Successes and failures in modular genetic engineering

Kittleson, Joshua T; Wu, Gabriel C.; Anderson, Janet S.

doi:10.1016/j.cbpa.2012.06.009

Cited by 61 publications

(59 citation statements)

References 117 publications

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“…Transcription factors can be toxic and exhibit slow growth when expressed above a critical threshold 41 . We measured the impact on cell growth by recording the OD 600 6 hours post-induction for each NOT gate at various levels of induction (Supplementary Figure 11).…”

Section: Resultsmentioning

confidence: 99%

Genomic mining of prokaryotic repressors for orthogonal logic gates

et al. 2013

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Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply “part mining” to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and do not interact with other promoters. Each repressor:promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOR gates, there are >1054 circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.

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Section: Resultsmentioning

confidence: 99%

Genomic mining of prokaryotic repressors for orthogonal logic gates

et al. 2013

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“…Current efforts have focused on approaches to limit the number of time-consuming steps required to characterize potential interactions and on identifying existing or engineered elements that act predictably when used in combination (26)(27)(28). However, these studies still suggest there are enough idiosyncratic interactions and context effects that it will be necessary to construct and measure many variants of a circuit to achieve desired function (29). For larger circuits, such approaches are necessarily limited in scope due to the difficulty in measuring large numbers of combinations (26,27).…”

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confidence: 99%

Composability of regulatory sequences controlling transcription and translation in Escherichia coli

Kosuri

Goodman

Cambray

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

410

453

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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.next-generation sequencing | synthetic biology | systems biology O rganisms can be engineered to produce chemical, material, fuel, and medical products that are often superior to nonbiological alternatives (1). Biotechnologists have sought to discover, improve, and industrialize such products through the use of recombinant DNA technologies (2, 3). In recent years, these efforts have increased in complexity from expressing a few genes at once to optimizing multicomponent circuits and pathways (4-7). To attain desired systems-level function reliably, careful and time-consuming optimization of individual components is required (8-11).To mitigate this slow trial-and-error optimization, two dominant approaches have taken hold. The first approach seeks to predict expression levels by elucidating the biophysical relationships between sequence and function. For example, several groups have modified promoters (12, 13) and ribosome binding sites (RBSs) (14-16) to see how small sequence changes affect transcription or translation. Such studies are fundamentally challenging due to the vastness of sequence space. In addition, because these approaches mostly look at either transcription or translation individually, they are rarely able to investigate interactions between these processes.The second approach uses combinations of individually characterized elements to attain desired expression without directly considering their DNA sequences (17-25). Current efforts have focused on approaches to limit the number of time-consuming steps required to characterize potential interactions and on identifying existing or engineered elements that act predictably when used in combination (26-28). However, these studies still suggest there are enough idiosyncratic interactions and context effects that it will be necessary to construct and measure many variants of a circuit to achieve desired function (29). For larger circuits, such approaches are necessarily limited in scope due to the difficulty in measuring large numbers of combinations (26, 27...

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“…How electronic circuit engineering can benefit the programming of complex genetic circuits for sophisticated functions in living cells, however, remains largely unexplored 33 . In this study, we present one of the largest transcriptional-regulator-based sequential-logic circuits developed thus far 34 , which comprises seven regulatory genes and 32 additional genetic parts.…”

Section: Discussionmentioning

confidence: 99%

Programming a Pavlovian-like conditioning circuit in Escherichia coli

et al. 2014

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Synthetic genetic circuits are programmed in living cells to perform predetermined cellular functions. However, designing higher-order genetic circuits for sophisticated cellular activities remains a substantial challenge. Here we program a genetic circuit that executes Pavlovianlike conditioning, an archetypical sequential-logic function, in Escherichia coli. The circuit design is first specified by the subfunctions that are necessary for the single simultaneous conditioning, and is further genetically implemented using four function modules. During this process, quantitative analysis is applied to the optimization of the modules and fine-tuning of the interconnections. Analogous to classical Pavlovian conditioning, the resultant circuit enables the cells to respond to a certain stimulus only after a conditioning process. We show that, although the conditioning is digital in single cells, a dynamically progressive conditioning process emerges at the population level. This circuit, together with its rational design strategy, is a key step towards the implementation of more sophisticated cellular computing.

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Successes and failures in modular genetic engineering

Cited by 61 publications

References 117 publications

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genomic mining of prokaryotic repressors for orthogonal logic gates

Composability of regulatory sequences controlling transcription and translation in Escherichia coli

Programming a Pavlovian-like conditioning circuit in Escherichia coli

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