1. Life with four
billion atoms
Tom Knight
Ginkgo Bioworks

2. Energy in the 1800s The steam engine has given more to science than
science has given to the steam engine Lord Kelvin

3. Information
in the 1900s

5. Core of simple universal parts (central metabolites) (Energy carriers)
Catabolism
Anabolism
Natural
Complexity
(Food)
Specified
Complexity
(Organisms)
Architecture – raw materials to building materials to new construction
Design Information
(Genome)
Core of simple universal parts
(central metabolites)
(Energy carriers)

6. Harold Morowitz 1962 & 1984

7. Some history… Confusion over what PPLO/Mycoplasma were
“The Microbe of pleuorpneumonia” Nocard 1896
1932 isolation of “PPLO” Koch postulates.
1958 Klieneberger-Nobel: free living bacterial species
Morowitz 1962 SciAm: “the smallest living cell”
1980 Gilbert effort to sequence M. capricolum
1982 Morowitz “complete understanding of life”
1996 Fraser et al. M. genitalium sequence
1999 Hutchison et al. Minimal genome set for M. genitalium
2009 Gibson & Lartigue: Genome transplantation
2012 Serrano et al. Comprehensive model

8. Complexity, minimality & simplicity
Complex systems have many parts
Reducing the part count leads generally to simpler system (minimal part count)
Extreme part count reduction leads to shared parts
These systems are ironically less simple
There is an optimal part count for modular design
Conservation of complexity
Stratified design
Structure
function

9. Complexity Reduction 100’s of OS calls 100 statements
User
Application software
Operating system, user interface
Programming language
Instruction set architecture
Virtual machine
Computer hardware design
Functional computing units
Logic synthesis
Logic gates
Circuit design
Transistors
Mask geometry
Fabrication technologies
Semiconductor physics
Quantum physics
100’s of OS calls
100 statements
100’s of instructions
10’s of units
10’s of gate types
4 types of transistors
15 mask layers
6 materials

10. Biology is modular and abstract
Complexity Reduction
Good News:
Biology is modular and abstract
Evolution needs modular design as much as we do
We can discover the modular designs, modify them, and use them

11. Engineered Simple Organisms
modular
understood
malleable
low complexity
Start with a simple existing organism
Remove structure until failure
Rationalize the infrastructure
Learn new biology along the way
The chassis and power supply for our computing

12. Relative Complexity Alive Autotroph Log Genome Size, base pairs
Mycoplasma genitalium (580 kB)
Mesoplasma florum (793 kB)
S. cerevisiae (12 MB)
T7 Phage (36 kB)
Lilly (12 GB)
E. coli (4.6 MB)
Human (3.3 GB)
Plasmid
Gene
100 1K
10K
100K 1M
10M
100M 1G
10G
100G
Alive
Autotroph
Log Genome Size, base pairs

13. Choosing an organism: Mesoplasma florum
Isolation from the flower of a lemon tree, Florida (McCoy84)
Safe BSL-1 organism -- an insect commensal
Not a human or plant or animal pathogen
No growth at 37C
Fast growing
40 minute vs.
six hours for doubling in M. genitalium
Convenient to work with
Facultative anaerobe
Small genome:
793,244 bp
682 coding regions

14. Tomographic EM of Me. florum
Grant Jensen – Caltech
3-D TEM image of
Mesoplasma florum
Reconstructed from angled
TEM images
300 x 400 nm
6 nm membranes
5 nm ribosomes
False colored DNA

15. How many atoms? Cell diameter is about 400 nm
Approximately 2000 atoms in diameter
About four billion atoms
70% of these are in water molecules
1.2 billion atoms in biomolecules
DNA is about 40 million atoms, 3%

17. Genome characteristics
base pairs
26.52% G + C
682 protein coding regions
UGA for tryptophan
No CGG codon or corresponding tRNA
Classic circular genome
oriC, terminator region, gene orientation
39 stable RNAs
29 tRNAs
2x 16S, 23S, 5S
RNAse-P, tmRNA, SRP
One inactive insertion sequence
Gene direction largely oriented with replication fork

18. Understand the metabolism
Identify major metabolic pathways by finding critical genes coding for known enzymes
Predict necessary enzymes which may not have been found
Evaluate the list of unknown function genes for candidates
Build the major metabolic pathway map of the organism
Consider elimination of entire pathways

19. Identified Metabolic Pathways in Mesoplasma florum
G. Fournier
02/23/04
PTS II System
Mfl519, Mfl565
sucrose
trehalose
xylose
beta-glucoside
glucose
unknown
ribose
ABC transporter
Mfl516, Mfl527,
Mfl187
Mfl500
Mfl669
Mfl009, Mfl033,
Mfl318, Mfl312
fructose
Mfl214, Mfl187
Mfl619, Mfl431,
Mfl426
Mfl181
ATP Synthase Complex
Mfl497
Mfl515, Mfl526
Mfl499
Mfl317?, Mfl313?
Mfl617, Mfl430, Mfl313?
Mfl425, Mfl615, Mfl034,
Mfl009, Mfl011, Mfl012, ?
Mfl112, Mfl113, Mfl114,
Mfl109, Mfl110, Mfl111,
Mfl115, Mfl116
Mfl666, Mfl667,
Mfl668
glucose-6-phosphate
chitin degradation
Mfl558
Mfl347,
ATP
ADP
sn-glycerol-3-phosphate
ABC transporter
Pentose-Phosphate Pathway
Glycolysis
Mfl023, Mfl024,
Mfl025, Mfl026
L-lactate,
acetate
Mfl223, Mfl640, Mfl642, Mfl105, Mfl349
glyceraldehyde-3-phosphate
Mfl254, Mfl180, Mfl514, Mfl174, Mfl644, Mfl200, Mfl504, Mfl578, Mfl577, Mfl502, Mfl120, Mfl468, Mfl175, Mfl259
Mfl039, Mfl040, Mfl041, Mfl042, Mfl043, Mfl044, Mfl596, Mfl281
Lipid Synthesis
unknown substrate
transporters
Mfl046, Mfl052
Mfl384, Mfl593,
fatty acid/lipid
transporter
ribose-5-phosphate
acetyl-CoA
Mfl230, Mfl382, Mfl286, Mfl663, Mfl465, Mfl626
Mfl590, Mfl591
Mfl325,Mfl482
Mfl099, Mfl474,Mfl315,
x13+
PRPP
cardiolipin/
phospholipids
membrane synthesis
Purine/Pyrimidine Salvage
phospholipid
membrane
Identified Metabolic Pathways in Mesoplasma florum
Mfl074, Mfl075, Mfl276, Mfl665, Mfl463, Mfl144, Mfl342, Mfl343,
Mfl419, Mfl676, Mfl635, Mfl119, Mfl107, Mfl679, Mfl306, Mfl648,
Mfl170, Mfl195, Mfl372
Mfl076, Mfl121, Mfl639, Mfl528, Mfl530, Mfl529, Mfl547, Mfl375
Mfl143, Mfl466, Mfl198, Mfl556, Mfl385
niacin?
Mfl038,
Mfl065,
Mfl063,
Mfl388
xanthine/uracil
permease
Pyridine Nucleotide Cycling
variable surface
lipoproteins
Mfl413, Mfl658
Mfl444, Mfl446,
Mfl451
Mfl340, Mfl373, Mfl521, Mfl588
Mfl583, Mfl288, Mfl002,
Mfl678, Mfl675, Mfl582,
Mfl055, Mfl328
Mfl150, Mfl598, Mfl597,
Mfl270, Mfl649
hypothetical
lipoproteins
DNA
Polymerase
RNA
Polymerase
x22
competence/
DNA transport
Mfl047, Mfl048, Mfl475
Electron Carrier Pathways
DNA
RNA
K+, Na+
transporter
Mfl027, Mfl369
Flavin Synthesis
Nfl289, Mfl037, Mfl653, Mfl193
Mfl064, Mfl178
NAD+
Mfl165, Mfl166
ribosomal RNA
transfer RNA
degradation
FMN, FAD
Mfl193
Mfl541, Mfl005, Mfl647,
Mfl258, Mfl329, Mfl374,
Mfl563, Mfl548, Mfl088,
Mfl231, Mfl209
Mfl282, Mfl387, Mfl682,
Mfl014, Mfl196,Mfl156,
Mfl029, Mfl412, Mfl540,
Mfl673, Mfl077, rnpRNA
Mfl283, Mfl334
malate
transporter?
hypothetical
transmembrane
proteins
NADP
Mfl378
x57
Ribosome
metal ion
transporter
Signal Recognition Particle (SRP)
riboflavin?
Mfl356, Mfl496,
Mfl217
messenger RNA
tRNA
aminoacylation
NADPH
NADH
protein secretion
(ftsY)
srpRNA, Mfl479
23sRNA, 16sRNA, 5sRNA,
Mfl122, Mfl149, Mfl624, Mfl148, Mfl136, Mfl284, Mfl542, Mfl132, Mfl082,
Mfl127, Mfl561, Mfl368.1, Mfl362.1, Mfl129, Mfl586, Mfl140, Mfl080,
Mfl623, Mfl137, Mfl492, Mfl406
Mfl608, Mfl602, Mfl609, Mfl493, Mfl133, Mfl141, Mfl130, Mfl151, Mfl139,
Mfl539, Mfl126, Mfl190, Mfl441, Mfl128, Mfl125, Mfl134, Mfl439, Mfl227,
Mfl131, Mfl123, Mfl638, Mfl396, Mfl089, Mfl380, Mfl682.1, Mfl189,
Mfl147, Mfl124, Mfl135, Mfl138, Mfl601, Mfl083, Mfl294, Mfl440?
cobalt
ABC transporter
Mfl237
Mfl152, Mfl153,
Mfl154
proteins
Formyl-THF Synthesis
Export
Mfl613, Mfl554, Mfl480, Mfl087, Mfl651, Mfl268, Mfl366,
Mfl389, Mfl490, Mfl030, Mfl036, Mfl399, Mfl398, Mfl589,
Mfl017, Mfl476, Mfl177, Mfl192, Mfl587, Mfl355
Mfl086, Mfl162, Mfl163, Mfl161
phosphonate
ABC transporter
met-tRNA formylation
Mfl571, Mfl572
Mfl060, Mfl167, Mfl383, Mfl250
protein translocation
complex (Sec)
Mfl057, Mfl068,
Mfl142,Mfl090,
Mfl275
Mfl409, Mfl569
phosphate
ABC transporter
Mfl233, Mfl234,
Mfl235
degradation
THF?
Mfl186
formate/nitrate
transporter
amino acids
intraconversion?
Mfl094, Mfl095,
Mfl096, Mfl097,
Mfl098
Mfl418, Mfl404, Mfl241, Mfl287, Mfl659, Mfl263, Mfl402,
Mfl484, Mfl494, Mfl210, tmRNA
Mfl509, Mfl510,
Mfl511
spermidine/putrescine
ABC transporter
oligopeptide
ABC transporter
Mfl016, Mfl664
putrescine/ornithine
APC transporter
Mfl015
Mfl182, Mfl183,
Mfl184
Mfl019
Mfl605
arginine/ornithine
antiporter
Mfl557
Mfl652
unknown amino acid
ABC transporter
glutamine
ABC transporter
lysine
APC transporter
alanine/Na+
symporter
glutamate/Na+
symporter
Amino Acid Transport

20. How Simple is this? Missing cell wall, outer membrane
Missing TCA cycle
Missing amino acid synthesis
Missing fatty acid synthesis
One sigma factor
Small number of dna binding proteins
One insertion sequence, probably not active
One restriction system (Sau3AI-like)
CTG/CAG methylation (function?)
Evidence for shared protein function
MDH/LDH (Pollack 97 Crit rev microbiol 23:269)

21. Proteome Collaboration with Steve Tannenbaum / Yingwu Wang
2-D gels + MS spot ID
LC/LC/MS/MS ID of trypsin digests

22. Proteome Results 180 spots picked and analyzed
Mudpit LC/LC/MS/MS also carried out
369 proteins identified by trypsin digestion and mass spec out of 682 annotated coding regions
Transcription of 16S ribosomal RNA
Stops don’t always stop
Instead they cause frame shifts into other frames

23. Transposome insertions
Engineered tetM tetracycline resistance gene
Promoter from Tn4001 tetM gene
Outward directed primers for insertion site verification
Unique I-SceI cut site
In vitro binding of Tn5 transposase
Electroporation of Tn5 transposome
Selection with tetracycline
Genomic DNA prep
Cut with MboI frequent cutter & religate
PCR with outward directed primers
Sequence to identify insertion site
Locate disrupted genes
Alternatively: directly sequence from genomic DNA

24. Custom Transposon

25. Tn5 Transposomes Transposon design issues Codon usage Promoter design
Restriction site avoidance
Cell transformation
Electroporation voltage
Selection medium

26. Transposome insertion events
2700 currently picked, saved, and sequenced
337 Essential Genes + 29 tRNA + 7 essential RNA genes
Most are unsurprising surface lipoproteins and “unknown function”
Some surprises: inessential ftsZ, mreB, many ribosomal & tRNA modification proteins,
But the Sau3AI homologous restriction system appears essential
About 80 unknown function genes (many GTPases) are essential
Compare with
Dybvig08 results on M. arthritidis
French08 results on M. pulmonis
Glass06 results on M. genitalium
Ordered library of cells with 330 inactivated genes

27. Functional Categories of Essential Genes
Category
Number
DNA Replication 22
Cell Division 5
Transcription 12
Nucleotide Transport & metabolism 20
Protein translation
112
Post translational modification 6
Protein secretion 7
Lipid metabolism
Coenzyme metabolism
Energy production 11
Transporters 35

28. Transposome insertion events

29. Essential is not absolute
Multi-copy genes are not identified as essential
NADH oxidase
Acyl carrier protein
Essentiality is defined by the culture conditions
Genes with stability and reliability function are marked as dispensable
DNA repair
Chaparones
Some RNA modification enzymes
This is a much more important effect in larger genomes

30. Next in Analysis and Tools
Genome re-engineering with knock-in/knock-out
Resequencing
Whole cell metabolic models
Plug and play modules for additional function
Biosafety issues

31. Genome re-engineering tools
Plasmid: S. citri pSci2 PE protein based (Breton08)
J70302 registry part, under test now
recET recombination system (S. citri recT gene)
J70007 recT part, DNA available, being mutated
Chloramphenicol resistance gene cassette
PheS mutant gene cassette
Phase 1:
Turn on recombination
Insert PheS/cat cassette in the target location
Select with Chloramphenicol
Phase 2:
Insert final modification
Select with p-chlorophenylalanine
Result: seamless editing of the chromosome

32. Resequencing Illumina sequencing is cheap and very high throughput
Relatively straightforward with a pre-existing scaffold sequence
We get millions of reads of limited length (35-70 bp)
Paired ends, bp fragments
Bar coded samples can multiplex the sequencing effort
Allows many samples to be sequenced in a single run
Resequence the Mesoplasma florum genome
De novo sequence for sixteen additional strains
Collection of Robert Whitcomb
De novo sequencing for several closely related species
Mesoplasma entomophilum
Mesoplasma lactucae

33. Whole cell modeling Approximately 2000 chemical reactions
About 300 small molecule species
Faster implementations of stochastic models
Faster computers
Comparison against reality
Mass spec quantitation of metabolites

34. Open Cell Modules Energy sources Arginine vs. glucose
Photosynthesis pathway
Citric acid cycle (reverse?)
Amino acid synthesis
Add unnatural AAs
Nucleotide synthesis
Lipid synthesis
Cofactor synthesis
Measurement structures
Environmental niche
Halobacterium
Sulfur reducer
Temperature optimum
Membrane export / import
Membrane structure
Sensing of chemical environment
Flagellar motion
Light sensing
Light production
Cell cycle control (sporulation)
Biosafety modules

35. Biosafety Barriers Codon isolation
CGG containing genes are unusable inside
TGA containing genes are unusable outside
Extend this idea with more codons
Pairs of required essential nutrients
Reduces likelihood of gradual evolution of workarounds
Explicit “kill” switches
Otherwise benign chemicals lethal to this organism
Shared function with critical metabolism reduces drift

36. Recoding the genome of entire organisms
Engineered
phage
Natural Phage X X X
Engineered
organism
No transfer: UGA
not translated
No transfer: CGG
not translated X
Natural
organism

37. Kit Part the genome
Make Biobrick parts from each gene, tRNA, promoter, other part-like genome element
Develop techniques for recombining parts into coherent modules
YAC editing and assembly, e.g.
Lambda RED or RecET recombination
Enable the bootstrapping of cells based on the redesigned genome
Liposome fusion, e.g.
Learn the design rules for chromosomes

38. Thanks to… Harold Morowitz Greg Fournier Gail Gasparich Bob Whitcomb
Eric Lander
Bruce Birren
Nicole Stange-Thomann
George Church
Roger Brent
Grant Jensen
Yingwu Wang
Samantha Burke
PJ Steiner
Nick Papadakis
Ron Weiss
Drew Endy
Randy Rettberg
Austin Che
Reshma Shetty
MIT Synthetic biology working group
DARPA, NTT, NSF, Microsoft
Colleagues at Ginkgo Bioworks

39. Thank you for
your attention

40. Our Plan Completely understand a simple organism
Build excellent models and predictive tools
Simplify the organism further
Remove inessential genes
Replace dual function genes with single function equivalents
Abstract useful modules from other living systems
Understand and create good models for these modules
Selectively add these modules to the existing simple cell
The code’s 4 billion years old; it’s time for a rewrite

41. The Mollicute Bibliome
Complete collection of mycoplasma related papers:
6,411 and counting
Books and book chapters also
Endnote file: mycoplasmas.enl
Downloaded .pdfs for articles > 1995
Scanned articles and books, OCR
Collaboration for “shallow semantic” understanding
people.csail.mit.edu/tk/mfpapers/ user=meso, pass=meso