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Biology Blended with Math and Computer Science

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Andrew Martens, Amber Shoecraft, and Mike Waters; Jordan Baumgardner, Tom ... Heard, Nick Morton, Michelle Ritter, Jessica Treece, Matt Unzicker, Amanda Valencia ... – PowerPoint PPT presentation

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Title: Biology Blended with Math and Computer Science


1
Biology Blended with Math and Computer Science
  • Malcolm Campbell

Reed College March 7, 2008
2
DNA Microarrays windows into a functional
genome Opportunities for Undergraduate
Research
3
How do microarrays work?
See the animation
4
Open Source and Free Software
www.bio.davidson.edu/MAGIC
5
How Can Microarrays be Introduced?
Wet-lab microarray simulation kit - fast, cheap,
works every time.
6
How Can Students Practice?
www.bio.davidson.edu/projects/GCAT/Spot_synthesize
r/Spot_synthesizer.html
7
What Else Can Chips Do?
Jackie Ryan 05
8
Comparative Genome Hybridizations
9
Synthetic Biology
10
What is Synthetic Biology?
11
BioBrick Registry of Standard Parts
http//parts.mit.edu/registry/index.php/Main_Page
12
What is iGEM?
Peking University
Imperial College
13
Davidson 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
14
Burnt Pancake Problem
15
Burnt Pancake Problem
16
Look familiar?
17
(No Transcript)
18
How to Make Flippable DNA Pancakes
19
Flipping DNA with Hin/hixC
20
Flipping DNA with Hin/hixC
21
Flipping DNA with Hin/hixC
22
How to Make Flippable DNA Pancakes
All on 1 Plasmid Two pancakes (Amp vector) Hin
23
Hin Flips DNA of Different Sizes
24
Hin Flips Individual Segments
-2
1
25
No Equilibrium 11 hrs Post-transformation
26
Hin Flips Paired Segments
mRFP off
1
-2
double-pancake flip
mRFP on
2
-1
u.v.
white light
27
Modeling to Understand Flipping
  • ( 1, 2)
  • (-2, -1)

(-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)
28
Modeling to Understand Flipping
  • ( 1, 2)
  • (-2, -1)

(-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
29
Modeling to Understand Flipping
  • ( 1, 2)
  • (-2, -1)

(-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
30
Success at iGEM 2006
31
Time for another story?
32
Living 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
33
The Hamiltonian Path Problem
1
4
3
2
5
34
The Hamiltonian Path Problem
1
4
3
2
5
35
Advantages of Bacterial Computation
Software
Hardware
Computation
Computation
Computation
36
Advantages of Bacterial Computation
Software
Hardware
Computation

Computation

Computation
37
Advantages of Bacterial Computation
  • Non-Polynomial (NP)
  • No Efficient Algorithms

of Processors
Cell Division
38
Using 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
39
Using 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
40
Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
41
Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
1
4
3
2
5
42
Using Hin/hixC to Solve the HPP
Using Hin/hixC to Solve the HPP
1
4
3
2
5
43
Using Hin/hixC to Solve the HPP
1
4
3
2
5
Solved Hamiltonian Path
44
How to Split a Gene
Reporter
Detectable Phenotype
RBS
Promoter
?
Detectable Phenotype
RBS
Repo-
rter
hixC
Promoter
45
Gene 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.
46
Gene-Splitter Output
Note Oligos are optimized for Tm.
47
Predicting Outcomes of Bacterial Computation
48
Starting Arrangements
4 Nodes 3 Edges
Probability of HPP Solution
Number of Flips
49
How 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)
50
False Positives
Extra Edge
1
4
3
2
5
51
False Positives
PCR Fragment Length
1
4
3
2
5
PCR Fragment Length
52
Detection of True Positives
Total of Positives
of Nodes / of Edges
of True Positives Total of Positives
of Nodes / of Edges
53
How to Build a Bacterial Computer
54
Choosing Graphs
D
A
B
Graph 2
55
Splitting Reporter Genes
Green Fluorescent Protein
Red Fluorescent Protein
56
Splitting Reporter Genes
GFP Split by hixC
RFP Split by hixC
57
HPP 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
58
Coupled Hin HPP Graph
PCR to Remove Hin Transform
Hin Unflipped HPP
Transformation
T7 RNAP
59
Flipping Detected by Phenotype
ACB (Red)
BAC (None)
60
Flipping Detected by Phenotype
Hin-Mediated Flipping
ACB (Red)
BAC (None)
61
ABC Flipping
Yellow
Hin
62
ACB Flipping
Red
Hin
63
BAC Flipping
None
Hin
64
Flipping Detected by PCR
ABC
ACB
BAC
BAC
ABC
ACB
Unflipped
Flipped
65
Flipping Detected by PCR
ABC
ACB
BAC
BAC
ABC
ACB
Unflipped
Flipped
66
Flipping Detected by Sequencing
BAC
RFP1 hixC
GFP2
67
Flipping Detected by Sequencing
BAC
RFP1 hixC
GFP2
Hin
Flipped-BAC
RFP1 hixC
RFP2
68
Conclusions
  • 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

69
Living 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.
70
What is the Focus?
71
Thanks to my life-long collaborators
72
(No Transcript)
73
Extra Slides
74
(No Transcript)
75
Can 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
76
Design of controlled flipping
RBS-mRFP (reverse)
hix
RBS-tetA(C)
hix
pLac
hix
77
(No Transcript)
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