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Biological Robustness in Complex Settings (BRICS)

Justin Gallivan, Ph.D. Program Manager

Biological Technologies Office

Briefing Prepared for the National Academy of Sciences Future of Biological Products Committee

Washington, DC

July 25, 2016

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BRICS Will Develop Enabling Technologies

Monitoring Water Quality

Preventing Equipment Corrosion

Enhancing Resistance to

Infection

Sensing Chemicals

Providing On-site Bioproduction

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Biological Robustness in Complex Settings (BRICS)

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Program Plan, Technical Milestones & Deliverables

Design methods for creating a self-organizing multi-

species consortium. Demonstrate control of 2-

species community.

Expand Phase I work to a 5-species community.

Engineer metabolic networks that divide labor

between multiple species in a community of at least 5

species.

Design a new genetic system that results in

reduced tolerance to point mutations. Demonstrate

stability in stressful conditions.

Expand Phase I work to a 5-species community.

Demonstrate the ability to maintain pure genotypes in a multi-species culture for

1000 generations.

Design methods for sensing physical and functional

properties of communities. Demonstrate override

mechanisms with simple reporter system

Expand Phase I work to include intracellular

monitoring. Demonstrate kinetics of override

mechanism.

Demonstrate complete growth arrest within 2 hrs and for up to 7 days after

triggering override mechanism.

Phase I (6 months) Prototype

Phase II (12 months) Scale-up/Optimize

Phase III (12 months) Demo

TA 1 Robustness

TA 2 Stability

TA 3 Safety

Phase I Phase II Phase III

Kick off 05/15 Today Next Decision

11/16 Next BAA

estimated 04/17

Solve a DoD-relevant problem

as described in the second BAA

Phase IV (18 months) Integration/App

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Four Approaches to Building Communities

Natural Synthetic

2. Middle-in Engineering Start with a model for predicting potential symbiotic interactions between species, mix, and allow community to evolve.

Major Challenge: predicting evolutionary dynamics of the community

1. Top-down Engineering Start with an existing community and develop methods for engineering in desired functions, safety, and stability. Major Challenge: introducing new genes and circuits into undomesticated species

3. Bottom-up Engineering Engineer symbiotic relationships into domesticated strains to force a group of microbes to co-exist as a community. Major Challenge: Engineering relationships between species that do not naturally live together

4. Synthetic Assembly Physically manipulate and constrain growth of individual species, so that communities can be assembled from building blocks. Major Challenge: Balancing physical separation with the need to share metabolites and biosynthetic precursors

UT-Austin MIT Harvard Caltech

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Team Harvard: Living biosensors that report and treat gastrointestinal infections

PI: Pam Silver

A robust, stable, and safe synthetic community of commensal gut bacteria that detects chemical signatures of pathogenic microbes.

Stable colonization of synthetic community in mouse colon

Signal amplification from proximal species to most abundant species

Closed-loop control of in-situ therapeutic production

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Team MIT: Modifying the gut microbiome to allow an animal to survive on a naturally indigestible food source

PI: Tim Lu

A gut microbiome engineered with synthetic metabolic pathways that enable an animal to extract energy from an indigestible source

cellulose degradation community

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Team UT-Austin: Controlling behavior of an animal through the gut microbiome

Engineered for biosynthesis of

neuropeptides or neurotransmitters

Passed from bee to bee

PI: Nancy Moran

Demonstration of engineering a microbiome to safely and stably control individual and collective animal behavior.

BGM: a community of only 8 species that lives in the bee hindgut

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Team Caltech: Performing incompatible reactions through physical encapsulation

PI: Rustem Ismagilov

BioFARMs: Biologically Functional Assemblies of Robust Microenvironments

One-pot synthesis of Brillinta®:

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Development of Supporting Technology

Columbia University: Overlapping-ORFs algorithm MIT: In situ microbiome engineering

LBNL: Community interaction modeling BCM: Community analytics

GOI is stabilized by linkage with essential gene

Engineered integrative conjugative elements

Time-series data

Principal component analysis

Euclidean distance Network model Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

Universal gene expression system

www.darpa.mil

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