Probing the operability regime of an engineered ribocomputing unit in terms of dynamic range maintenance with extracellular changes and time.

Synthetic biology aims at engineering gene regulatory circuits to end with cells (re)programmed on purpose to implement novel functions or discover natural behaviors. However, one overlooked question is whether the resulting circuits perform as intended in variety of environments or with time. Here, we considered a recently engineered genetic system that allows programming the cell to work as a minimal computer (arithmetic logic unit) in order to analyze its operability regime. This system involves transcriptional and post-transcriptional regulations. In particular, we studied the analog behavior of the system, the effect of physicochemical changes in the environment, the impact on cell growth rate of the heterologous expression, and the ability to maintain the arithmetic functioning over time. Conclusively, our results suggest 1) that there are wide input concentration ranges that the system can correctly process, the resulting outputs being predictable with a simple mathematical model, 2) that the engineered circuitry is quite sensitive to temperature effects, 3) that the expression of heterologous small RNAs is costly for the cell, not only of heterologous proteins, and 4) that a proper genetic reorganization of the system to reduce the amount of heterologous DNA in the cell can improve its evolutionary stability.

Boolean Computation in Plants Using Post-translational Genetic Control and a Visual Output Signal.

Due to autotrophic growing capacity and extremely rich secondary metabolism, plants should be preferred targets of synthetic biology. However, developments in plants usually run below those in other taxonomic groups. In this work we engineered genetic circuits capable of logic YES, OR and AND Boolean computation in plant tissues with a visual output signal. The circuits, which are deployed by means of Agrobacterium tumefaciens, perform with the conditional activity of the MYB transcription factor Rosea1 from Antirrhinum majus inducing the accumulation of anthocyanins, plant endogenous pigments that are directly visible to the naked eye or accurately quantifiable by spectrophotometric analysis. The translational fusion of Rosea1 to several viral proteins, such as potyvirus NIb or fragments thereof, rendered the transcription factor inactive. However, anthocyanin accumulation could be restored by inserting protease cleavage sites between both moieties of the fusion and by coexpressing specific proteases, such as potyvirus nuclear inclusion a protease.

Binary addition in a living cell based on riboregulation.

Synthetic biology aims at (re-)programming living cells like computers to perform new functions for a variety of applications. Initial work rested on transcription factors, but regulatory RNAs have recently gained much attention due to their high programmability. However, functional circuits mainly implemented with regulatory RNAs are quite limited. Here, we report the engineering of a fundamental arithmetic logic unit based on de novo riboregulation to sum two bits of information encoded in molecular concentrations. Our designer circuit robustly performs the intended computation in a living cell encoding the result as fluorescence amplitudes. The whole system exploits post-transcriptional control to switch on tightly silenced genes with small RNAs, together with allosteric transcription factors to sense the molecular signals. This important result demonstrates that regulatory RNAs can be key players in synthetic biology, and it paves the way for engineering more complex RNA-based biocomputers using this designer circuit as a building block.

A network model of the molecular organization of chromatin in Drosophila.

Chromatin governs gene regulation and genome maintenance, yet a substantial fraction of the chromatin proteome is still unexplored. Moreover, a global model of the chromatin protein network is lacking. By screening >100 candidates we identify 42 Drosophila proteins that were not previously associated with chromatin, which all display specific genomic binding patterns. Bayesian network modeling of the binding profiles of these and 70 known chromatin components yields a detailed blueprint of the in vivo chromatin protein network. We demonstrate functional compartmentalization of this network, and predict functions for most of the previously unknown chromatin proteins, including roles in DNA replication and repair, and gene activation and repression.