Synthetic Biology

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Synthetic Biology Microbial Biofuels
George Church, MIT/Harvard DOE GtL Center DuPont
13-Sep-2006
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Our DOE Biofuels Center goals strengths

• 1. Basic enabling technologies omics, models,
• genome synthesis, evolution, sequencing
• 2. Harnessing new insights from ecosystems.
• 3. Improving photosynthetic and conversion
  efficiencies.
• 4. Fermentative production of alcohols
  biodiesel.

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Synthetic Biology Engineering Research Center
(SynBERC) 16M NSF, IGEM
UC-Berkeley, Harvard, MIT, UCSF Keasling, Lim,
Endy, Church, Prather, Voigt, Knight Parts,
Devices, Chassis, Thrust in biochemical
engineering Stress parasite resistance
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Engineering a mevalonate pathway in Escherichia
coli for production of terpenoids. Martin VJ, et
al. Nat. Biotech 2003
Production of the antimalarial drug precursor
artemisinic acid in engineered yeast. Ro DK, et
al. Nature. 2006 8
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Programmable ligand-controlled riboregulators to
monitor metabolites.
OFF
ON
ON
Bayer Smolke Isaacs Collins 2005 Nature
Biotech.
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Genome Metabolome Computer Aided Design (CAD)

• 4.7 Mbp new genetic codes new amino acids
• 77 4.7 Mbp mini-ecosystems
• biosensors, bioenergy, high
  secretors,
• DNA
  metabolic isolation
• Top Design Utility, safety
  scalability
• CAD-PAM
• Synthesis (chip error correction)
• Combinatorics
• Evolution
• Sequence

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How? 10 Mbp of oligos / 1000 chip
( 2 E.coli genomes or 20 Mycoplasmas /chip)
Digital Micromirror Array
1000X lower oligo costs

• 8K Atactic/Xeotron/Invitrogen
• Photo-Generated Acid
• Sheng , Zhou, Gulari, Gao (Houston)
• 12K Combimatrix Electrolytic
• 44K Agilent Ink-jet standard reagents
• 380K Nimblegen Photolabile 5'protection

Amplify pools of 50mers using flanking universal
PCR primers and three paths to 10X error
correction
Tian et al. Nature. 4321050 Carr Jacobson
2004 NAR Smith Modrich 1997 PNAS
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rE.coli new in vivo genetic codes
Freeing 4 tRNAs, 7 codons UAG, UUR, AGY,
AGR e.g. PEG-pAcPhe-hGH (Ambrx, Schultz) high
serum stability
TTT F 30362 TCT S 11495 TAT Y 21999 TGT C 7048
TTC F 22516 TCC S 11720 TAC Y 16601 TGC C 8816
TTA L 18932 TCA S 9783 TAA STOP STOP 2703 TGA STOP 1256
TTG L 18602 TCG S 12166 TAG STOP STOP 326 TGG W 20683
CTT L 15002 CCT P 9559 CAT H 17613 CGT R 28382
CTC L 15077 CCC P 7485 CAC H 13227 CGC R 29898
CTA L 5314 CCA P 11471 CAA Q 20888 CGA R 4859
CTG L 71553 CCG P 31515 CAG Q 39188 CGG R 7399
ATT I 41309 ACT T 12198 AAT N 24159 AGT S 11970
ATC I 34178 ACC T 31796 AAC N 29385 AGC S 21862
ATA 5967 ACA T 9670 AAA K 45687 AGA R 2896
ATG M 37915 ACG T 19624 AAG K 14029 AGG R 1692
GTT V 24858 GCT A 20762 GAT D 43719 GGT G 33622
GTC V 20753 GCC A 34695 GAC D 25918 GGC G 40285
GTA V 14822 GCA A 27418 GAA E 53641 GGA G 10893
GTG V 35918 GCG A 45741 GAG E 24254 GGG G 15090
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1
Isaacs Church Forster Carr Jacobson Jahnz Schu
ltz
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2
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Our DOE Biofuels Center goals strengths

• 1. Basic enabling technologies omics, models,
• genome synthesis, evolution, sequencing
• 2. Harnessing new insights from ecosystems.
• 3. Improving photosynthetic and conversion
  efficiencies.
• 4. Fermentative production of alcohols
  biodiesel.

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Prochlorococcus 40ºN - 40ºS Chisholm et al.
Ocean chl a (Aug 1997 Sept 2000) Provided by the
SeaWiFS Project, NASA
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Light regulated Prochlorococcus metabolism
glgA
glgB
glgC
Central Carbon Metabol.
a-Glc-1P
ADP-Glc
glycogen
a-1,4-glucosyl-glucan
glgX
glgP
Zinser et al. unpubl.
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Photosynthetic Genes in Phage
Podovirus P-SSP7 46 kb
Myovirus P-SSM2 255 kb
PC
HLIPs
Fd
D1
PC
HLIPs
Fd
D1
12kb 24kb
12kb 24kb
Myovirus P-SSM4 181 kb
HLIPs
D1
D2
HLIPs
D1
D2
500
bp
500
bp
6.4kb

2.8kb
6.4kb

2.8kb
Lindell, Sullivan, Chisholm et al. 2004
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RNA Responses to Phage
MED4 host psbA
MED4-0682 (60 aa Conserved URF)
Phage SSP7 psbA
Lindell, Sullivan, Zinser, Chisholm
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Our DOE Biofuels Center goals strengths

• 1. Basic enabling technologies omics, models,
• genome synthesis, evolution, sequencing
• 2. Harnessing new insights from ecosystems.
• 3. Improving photosynthetic and conversion
  efficiencies.
• 4. Fermentative production of alcohols
  biodiesel.

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Brazils Bioethanol

• Land use45,000 km²
• Sugarcane344 million tons
• Sugar 23 million tons
• Ethanol14 million m³ 0.26/L (feedstock 70)
• yield increase 3.5/yr
• Dry bagasse 50 million tons
• Electricity 1350 MW
• Bagasse ash 2.5 (vs 40 for coal),
• nearly no sulfur. Burns at low temperatures,
• so low nitrogen oxides.

Saccharum officinarum
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Our DOE Biofuel Center Goals

• Miscanthus v Panicum (switchgrass) 22 v 10
  tons/ha
• Goals 2kg Hybrid seeds v 2 tons rhizomes
• self-destruction to aid crop rotation,
  pretreatment
• 0.10/L goal (NEB gt4, corn-EtOH1.3
  soy-diesel1.93)
• Pretreatment 0.03/L
• Ammonia fiber explosion (AFEX), dilute acid
• Integrated cellulases fermentation to ethanol,
  butanol, biodiesel, alkanes 0.02/L

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High Ethanol (low Lactate, Acetate)
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Butanol pathways
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Lab Evolution collaborations
Sacharomyces Growth on cellulose (Lee
Lynd) Ethanol resistance (Greg Stephanopoulos) Es
cherichia Radiation resistance (Edwards
Battista) Tyr/Trp production transport (Lin
Reppas) Cutrate utilization (Rich Lenski) Lactate
production (Lonnie Ingram) Thermotolerance
(Phillipe Marliere) Glycerol utilization
(Bernahard Palsson)
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Intelligent Design Metabolic Evolution

• Fong SS, Burgard AP, Herring CD, Knight EM,
  Blattner FR, Maranas CD, Palsson BO. In silico
  design and adaptive evolution of Escherichia coli
  for production of lactic acid. Biotechnol Bioeng.
  2005 91(5)643-8.
• Rozen DE, Schneider D, Lenski RE Long-term
  experimental evolution in Escherichia coli. XIII.
  Phylogenetic history of a balanced polymorphism.
  J Mol Evol. 2005 61(2)171-80
• Andries K, et al. (JJ) A diarylquinoline drug
  active
• on the ATP synthase of Mycobacterium
  tuberculosis.
• Science. 2005 307223-7.
• Shendure et al. Accurate Multiplex Polony
  Sequencing of an Evolved Bacterial Genome
  Science 2005 3091728 (Select for secretion
  altruism).

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Competition cooperation

• Cooperation between two auxotrophs
• Overall fitness depends on secretion
• Over-production, increase of export
• Competition among each sub-population
• The fastest growing one wins
• Increase of uptake
• Coupling between evolution of import and export
  properties?
• Amplified genes
• Transporter pore genes

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Cross-feeding symbiotic systemsaphids Buchnera

• obligate mutualism
• nutritional interactions amino acids and
  vitamins
• established 200-250 million years ago
• close relative of E. coli with tiny genome
  (618641kb)

Internal view of the aphid. (by T. Sasaki)
Bacteriocyte (Photo by T. Fukatsu)
Buchnera (Photo by M. Morioka)
Aphids
http//buchnera.gsc.riken.go.jp
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Shigenobu et al. Genome sequence of the
endocellular bacterial symbiont of aphids
Buchnera sp.APS. Nature 407, 81-86 (2000).
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Shigenobu et al. Genome sequence of the
endocellular bacterial symbiont of aphids
Buchnera sp.APS. Nature 407, 81-86 (2000).
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ODE based simulation of population dynamics of
cross-feeding ?Trp-?Tyr

• Questions
• When mixed in minimum medium, how do the cell
  population and the amino acid concentrations
  change over time?
• What happens when the strains evolve?
• improve on amino acid imports
• improve on amino acid synthesis and/or exports

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Governing ODE system
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Steady-state solution
Variables
Parameters
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Invasion of advantageous mutants
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Next Generation Technology Development
Multi-molecule Our role Affymetrix
Software 454 LifeSci Paired ends,
emulsion Solexa/Lynx Multiplexing
polony AB/APG Seq by Ligation (SbL) Complete
Genomics SbL Gorfinkel Polony to
Capillary Single molecules Helicos Biosci
SAB, cleavable fluors Pacific Biosci
Advisor KPCB Agilent Nanopores Visigen
Biotech AB
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Polony Sequencing EquipmentHMS/AB/APG
microscope with xyz controls
HPLC autosampler (96 wells)
flow-cell
syringe pump
temperature control
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Synthetic combinatorics evolution of 77 4.7
Mbp genomes
Second Passage
First Passage
?trp/?tyrA pair of genomes shows the best
co-growth Reppas, Lin Church Shendure et
al. Accurate Multiplex Polony Sequencing of an
Evolved Bacterial Genome(2005) Science 3091728
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Why low error rates?
Goal of genotyping resequencing ? Discovery of
variants E.g. cancer somatic mutations 1E-6 (or
lab evolved cells)
Consensus error rate Total errors (E.coli)
(Human) 1E-4 Bermuda/Hapmap 500
600,000 4E-5 454 _at_40X
200 240,000 3E-7 Polony-SbL _at_6X
0 1800 1E-8 Goal
for 2006 0 60
Also, effectively reduce (sub)genome target size
by enrichment for exons or common SNPs to reduce
cost false positives.
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Mutation Discovery in Engineered/Evolved E.coli
Position Type Gene Location ABI Confirm Comments
986,334 T gt G ompF Promoter-10 ? Only in evolved strain
985,797 T gt G ompF Glu gt Ala ? Only in evolved strain
931,960 ?8 bp lrp frameshift ? Only in evolved strain
3,957,960 C gt T ppiC 5' UTR ? MG1655 heterogeneity
l-3274 T gt C cI Glu gt Glu ? l-red heterogeneity
l-9846 T gt C ORF61 Lys gt Gly ? l-red heterogeneity

Shendure, Porreca, et al. (2005) Science
3091728
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ompF - non-specific transport channel
Can increase import export capability
simultaneously

• Glu-117 ? Ala (in the pore)
• Charged residue known to affect pore size and
  selectivity

• Promoter mutation at position (-12)
• Makes -10 box more consensus-like

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Sequence monitoring of evolution(optimize small
molecule synthesis/transport)
Sequence trp-
Reppas, Lin Church
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Co-evolution of mutual biosensors sequenced
across time within each time-point

• 3 independent lines of Trp/Tyr co-culture frozen.
  
• OmpF 42R-gt G, L, C, 113 D-gtV, 117 E-gtA
• Promoter -12A-gtC, -35 C-gtA
• Lrp 1bp deletion, 9bp deletion, 8bp deletion,
  IS2 insertion, R-gtL in DBD.
• Heterogeneity within each time-point reflecting
  colony heterogeneity.

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Our DOE Biofuels Center goals strengths

• 1. Basic enabling technologies omics, models,
• genome synthesis, evolution, sequencing
• 2. Harnessing new insights from ecosystems.
• 3. Improving photosynthetic and conversion
  efficiencies.
• 4. Fermentative production of alcohols
  biodiesel.

38
Synthetic Biology Microbial Biofuels
George Church, MIT/Harvard DOE GtL Center DuPont
13-Sep-2006
39
.
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.
MI, OK, IL, IN, MN, KY, PA, MA, CA, NH. Because
our GTL-Systems Biology Center renewal is a bit
before the GTL-Bioenergy Research Centers, we're
on target for an integrated SB-BRC including
strengths in A. Technology development,
ecological economical modeling Franco Cerrina
(U. Wisc EE), George Church (MIT/HMS), Ed DeLong
(MIT BE), Chris Marx (Harvard OEB), Penny
Chisholm (MIT Civil Eng). These basic enabling
technologies feed into all of the other aims. We
are improving our pipeline from 1. metagenomics
(single cell sequencing) to 2. datamining to 3.
combinatorial (semi)synthetic library formation,
to 4. lab-evolution, then 5. sequencing. B.
Innovative macromolecular production and
structural studies. William Shih (DFCI), James
Chou(Harvard), Phil Laible (ANL). William
James have made a breakthrough using
DNA-nanotubes which greatly improves the NMR
structures including membrane proteins. . We
also have world leaders in high-resolution
cryo-EM. Phil has developed an impressive what to
produce large quantities of pure membrane
proteins. My group is scaling-up DNA preps to
the multi-gram levels. Membrane and
ligno-cellulosic compartments are previous
blind-spots for structural genomics which we are
addressing. C. Synthetic systems biology
Daniel Segre (BU BME) Nina Lin (MSU), Pam Silver
(HMS SysBiol), Drew Endy (MIT), Jim Collins (BU
BME), Anthony Forster (VUMC), Joseph Jacobson
(MIT ML). We are proposing a BioFoundry in
collaboration with Codon Devices) to bring the
cost down of open-wetware and genome-engineering.
This includes novel ways to improve accuracy of
synthesis and in vivo homologous recombination
especially organisms with previously
'challenging' genetics. Phage-, bacterial-, and
in vitro- display systems for evolution of
enzymes subsystems. Ref Building a Fab for
Biology D. Phototrophs Fred Ausubel (Harvard),
Wayne Curtis (Penn State U ChE), Clint Chapple
(Purdue) Arabidopsis lignins, Richard Dixon
(Noble Plant Science Center, OK) Medicago
lignins digestability, Stephen Long, (U Ill
Champaign) Mischanthus. It is clear that food
crops can support only a tiny fraction of our
energy needs, while plants growing in marginal
lands (Miscanthus at 60 tons/ha), Panicum, and
Populus tricocarpa offer the best starting
points. We are engineering these to maximize
yield, tolerate stress, and self-destruct when
harvested. We also are engineering algae for
higher yield/lower cost than grasses, and
specialized applications including power plant
gases with Greenfuel Tech Corp). E. Microbial
metabolic engineering fermentation, including
ligno-cellulose to alcohols alkanes Greg
Stephanopoulos (MIT ChE) E.coli Saccharomyces,
Lee Lynd (Dartmouth Eng) Clostridia, Lonnie
Ingram (U FL) E.coli, Kristala Jones Prather (MIT
ChE) E.coli, Thomas Jeffries (USDA, WI) Pichia.
We are collecting/evolving enzyme systems to
extend the range of input substrates and output
fuels and specialty chemicals.
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Smart therapeutics example Environmentally
controlled invasion of cancer cells by engineered
bacteria. Anderson et al. J Mol Biol. 2006
Metabolic constraints Regulated Capsule TonB,
DapD new genetic codes for safety
Optical imaging bacteria, viruses, and mammalian
cells encoding light- emitting proteins reveal
the locations of primary tumors metastases
in animals. Yu, et al. Anal. Bioanal. Chem.
2003. accumulate in tumors at ratios in excess
of 10001 compared with normal tissues.
http//www.vionpharm.com/tapet_virulence.html
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LPS- Capsule Dap- for safety
DapD
7