recombinase-based circuits for environmental detection...

Recombinase-Based Circuits for Environmental Detection, Diagnostics, and Logging

Richard M. Murray California Institute of Technology

Victoria Hsiao (Amyris) Yutaka Hori (Keio U) Andrey Shur

Outline I. Event detection and introduction to recombinases II. Event diagnostics using population-level, stochastic response III. New directions: event logging, field-programmability IV. Summary and next steps

Richard M. Murray, Caltech CDS/BESynBio Control, 18 Jul 2017

Detection • Monitor the environment and look for a specified “trigger”

• Simple monitoring: signal detection; logic (AND, OR, …)

• More complex detection: temporal sequences of events Diagnostics • Extract quantitative properties: magnitude, duration, etc

Logging • Remember environmental conditions for later readout

Approach • Component technolo-

gies: signal detection, memory, species comp-arison, logic functions

• Event detectors: A > B, A followed by B, A > thresh

• Interconnection frame-work: modular techni-ques for interconnecting components & detectors

Environmental Detection, Diagnostics, and Logging

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Interconnection of modulesto detect more complex events

GFP if A is always less than B RFP if A is greater than B

Applications: environmental monitoring, diagnostics for health, circuit debugging, …


Integrases and Excisionases(Serine) Integrases • Mechanism by which phage insert DNA into the

chromosome of a bacterial host • attP = phage recognition site

• attB = bacterial recognition site

• Integrase action: insert phage DNA into bacterial chromosome, leaving changing recognition sites

Excisionases • Reverse reaction requires second phage-coded

protein, excisonase

Other recombinases • Cre recombinase - tyrosine recombinase

• Cre-Lox & Flp-FRT recombinases - insertion, excision, inversion, translocation

• CRISPR/Cas9 - guide RNA-directed excision, insertion

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A. Campbell, “General Aspects of Lysogeny”. In Bacteriophages, R. Calendar (ed), 2006.


Repurposing Recombinases for Synthetic BiologyBasic trick: put attB/attP on same piece of DNA • Integrase activity causes DNA between sites to flip

• Excisionase (+ integrases) causes reverse flip

Effects depend on orientation of attachment sides • Attachment sites pointing toward each other: flip

• Attachment sites in same direction: excise

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attB attP

attB attP

attB

attP

Cutting dimer

Rotating dimer

{

{

attL attR

Original DNA

( ‘B’ and ‘P’ stand for ‘bacteria’ and ‘phage’)

Integrase monomers bind

Integrase tetramer forms

DNA digestion

DNA rotation and ligation

Final DNA state

( ‘L’ and ‘R’ stand for ‘left’ and ‘right’)

J. Bonnet, P. Yin, M. E. Ortiz, P. Subsoontorn, and D. Endy. Amplifying genetic logic gates. Science, 340(6132):

599–603, 2013.

N. Roquet, A. P. Soleimany, A. C. Ferris, S. Aaronson, and T. K. Lu, “Synthetic recombinase-based state machines in

living cells”. Science, 353(6297):aad8559, 2016.


Several examples of recombinase based circuits in the literature

Recombinase-Based Circuit Examples

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P. Siuti, J. Yazbek, T. K. Lu, “Synthetic circuits integrating logic and memory in living cells”.

Nature Biotechnology, 1–6, 2013

A. E. Friedland, T. K. Lu, X. Wang, D. Shi, G. Church and J. J. Collins, “Synthetic gene networks that count”. Science,

324(5931), 1199–1202, 2009.

J. Bonnet, P. Subsoontorn, and D. Endy, “Rewritable digital data storage in live cells via

engineered control of recombination directionality”.

PNAS, 1–56, 2012.

Richard M. Murray, Caltech CDS/BECCC/SICE, Jul 2015

0 2 4 6 8 10

0

100

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∆TB−A

Fin

al n

um

be

r o

f ce

lls in

sta

te (

N)

Original state

A onlyB first

A then B

Event Ordering Detection (A then B)

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Arabinose (“A”) aTc (“B”)

GFPRFP α2

α1 α3

GFPRFP GFPRFP

GFPRFPGFPRFP

X

Z

Y

WTP-901 Bxb1

A 1 0B 0 0

A then B 0 1B then A 0 0Integrases:

Terminator PromoterReporter Reporter

GFPRFP

0 5 10 15 200

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Fina

l num

ber o

f cel

ls in

sta

te (N

)

Time (h)

∆T = 2 hr

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Fina

l num

ber o

f cel

ls in

sta

te (N

)

Time (h)

∆T = 1 hr

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Fina

l num

ber o

f cel

ls in

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te (N

)

Time (h)

X, original DNA stateY, A onlyZ, B firstW, A then B

X, original DNA state

Y, A onlyZ, B first

W, A then B

∆T = 0 hr


Y, A only

Z, B first

W, A then B

A and B simultaneously

0 5 10 15 200

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Fina

l num

ber o

f cel

ls in

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te (N

)

Time (h)

∆T = 2 hr

0 5 10 15 200

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Fina

l num

ber o

f cel

ls in

sta

te (N

)

Time (h)

∆T = 1 hr

0 5 10 15 200

100

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Fina

l num

ber o

f cel

ls in

sta

te (N

)

Time (h)

X, original DNA stateY, A onlyZ, B firstW, A then B


Y, A onlyZ, B first

W, A then B

∆T = 0 hr


Y, A only

Z, B first

W, A then B

A at t = 0 hr B at t = 1 hr

Number of cellsthat switch dependson interval between

the two inputs

Experiments match

simulations

# ce

lls in

eac

h st

ate

# ce

lls in

eac

h st

ate

Frac

tion

of m

ax G

FP

DNA layout

Steady state responseMarkov process model

for DNA state in each cell

∆ Tind1-ind2 (h)0 2 4 6 8 10

Frac

tion

of m

ax G

FP0

0.2

0.4

0.6

0.8

1

1.2

A only

B only No inducer

A then B

B then A

Hsiao, Hori and M., MSB, 2016


Additional Event “Diagnostics”Q: can we keep track of other things in addition to ΔT? • Have two measurements: #red, #green (versus total concentration)

• Idea: GFP population depends on the duration of pulse B => can also measure PWb

Use calibration phase (or models -:) to create lookup table and determine properties of inputs

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Simulation Experiment (flow cytometry)

Hsiao, Hori and M., MSB, 2016


Event Logging CircuitObjectives • Implement a genome ‘recording

site’ with a chronological order of inserted DNA fragments

• Utilize plasmids as the source of recording material, and use integrases as the means for DNA insertion

Status • Built event logger design

consisting of four modules: event plasmid (ID sequence), input selector (not shown), controller, logging site

• One event detector circuit tested and working

• Event plasmid selector using Cas9 gRNA to block integrases working in TX-TL

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Event logging circuit using DNA integrases

Proof-of-concept experimental validation

Event Plasmid

A. Shur (unpublished)


Field Programmable Circuits

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Shur and M., bioRxiv, 2017

Idea: use dCas9 to block integrases • Use gRNA to guide dCas9 to

recognition site => no integration • Can create different circuits by

controlling insertion of elements

Similar to field programmable gate arrays (FPGA) technology in circuits • Use expression of different integrases

to interconnect circuits

Preliminary experiments: it works! • Cell-free assays show repression of

integrates activity

A. Shur, R. M. Murray, “Repressing integrase attachment site opera-tion with CRISPR-Cas9 in E. coli”. bioRxiv, 2017. DOI 10.1101/110254


Recombinase-Based Circuits for Environmental Detection, Diagnostics, and Logging

Recombinase-based circuits compliment capabilities of genetic networks • Ability to reconfigure DNA in cells can be

used for logic and memory (detection logic)

• Stochastic response across populations of cells provides diagnostic capability

• Use DNA as a “recording tape” (logging) [see also recent paper by Shipman et al.]

Other uses to be explored • Integrases as a means of “programming”

circuits (FPGA-style)

• Use integrase/excisionase pairing as feedback mechanism (see Folliard poster)

Some open problems • Compilers: specs → (recombinase) circuits • Leaks are still a problem (leaky integrate

expression => noisy flipping) • Better exploiting stochastic dynamics

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Richard M. Murray, Caltech CDS/BEEngSci Syn Bio workshop, Sep 2014

Some Challenges and Research Directions (BFS)Better understanding of uncertainty • How do we capture observed behavior using

structured models for (dynamic) uncertainty

Stochastic specifications and design tools • How do we describe stochastic behavior in a

systematic and useful way? • How do we design stochastic behavior? • What are the right design “knobs”?

Higher level design abstractions • What are the right “device-level” design

abstractions (and corresponding diagrams)?

Redundant design strategies • Start implementing non-minimal designs

• Analogy: stochastic memory storage

Scaling up: components → devices → systems • How can we use in vitro “breadboarding” to

design and implement complex systems

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recombinase-based circuits for environmental detection...

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