3
1
5
4
3
4
2
3
4
1
4
2
5
3
1
4
39Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
3
1
5
4
3
4
2
3
4
1
4
2
5
3
1
4
hixC Sites
40Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
41Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
1
4
3
2
5
42Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
1
4
3
2
5
43Using Hin/hixC to Solve the HPP
1
4
3
2
5
Solved Hamiltonian Path
44How to Split a Gene
Reporter
Detectable Phenotype
RBS
Promoter
?
Detectable Phenotype
RBS
Repo-
rter
hixC
Promoter
45Gene Splitter Software
http//gcat.davidson.edu/iGEM07/genesplitter.html
Input
Output
- 1. Generates 4 Primers (optimized
for Tm). - 2. Biobrick ends are added to primers.
- 3. Frameshift is eliminated.
1. Gene Sequence (cut and paste) 2. Where do
you want your hixC site? 3.
Pick an extra base to avoid a frameshift.
46Gene-Splitter Output
Note Oligos are optimized for Tm.
47Predicting Outcomes of Bacterial Computation
48Starting Arrangements
4 Nodes 3 Edges
Probability of HPP Solution
Number of Flips
49How Many Plasmids Do We Need?
Probability of at least k solutions on m plasmids
for a 14-edge graph
k actual number of occurrences ? expected
number of occurrences
? m plasmids solved permutations of edges
permutations of edges
Cumulative Poisson Distribution
P( of solutions k)
50False Positives
Extra Edge
1
4
3
2
5
51False Positives
PCR Fragment Length
1
4
3
2
5
PCR Fragment Length
52Detection of True Positives
Total of Positives
of Nodes / of Edges
of True Positives Total of Positives
of Nodes / of Edges
53How to Build a Bacterial Computer
54Choosing Graphs
D
A
B
Graph 2
55Splitting Reporter Genes
Green Fluorescent Protein
Red Fluorescent Protein
56Splitting Reporter Genes
GFP Split by hixC
RFP Split by hixC
57HPP Constructs
Graph 0 Construct
A
AB
B
Graph 0
Graph 1 Constructs
ABC
C
A
ACB
B
Graph 1
BAC
Graph 2 Construct
D
A
B
DBA
Graph 2
58Coupled Hin HPP Graph
PCR to Remove Hin Transform
Hin Unflipped HPP
Transformation
T7 RNAP
59Flipping Detected by Phenotype
ACB (Red)
BAC (None)
60Flipping Detected by Phenotype
Hin-Mediated Flipping
ACB (Red)
BAC (None)
61ABC Flipping
Yellow
Hin
62ACB Flipping
Red
Hin
63BAC Flipping
None
Hin
64Flipping Detected by PCR
ABC
ACB
BAC
BAC
ABC
ACB
Unflipped
Flipped
65Flipping Detected by PCR
ABC
ACB
BAC
BAC
ABC
ACB
Unflipped
Flipped
66Flipping Detected by Sequencing
BAC
RFP1 hixC
GFP2
67Flipping Detected by Sequencing
BAC
RFP1 hixC
GFP2
Hin
Flipped-BAC
RFP1 hixC
RFP2
68Conclusions
- Modeling revealed feasibility of our approach
- GFP and RFP successfully split using hixC
- Added 69 parts to the Registry
- HPP problems given to bacteria
- Flipping shown by fluorescence, PCR, and
sequence - Bacterial computers are working on the HPP and
may have solved it
69Living Hardware to Solve the Hamiltonian Path
Problem
Acknowledgements Thanks to The Duke Endowment,
HHMI, NSF DMS 0733955, Genome Consortium for
Active Teaching, Davidson College James G. Martin
Genomics Program, Missouri Western SGA,
Foundation, and Summer Research Institute, and
Karen Acker (DC 07). Oyinade Adefuye is from
North Carolina Central University and Amber
Shoecraft is from Johnson C. Smith University.
70What is the Focus?
71Thanks to my life-long collaborators
72(No Transcript)
73Extra Slides
74(No Transcript)
75Can we build a biological computer?The burnt
pancake problem can be modeled as DNA
(-2, 4, -1, 3)
(1, 2, 3, 4)
DNA Computer Movie gtgt
76Design of controlled flipping
RBS-mRFP (reverse)
hix
RBS-tetA(C)
hix
pLac
hix
77(No Transcript)