Drew Endy
Associate Professor of Bioengineering
Bio
Drew Endy developed the world's first "fabless" genetic engineering teaching lab in the new Bioengineering program at Stanford and previously helped start the Biological Engineering major at MIT. His Stanford research team develops genetically encoded computers and redesigns genomes. He co-founded the BioBricks Foundation as a public-benefit charity supporting free-to-use standards and technology that enable the engineering of biology (BioBricks.org). He co-organized the International Genetically Engineered Machines (iGEM.org) competition, the BIOFAB International Open Facility Advancing Biotechnology (BIOFAB.org), and Gen9, Inc. (Gen9bio.com). He serves on the US Committee on Science Technology and Law and is a new voting member of the US National Science Advisory Board for Biosecurity. He chaired the 2003 Synthetic Biology study as a member of DARPA ISAT, served as an ad hoc member of the US NIH Recombinant DNA Advisor Committee, and co-authored the 2007 "Synthetic Genomics: Options for Governance" report with colleagues from the Center for Strategic & International Studies and the J. Craig Venter Institute. Esquire named Endy one of the 75 most influential people of the 21st century. He lives in Menlo Park CA with his wife and Stanford Bioengineering colleague Prof. Christina Smolke.
Honors & Awards
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Arthur Humphrey Teaching Award, Lehigh University (1993)
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Darling Fellowship, Thayer School, Dartmouth College (1994)
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Goodrich Prize, Thayer School, Dartmouth College (1998)
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Certificate of Appreciation, Synthetic Biology Study Chair, DARPA (2003)
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Certificate of Service, DARPA ISAT (2004)
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Cabot Career Development Award, MIT (2005)
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WIRED Rave Awards, WIRED (2005)
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Best & Brightest, Esquire (2007)
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Terman Fellow, Stanford University (2008)
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Most Influential People of the 21st Century, Esquire (2009)
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Best Research Article for 2011, Journal of Biological Engineering (2011)
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Kavli Fellow, US National Academies of Sciences (2012)
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Best Research Article for 2012, Journal of Biological Engineering (2012)
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Presidential Champion of Change, The White House (2013)
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The Seymour Benzer Lectureship, US National Academy of Sciences (2013)
Professional Education
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PhD, Dartmouth, Biotechnology & Biochemical Engineering (1998)
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MS, Lehigh, Environmental Engineering (1994)
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BS, Lehigh, Civil Engineering (1992)
2015-16 Courses
- Advanced Frameworks and Approaches for Engineering Integrated Genetic Systems
BIOE 244 (Spr) - Introduction to Bioengineering (Engineering Living Matter)
BIOE 80, ENGR 80 (Spr) -
Independent Studies (4)
- Bioengineering Problems and Experimental Investigation
BIOE 191 (Aut, Win, Spr, Sum) - Directed Investigation
BIOE 392 (Aut, Win, Spr, Sum) - Directed Study
BIOE 391 (Aut, Win, Spr, Sum) - Teaching of Biology
BIO 290 (Aut, Win, Spr)
- Bioengineering Problems and Experimental Investigation
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Prior Year Courses
2014-15 Courses
- Advanced Frameworks and Approaches for Engineering Integrated Genetic Systems
BIOE 244 (Spr) - Introduction to Bioengineering
BIOE 80, ENGR 80 (Spr)
2013-14 Courses
- Advanced Frameworks and Approaches for Engineering Integrated Genetic Systems
BIOE 244 (Aut) - Fundamentals for Engineering Biology Lab
BIOE 44 (Aut) - Introduction to Bioengineering
BIOE 80, ENGR 80 (Spr)
2012-13 Courses
- Fundamentals for Engineering Biology Lab
BIOE 44 (Aut, Spr)
- Advanced Frameworks and Approaches for Engineering Integrated Genetic Systems
All Publications
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Amplifying genetic logic gates.
Science
2013; 340 (6132): 599-603
Abstract
Organisms must process information encoded via developmental and environmental signals to survive and reproduce. Researchers have also engineered synthetic genetic logic to realize simpler, independent control of biological processes. We developed a three-terminal device architecture, termed the transcriptor, that uses bacteriophage serine integrases to control the flow of RNA polymerase along DNA. Integrase-mediated inversion or deletion of DNA encoding transcription terminators or a promoter modulates transcription rates. We realized permanent amplifying AND, NAND, OR, XOR, NOR, and XNOR gates actuated across common control signal ranges and sequential logic supporting autonomous cell-cell communication of DNA encoding distinct logic-gate states. The single-layer digital logic architecture developed here enables engineering of amplifying logic gates to control transcription rates within and across diverse organisms.
View details for DOI 10.1126/science.1232758
View details for PubMedID 23539178
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Precise and reliable gene expression via standard transcription and translation initiation elements
NATURE METHODS
2013; 10 (4): 354-?
Abstract
An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mRNA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ?93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales.
View details for DOI 10.1038/NMETH.2404
View details for Web of Science ID 000316851100025
View details for PubMedID 23474465
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Rewritable digital data storage in live cells via engineered control of recombination directionality
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2012; 109 (23): 8884-8889
Abstract
The use of synthetic biological systems in research, healthcare, and manufacturing often requires autonomous history-dependent behavior and therefore some form of engineered biological memory. For example, the study or reprogramming of aging, cancer, or development would benefit from genetically encoded counters capable of recording up to several hundred cell division or differentiation events. Although genetic material itself provides a natural data storage medium, tools that allow researchers to reliably and reversibly write information to DNA in vivo are lacking. Here, we demonstrate a rewriteable recombinase addressable data (RAD) module that reliably stores digital information within a chromosome. RAD modules use serine integrase and excisionase functions adapted from bacteriophage to invert and restore specific DNA sequences. Our core RAD memory element is capable of passive information storage in the absence of heterologous gene expression for over 100 cell divisions and can be switched repeatedly without performance degradation, as is required to support combinatorial data storage. We also demonstrate how programmed stochasticity in RAD system performance arising from bidirectional recombination can be achieved and tuned by varying the synthesis and degradation rates of recombinase proteins. The serine recombinase functions used here do not require cell-specific cofactors and should be useful in extending computing and control methods to the study and engineering of many biological systems.
View details for DOI 10.1073/pnas.1202344109
View details for Web of Science ID 000304991100029
View details for PubMedID 22615351
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Engineered cell-cell communication via DNA messaging.
Journal of biological engineering
2012; 6 (1): 16-?
Abstract
Evolution has selected for organisms that benefit from genetically encoded cell-cell communication. Engineers have begun to repurpose elements of natural communication systems to realize programmed pattern formation and coordinate other population-level behaviors. However, existing engineered systems rely on system-specific small molecules to send molecular messages among cells. Thus, the information transmission capacity of current engineered biological communication systems is physically limited by specific biomolecules that are capable of sending only a single message, typically "regulate transcription."We have engineered a cell-cell communication platform using bacteriophage M13 gene products to autonomously package and deliver heterologous DNA messages of varying lengths and encoded functions. We demonstrate the decoupling of messages from a common communication channel via the autonomous transmission of various arbitrary genetic messages. Further, we increase the range of engineered DNA messaging across semisolid media by linking message transmission or receipt to active cellular chemotaxis.We demonstrate decoupling of a communication channel from message transmission within engineered biological systems via the autonomous targeted transduction of user-specified heterologous DNA messages. We also demonstrate that bacteriophage M13 particle production and message transduction occurs among chemotactic bacteria. We use chemotaxis to improve the range of DNA messaging, increasing both transmission distance and communication bit rates relative to existing small molecule-based communication systems. We postulate that integration of different engineered cell-cell communication platforms will allow for more complex spatial programming of dynamic cellular consortia.
View details for DOI 10.1186/1754-1611-6-16
View details for PubMedID 22958599
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Measuring the activity of BioBrick promoters using an in vivo reference standard.
Journal of biological engineering
2009; 3: 4-?
Abstract
The engineering of many-component, synthetic biological systems is being made easier by the development of collections of reusable, standard biological parts. However, the complexity of biology makes it difficult to predict the extent to which such efforts will succeed. As a first practical example, the Registry of Standard Biological Parts started at MIT now maintains and distributes thousands of BioBrick standard biological parts. However, BioBrick parts are only standardized in terms of how individual parts are physically assembled into multi-component systems, and most parts remain uncharacterized. Standardized tools, techniques, and units of measurement are needed to facilitate the characterization and reuse of parts by independent researchers across many laboratories.We found that the absolute activity of BioBrick promoters varies across experimental conditions and measurement instruments. We choose one promoter (BBa_J23101) to serve as an in vivo reference standard for promoter activity. We demonstrated that, by measuring the activity of promoters relative to BBa_J23101, we could reduce variation in reported promoter activity due to differences in test conditions and measurement instruments by approximately 50%. We defined a Relative Promoter Unit (RPU) in order to report promoter characterization data in compatible units and developed a measurement kit so that researchers might more easily adopt RPU as a standard unit for reporting promoter activity. We distributed a set of test promoters to multiple labs and found good agreement in the reported relative activities of promoters so measured. We also characterized the relative activities of a reference collection of BioBrick promoters in order to further support adoption of RPU-based measurement standards.Relative activity measurements based on an in vivoreference standard enables improved measurement of promoter activity given variation in measurement conditions and instruments. These improvements are sufficient to begin to support the measurement of promoter activities across many laboratories. Additional in vivo reference standards for other types of biological functions would seem likely to have similar utility, and could thus improve research on the design, production, and reuse of standard biological parts.
View details for DOI 10.1186/1754-1611-3-4
View details for PubMedID 19298678
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Determination of cell fate selection during phage lambda infection
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2008; 105 (52): 20705-20710
Abstract
Bacteriophage lambda infection of Escherichia coli can result in distinct cell fate outcomes. For example, some cells lyse whereas others survive as lysogens. A quantitative biophysical model of lambda infection supports the hypothesis that spontaneous differences in the timing of individual molecular events during lambda infection leads to variation in the selection of cell fates. Building from this analysis, the lambda lysis-lysogeny decision now serves as a paradigm for how intrinsic molecular noise can influence cellular behavior, drive developmental processes, and produce population heterogeneity. Here, we report experimental evidence that warrants reconsidering this framework. By using cell fractioning, plating, and single-cell fluorescent microscopy, we find that physical differences among cells present before infection bias lambda developmental outcomes. Specifically, variation in cell volume at the time of infection can be used to help predict cell fate: a approximately 2-fold increase in cell volume results in a 4- to 5-fold decrease in the probability of lysogeny. Other cell fate decisions now thought to be stochastic might also be determined by pre-existing variation.
View details for DOI 10.1073/pnas.0808831105
View details for Web of Science ID 000262092800027
View details for PubMedID 19098103
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Refinement and standardization of synthetic biological parts and devices
NATURE BIOTECHNOLOGY
2008; 26 (7): 787-793
Abstract
The ability to quickly and reliably engineer many-component systems from libraries of standard interchangeable parts is one hallmark of modern technologies. Whether the apparent complexity of living systems will permit biological engineers to develop similar capabilities is a pressing research question. We propose to adapt existing frameworks for describing engineered devices to biological objects in order to (i) direct the refinement and use of biological 'parts' and 'devices', (ii) support research on enabling reliable composition of standard biological parts and (iii) facilitate the development of abstraction hierarchies that simplify biological engineering. We use the resulting framework to describe one engineered biological device, a genetically encoded cell-cell communication receiver named BBa_F2620. The description of the receiver is summarized via a 'datasheet' similar to those widely used in engineering. The process of refinement and characterization leading to the BBa_F2620 datasheet may serve as a starting template for producing many standardized genetically encoded objects.
View details for DOI 10.1038/nbt1413
View details for Web of Science ID 000257491600023
View details for PubMedID 18612302
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Engineering BioBrick vectors from BioBrick parts.
Journal of biological engineering
2008; 2: 5-?
Abstract
The underlying goal of synthetic biology is to make the process of engineering biological systems easier. Recent work has focused on defining and developing standard biological parts. The technical standard that has gained the most traction in the synthetic biology community is the BioBrick standard for physical composition of genetic parts. Parts that conform to the BioBrick assembly standard are BioBrick standard biological parts. To date, over 2,000 BioBrick parts have been contributed to, and are available from, the Registry of Standard Biological Parts.Here we extended the same advantages of BioBrick standard biological parts to the plasmid-based vectors that are used to provide and propagate BioBrick parts. We developed a process for engineering BioBrick vectors from BioBrick parts. We designed a new set of BioBrick parts that encode many useful vector functions. We combined the new parts to make a BioBrick base vector that facilitates BioBrick vector construction. We demonstrated the utility of the process by constructing seven new BioBrick vectors. We also successfully used the resulting vectors to assemble and propagate other BioBrick standard biological parts.We extended the principles of part reuse and standardization to BioBrick vectors. As a result, myriad new BioBrick vectors can be readily produced from all existing and newly designed BioBrick parts. We invite the synthetic biology community to (1) use the process to make and share new BioBrick vectors; (2) expand the current collection of BioBrick vector parts; and (3) characterize and improve the available collection of BioBrick vector parts.
View details for DOI 10.1186/1754-1611-2-5
View details for PubMedID 18410688
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DNA synthesis and biological security
NATURE BIOTECHNOLOGY
2007; 25 (6): 627-629
View details for DOI 10.1038/nbt0607-627
View details for Web of Science ID 000247077500014
View details for PubMedID 17557094
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Foundations for engineering biology
NATURE
2005; 438 (7067): 449-453
Abstract
Engineered biological systems have been used to manipulate information, construct materials, process chemicals, produce energy, provide food, and help maintain or enhance human health and our environment. Unfortunately, our ability to quickly and reliably engineer biological systems that behave as expected remains quite limited. Foundational technologies that make routine the engineering of biology are needed. Vibrant, open research communities and strategic leadership are necessary to ensure that the development and application of biological technologies remains overwhelmingly constructive.
View details for DOI 10.1038/nature04342
View details for Web of Science ID 000233458200039
View details for PubMedID 16306983
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Refactoring bacteriophage T7
MOLECULAR SYSTEMS BIOLOGY
2005; 1
Abstract
Natural biological systems are selected by evolution to continue to exist and evolve. Evolution likely gives rise to complicated systems that are difficult to understand and manipulate. Here, we redesign the genome of a natural biological system, bacteriophage T7, in order to specify an engineered surrogate that, if viable, would be easier to study and extend. Our initial design goals were to physically separate and enable unique manipulation of primary genetic elements. Implicit in our design are the hypotheses that overlapping genetic elements are, in aggregate, nonessential for T7 viability and that our models for the functions encoded by elements are sufficient. To test our initial design, we replaced the left 11,515 base pairs (bp) of the 39,937 bp wild-type genome with 12,179 bp of engineered DNA. The resulting chimeric genome encodes a viable bacteriophage that appears to maintain key features of the original while being simpler to model and easier to manipulate. The viability of our initial design suggests that the genomes encoding natural biological systems can be systematically redesigned and built anew in service of scientific understanding or human intention.
View details for DOI 10.1038/msb4100025
View details for Web of Science ID 000243244500019
View details for PubMedID 16729053
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Modelling cellular behaviour
NATURE
2001; 409 (6818): 391-395
View details for Web of Science ID 000166434300061
View details for PubMedID 11201753
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Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2000; 97 (10): 5375-5380
Abstract
We created a simulation based on experimental data from bacteriophage T7 that computes the developmental cycle of the wild-type phage and also of mutants that have an altered genome order. We used the simulation to compute the fitness of more than 10(5) mutants. We tested these computations by constructing and experimentally characterizing T7 mutants in which we repositioned gene 1, coding for T7 RNA polymerase. Computed protein synthesis rates for ectopic gene 1 strains were in moderate agreement with observed rates. Computed phage-doubling rates were close to observations for two of four strains, but significantly overestimated those of the other two. Computations indicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faster, the highest 31% faster, than wild type. Specific discrepancies between computations and observations suggest that a better understanding of the translation efficiency of individual mRNAs and the functions of qualitatively "nonessential" genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, prediction, and observation should increase the rate at which biological hypotheses are formulated and tested.
View details for Web of Science ID 000086998500068
View details for PubMedID 10792041
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Toward antiviral strategies that resist viral escape
ANTIMICROBIAL AGENTS AND CHEMOTHERAPY
2000; 44 (4): 1097-1099
Abstract
We studied the effect on viral growth of drugs targeting different virus functions using a computer simulation for the intracellular growth of bacteriophage T7. We found that drugs targeting components of negative-feedback loops gain effectiveness against mutant viruses that attenuate the drug-target interaction. The greater inhibition of such mutants than of the wild type suggests a drug design strategy that would hinder the development of drug resistance.
View details for Web of Science ID 000085997200049
View details for PubMedID 10722522
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One-Step Cloning and Chromosomal Integration of DNA
ACS SYNTHETIC BIOLOGY
2013; 2 (9): 537-541
Abstract
We describe "clonetegration", a method for integrating DNA into prokaryotic chromosomes that approaches the simplicity of cloning DNA within extrachromosomal vectors. Compared to existing techniques, clonetegration drastically decreases the time and effort needed for integration of single or multiple DNA fragments. Additionally, clonetegration facilitates cloning and expression of genetic elements that are impossible to propagate within typical multicopy plasmids.
View details for DOI 10.1021/s400021j
View details for Web of Science ID 000324842100007
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Composability of regulatory sequences controlling transcription and translation in Escherichia coli
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (34): 14024-14029
Abstract
The inability to predict heterologous gene expression levels precisely hinders our ability to engineer biological systems. Using well-characterized regulatory elements offers a potential solution only if such elements behave predictably when combined. We synthesized 12,563 combinations of common promoters and ribosome binding sites and simultaneously measured DNA, RNA, and protein levels from the entire library. Using a simple model, we found that RNA and protein expression were within twofold of expected levels 80% and 64% of the time, respectively. The large dataset allowed quantitation of global effects, such as translation rate on mRNA stability and mRNA secondary structure on translation rate. However, the worst 5% of constructs deviated from prediction by 13-fold on average, which could hinder large-scale genetic engineering projects. The ease and scale this of approach indicates that rather than relying on prediction or standardization, we can screen synthetic libraries for desired behavior.
View details for DOI 10.1073/pnas.1301301110
View details for Web of Science ID 000323271400076
View details for PubMedID 23924614
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Measurement and modeling of intrinsic transcription terminators.
Nucleic acids research
2013; 41 (9): 5139-5148
Abstract
The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used routinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode termination efficiencies across an ∼800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termination activity. We found that structures extending beyond the core terminator stem are likely to increase terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r = 0.9, n = 31) better than models trained on all terminators (r = 0.67, n = 54). The resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination.
View details for DOI 10.1093/nar/gkt163
View details for PubMedID 23511967
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Quantitative estimation of activity and quality for collections of functional genetic elements
NATURE METHODS
2013; 10 (4): 347-?
Abstract
The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.
View details for DOI 10.1038/NMETH.2403
View details for Web of Science ID 000316851100024
View details for PubMedID 23474467
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Switches, Switches, Every Where, In Any Drop We Drink
MOLECULAR CELL
2013; 49 (2): 232-233
Abstract
In this issue, Broussard et al. (2013) report genetic switches that regulate cell fate selection; a recombinase attachment site is embedded within a repressor coding sequence, such that integration truncates a proteolysis domain, stabilizing the repressor and setting the switch.
View details for DOI 10.1016/j.molcel.2013.01.005
View details for Web of Science ID 000314379400005
View details for PubMedID 23352244
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A survey of enabling technologies in synthetic biology.
Journal of biological engineering
2013; 7 (1): 13-?
Abstract
Realizing constructive applications of synthetic biology requires continued development of enabling technologies as well as policies and practices to ensure these technologies remain accessible for research. Broadly defined, enabling technologies for synthetic biology include any reagent or method that, alone or in combination with associated technologies, provides the means to generate any new research tool or application. Because applications of synthetic biology likely will embody multiple patented inventions, it will be important to create structures for managing intellectual property rights that best promote continued innovation. Monitoring the enabling technologies of synthetic biology will facilitate the systematic investigation of property rights coupled to these technologies and help shape policies and practices that impact the use, regulation, patenting, and licensing of these technologies.We conducted a survey among a self-identifying community of practitioners engaged in synthetic biology research to obtain their opinions and experiences with technologies that support the engineering of biological systems. Technologies widely used and considered enabling by survey participants included public and private registries of biological parts, standard methods for physical assembly of DNA constructs, genomic databases, software tools for search, alignment, analysis, and editing of DNA sequences, and commercial services for DNA synthesis and sequencing. Standards and methods supporting measurement, functional composition, and data exchange were less widely used though still considered enabling by a subset of survey participants.The set of enabling technologies compiled from this survey provide insight into the many and varied technologies that support innovation in synthetic biology. Many of these technologies are widely accessible for use, either by virtue of being in the public domain or through legal tools such as non-exclusive licensing. Access to some patent protected technologies is less clear and use of these technologies may be subject to restrictions imposed by material transfer agreements or other contract terms. We expect the technologies considered enabling for synthetic biology to change as the field advances. By monitoring the enabling technologies of synthetic biology and addressing the policies and practices that impact their development and use, our hope is that the field will be better able to realize its full potential.
View details for DOI 10.1186/1754-1611-7-13
View details for PubMedID 23663447
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A fully decompressed synthetic bacteriophage empty setX174 genome assembled and archived in yeast
VIROLOGY
2012; 434 (2): 278-284
Abstract
The 5386 nucleotide bacteriophage øX174 genome has a complicated architecture that encodes 11 gene products via overlapping protein coding sequences spanning multiple reading frames. We designed a 6302 nucleotide synthetic surrogate, øX174.1, that fully separates all primary phage protein coding sequences along with cognate translation control elements. To specify øX174.1f, a decompressed genome the same length as wild type, we truncated the gene F coding sequence. We synthesized DNA encoding fragments of øX174.1f and used a combination of in vitro- and yeast-based assembly to produce yeast vectors encoding natural or designer bacteriophage genomes. We isolated clonal preparations of yeast plasmid DNA and transfected E. coli C strains. We recovered viable øX174 particles containing the øX174.1f genome from E. coli C strains that independently express full-length gene F. We expect that yeast can serve as a genomic 'drydock' within which to maintain and manipulate clonal lineages of other obligate lytic phage.
View details for DOI 10.1016/j.virol.2012.09.020
View details for Web of Science ID 000312509300018
View details for PubMedID 23079106
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Refactored M13 Bacteriophage as a Platform for Tumor Cell Imaging and Drug Delivery
ACS SYNTHETIC BIOLOGY
2012; 1 (12): 576-582
Abstract
M13 bacteriophage is a well-characterized platform for peptide display. The utility of the M13 display platform is derived from the ability to encode phage protein fusions with display peptides at the genomic level. However, the genome of the phage is complicated by overlaps of key genetic elements. These overlaps directly couple the coding sequence of one gene to the coding or regulatory sequence of another, making it difficult to alter one gene without disrupting the other. Specifically, overlap of the end of gene VII and the beginning of gene IX has prevented the functional genomic modification of the N-terminus of p9. By redesigning the M13 genome to physically separate these overlapping genetic elements, a process known as "refactoring," we enabled independent manipulation of gene VII and gene IX and the construction of the first N-terminal genomic modification of p9 for peptide display. We demonstrate the utility of this refactored genome by developing an M13 bacteriophage-based platform for targeted imaging of and drug delivery to prostate cancer cells in vitro. This successful use of refactoring principles to re-engineer a natural biological system strengthens the suggestion that natural genomes can be rationally designed for a number of applications.
View details for DOI 10.1021/sb300052u
View details for Web of Science ID 000312679800002
View details for PubMedID 23656279
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Scaffold number in yeast signaling system sets tradeoff between system output and dynamic range
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (50): 20265-20270
Abstract
Although the proteins comprising many signaling systems are known, less is known about their numbers per cell. Existing measurements often vary by more than 10-fold. Here, we devised improved quantification methods to measure protein abundances in the Saccharomyces cerevisiae pheromone response pathway, an archetypical signaling system. These methods limited variation between independent measurements of protein abundance to a factor of two. We used these measurements together with quantitative models to identify and investigate behaviors of the pheromone response system sensitive to precise abundances. The difference between the maximum and basal signaling output (dynamic range) of the pheromone response MAPK cascade was strongly sensitive to the abundance of Ste5, the MAPK scaffold protein, and absolute system output depended on the amount of Fus3, the MAPK. Additional analysis and experiment suggest that scaffold abundance sets a tradeoff between maximum system output and system dynamic range, a prediction supported by recent experiments.
View details for DOI 10.1073/pnas.1004042108
View details for Web of Science ID 000298034800083
View details for PubMedID 22114196
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Editorial-Synthetic Biology
NUCLEIC ACIDS RESEARCH
2010; 38 (8): 2513-2513
View details for DOI 10.1093/nar/gkq221
View details for Web of Science ID 000277238900001
View details for PubMedID 20423911
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Gemini, a Bifunctional Enzymatic and Fluorescent Reporter of Gene Expression
PLOS ONE
2009; 4 (11)
Abstract
The development of collections of quantitatively characterized standard biological parts should facilitate the engineering of increasingly complex and novel biological systems. The existing enzymatic and fluorescent reporters that are used to characterize biological part functions exhibit strengths and limitations. Combining both enzymatic and fluorescence activities within a single reporter protein would provide a useful tool for biological part characterization.Here, we describe the construction and quantitative characterization of Gemini, a fusion between the beta-galactosidase (beta-gal) alpha-fragment and the N-terminus of full-length green fluorescent protein (GFP). We show that Gemini exhibits functional beta-gal activity, which we assay with plates and fluorometry, and functional GFP activity, which we assay with fluorometry and microscopy. We show that the protein fusion increases the sensitivity of beta-gal activity and decreases the sensitivity of GFP.Gemini is therefore a bifunctional reporter with a wider dynamic range than the beta-gal alpha-fragment or GFP alone. Gemini enables the characterization of gene expression, screening assays via enzymatic activity, and quantitative single-cell microscopy or FACS via fluorescence activity. The analytical flexibility afforded by Gemini will likely increase the efficiency of research, particularly for screening and characterization of libraries of standard biological parts.
View details for DOI 10.1371/journal.pone.0007569
View details for Web of Science ID 000271414600002
View details for PubMedID 19888458
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The Alpha Project: a model system for systems biology research
IET SYSTEMS BIOLOGY
2008; 2 (5): 222-233
Abstract
One goal of systems biology is to understand how genome-encoded parts interact to produce quantitative phenotypes. The Alpha Project is a medium-scale, interdisciplinary systems biology effort that aims to achieve this goal by understanding fundamental quantitative behaviours of a prototypic signal transduction pathway, the yeast pheromone response system from Saccharomyces cerevisiae. The Alpha Project distinguishes itself from many other systems biology projects by studying a tightly bounded and well-characterised system that is easily modified by genetic means, and by focusing on deep understanding of a discrete number of important and accessible quantitative behaviours. During the project, the authors have developed tools to measure the appropriate data and develop models at appropriate levels of detail to study a number of these quantitative behaviours. The authors have also developed transportable experimental tools and conceptual frameworks for understanding other signalling systems. In particular, the authors have begun to interpret system behaviours and their underlying molecular mechanisms through the lens of information transmission, a principal function of signalling systems. The Alpha Project demonstrates that interdisciplinary studies that identify key quantitative behaviours and measure important quantities, in the context of well-articulated abstractions of system function and appropriate analytical frameworks, can lead to deeper biological understanding. The authors' experience may provide a productive template for systems biology investigations of other cellular systems.
View details for DOI 10.1049/iet-syb:20080127
View details for Web of Science ID 000259928800003
View details for PubMedID 19045818
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Genomics - Reconstruction of the Genomes
SCIENCE
2008; 319 (5867): 1196-1197
View details for DOI 10.1126/science.1155749
View details for Web of Science ID 000253530600024
View details for PubMedID 18309068
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Stimulus design for model selection and validation in cell signaling
PLOS COMPUTATIONAL BIOLOGY
2008; 4 (2)
Abstract
Mechanism-based chemical kinetic models are increasingly being used to describe biological signaling. Such models serve to encapsulate current understanding of pathways and to enable insight into complex biological processes. One challenge in model development is that, with limited experimental data, multiple models can be consistent with known mechanisms and existing data. Here, we address the problem of model ambiguity by providing a method for designing dynamic stimuli that, in stimulus-response experiments, distinguish among parameterized models with different topologies, i.e., reaction mechanisms, in which only some of the species can be measured. We develop the approach by presenting two formulations of a model-based controller that is used to design the dynamic stimulus. In both formulations, an input signal is designed for each candidate model and parameterization so as to drive the model outputs through a target trajectory. The quality of a model is then assessed by the ability of the corresponding controller, informed by that model, to drive the experimental system. We evaluated our method on models of antibody-ligand binding, mitogen-activated protein kinase (MAPK) phosphorylation and de-phosphorylation, and larger models of the epidermal growth factor receptor (EGFR) pathway. For each of these systems, the controller informed by the correct model is the most successful at designing a stimulus to produce the desired behavior. Using these stimuli we were able to distinguish between models with subtle mechanistic differences or where input and outputs were multiple reactions removed from the model differences. An advantage of this method of model discrimination is that it does not require novel reagents, or altered measurement techniques; the only change to the experiment is the time course of stimulation. Taken together, these results provide a strong basis for using designed input stimuli as a tool for the development of cell signaling models.
View details for DOI 10.1371/journal.pcbi.0040030
View details for Web of Science ID 000255407800023
View details for PubMedID 18282085
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TABASCO: A single molecule, base-pair resolved gene expression simulator
BMC BIOINFORMATICS
2007; 8
Abstract
Experimental studies of gene expression have identified some of the individual molecular components and elementary reactions that comprise and control cellular behavior. Given our current understanding of gene expression, and the goals of biotechnology research, both scientists and engineers would benefit from detailed simulators that can explicitly compute genome-wide expression levels as a function of individual molecular events, including the activities and interactions of molecules on DNA at single base pair resolution. However, for practical reasons including computational tractability, available simulators have not been able to represent genome-scale models of gene expression at this level of detail.Here we develop a simulator, TABASCO http://openwetware.org/wiki/TABASCO, which enables the precise representation of individual molecules and events in gene expression for genome-scale systems. We use a single molecule computational engine to track individual molecules interacting with and along nucleic acid polymers at single base resolution. Tabasco uses logical rules to automatically update and delimit the set of species and reactions that comprise a system during simulation, thereby avoiding the need for a priori specification of all possible combinations of molecules and reaction events. We confirm that single molecule, base-pair resolved simulation using TABASCO (Tabasco) can accurately compute gene expression dynamics and, moving beyond previous simulators, provide for the direct representation of intermolecular events such as polymerase collisions and promoter occlusion. We demonstrate the computational capacity of Tabasco by simulating the entirety of gene expression during bacteriophage T7 infection; for reference, the 39,937 base pair T7 genome encodes 56 genes that are transcribed by two types of RNA polymerases active across 22 promoters.Tabasco enables genome-scale simulation of transcription and translation at individual molecule and single base-pair resolution. By directly representing the position and activity of individual molecules on DNA, Tabasco can directly test the effects of detailed molecular processes on system-wide gene expression. Tabasco would also be useful for studying the complex regulatory mechanisms controlling eukaryotic gene expression. The computational engine underlying Tabasco could also be adapted to represent other types of processive systems in which individual reaction events are organized across a single spatial dimension (e.g., polysaccharide synthesis).
View details for DOI 10.1186/1471-2105-8-480
View details for Web of Science ID 000253159400001
View details for PubMedID 18093293
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Synthetic genomics - Options for governance
BIOSECURITY AND BIOTERRORISM-BIODEFENSE STRATEGY PRACTICE AND SCIENCE
2007; 5 (4): 359-361
View details for DOI 10.1089/bsp.2007.0923
View details for Web of Science ID 000251948300015
View details for PubMedID 18081496
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Engineering life: Building a fab for biology
SCIENTIFIC AMERICAN
2006; 294 (6): 44-51
View details for Web of Science ID 000237445200027
View details for PubMedID 16711359
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Regulated cell-to-cell variation in a cell-fate decision system
NATURE
2005; 437 (7059): 699-706
Abstract
Here we studied the quantitative behaviour and cell-to-cell variability of a prototypical eukaryotic cell-fate decision system, the mating pheromone response pathway in yeast. We dissected and measured sources of variation in system output, analysing thousands of individual, genetically identical cells. Only a small proportion of total cell-to-cell variation is caused by random fluctuations in gene transcription and translation during the response ('expression noise'). Instead, variation is dominated by differences in the capacity of individual cells to transmit signals through the pathway ('pathway capacity') and to express proteins from genes ('expression capacity'). Cells with high expression capacity express proteins at a higher rate and increase in volume more rapidly. Our results identify two mechanisms that regulate cell-to-cell variation in pathway capacity. First, the MAP kinase Fus3 suppresses variation at high pheromone levels, while the MAP kinase Kss1 enhances variation at low pheromone levels. Second, pathway capacity and expression capacity are negatively correlated, suggesting a compensatory mechanism that allows cells to respond more precisely to pheromone in the presence of a large variation in expression capacity.
View details for DOI 10.1038/nature03998
View details for Web of Science ID 000232157900045
View details for PubMedID 16170311
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Signal transduction - Molecular monogamy
NATURE
2003; 426 (6967): 614-615
View details for DOI 10.1038/426614a
View details for Web of Science ID 000187132800023
View details for PubMedID 14668845
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Signal transduction. Decoding NF-kappaB signaling.
Science
2002; 298 (5596): 1189-1190
View details for PubMedID 12424362
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Intracellular kinetics of a growing virus: A genetically structured simulation for bacteriophage T7
BIOTECHNOLOGY AND BIOENGINEERING
1997; 55 (2): 375-389
Abstract
Viruses have evolved to efficiently direct the resources of their hosts toward their own reproduction. A quantitative understanding of viral growth will help researchers develop antiviral strategies, design metabolic pathways, construct vectors for gene therapy, and engineer molecular systems that self-assemble. As a model system we examine here the growth of bacteriophage T7 in Escherichia coli using a chemical-kinetic framework. Data published over the last three decades on the genetics, physiology, and biophysics of phage T7 are incorporated into a genetically structured simulation that accounts for entry of the T7 genome into its host, expression of T7 genes, replication of T7 DNA, assembly of T7 procapsids, and packaging of T7 DNA to finally produce intact T7 progeny. Good agreement is found between the simulated behavior and experimental observations for the shift in transcription capacity from the host to the phage, the initiation times of phage protein synthesis, and the intracellular assembly of both wild-type phage and a fast-growing deletion mutant. The simulation is utilized to predict the effect of antisense molecules targeted to different T7 mRNA. Further, a postulated mechanism for the down regulation of T7 transcription in vivo is quantitatively examined and shown to agree with available data. The simulation is found to be a useful tool for exploring and understanding the dynamics of virus growth at the molecular level. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 375-389, 1997.
View details for Web of Science ID A1997XH85500015
View details for PubMedID 18636496