A Synthetic Multicellular Memory Device.

Changing environments pose a challenge to living organisms. Cells need to gather and process incoming information, adapting to changes in predictable ways. This requires in particular the presence of memory, which allows different internal states to be stored. Biological memory can be stored by switches that retain information on past and present events. Synthetic biologists have implemented a number of memory devices for biological applications, mostly in single cells. It has been shown that the use of multicellular consortia provides interesting advantages to implement biological circuits. Here we show how to build a synthetic biological memory switch using an eukaryotic consortium. We engineered yeast cells that can communicate and retain memory of changes in the extracellular environment. These cells were able to produce and secrete a pheromone and sense a different pheromone following NOT logic. When the two strains were cocultured, they behaved as a double-negative-feedback motif with memory. In addition, we showed that memory can be effectively changed by the use of external inputs. Further optimization of these modules and addition of other cells could lead to new multicellular circuits that exhibit memory over a broad range of biological inputs.

Synthetic biology: insights into biological computation.

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia.

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit's complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined.

Novel RasGRF1-derived Tat-fused peptides inhibiting Ras-dependent proliferation and migration in mouse and human cancer cells.

Mutations of RAS genes are critical events in the pathogenesis of different human tumors and Ras proteins represent a major clinical target for the development of specific inhibitors to use as anticancer agents. Here we present RasGRF1-derived peptides displaying both in vitro and in vivo Ras inhibitory properties. These peptides were designed on the basis of the down-sizing of dominant negative full-length RasGRF1 mutants. The over-expression of these peptides can revert the phenotype of K-RAS transformed mouse fibroblasts to wild type, as monitored by several independent biological readouts, including Ras-GTP intracellular levels, ERK activity, morphology, proliferative potential and anchorage independent growth. Fusion of the RasGRF1-derived peptides with the Tat protein transduction domain allows their uptake into mammalian cells. Chemically synthesized Tat-fused peptides, reduced to as small as 30 residues on the basis of structural constraints, retain Ras inhibitory activity. These small peptides interfere in vitro with the GEF catalyzed nucleotide dissociation and exchange on Ras, reduce cell proliferation of K-RAS transformed mouse fibroblasts, and strongly reduce Ras-dependent IGF-I-induced migration and invasion of human bladder cancer cells. These results support the use of RasGRF1-derived peptides as model compounds for the development of Ras inhibitory anticancer agents.

Oscillations in Cdc14 release and sequestration reveal a circuit underlying mitotic exit.

In budding yeast, the phosphatase Cdc14 orchestrates progress through anaphase and mitotic exit, thereby resetting the cell cycle for a new round of cell division. Two consecutive pathways, Cdc fourteen early anaphase release (FEAR) and mitotic exit network (MEN), contribute to the progressive activation of Cdc14 by regulating its release from the nucleolus, where it is kept inactive by Cfi1. In this study, we show that Cdc14 activation requires the polo-like kinase Cdc5 together with either Clb-cyclin-dependent kinase (Cdk) or the MEN kinase Dbf2. Once active, Cdc14 triggers a negative feedback loop that, in the presence of stable levels of mitotic cyclins, generates periodic cycles of Cdc14 release and sequestration. Similar phenotypes have been described for yeast bud formation and centrosome duplication. A common theme emerges where events that must happen only once per cycle, although intrinsically capable of oscillations, are limited to one occurrence by the cyclin-Cdk cell cycle engine.

The influence of catalysis on mad2 activation dynamics.

Mad2 is a key component of the spindle assembly checkpoint, a safety device ensuring faithful sister chromatid separation in mitosis. The target of Mad2 is Cdc20, an activator of the anaphase-promoting complex/cyclosome (APC/C). Mad2 binding to Cdc20 is a complex reaction that entails the conformational conversion of Mad2 from an open (O-Mad2) to a closed (C-Mad2) conformer. Previously, it has been hypothesized that the conversion of O-Mad2 is accelerated by its conformational dimerization with C-Mad2. This hypothesis, known as the Mad2-template hypothesis, is based on the unproven assumption that the natural conversion of O-Mad2 required to bind Cdc20 is slow. Here, we provide evidence for this fundamental assumption and demonstrate that conformational dimerization of Mad2 accelerates the rate of Mad2 binding to Cdc20. On the basis of our measurements, we developed a set of rate equations that deliver excellent predictions of experimental binding curves under a variety of different conditions. Our results strongly suggest that the interaction of Mad2 with Cdc20 is rate limiting for activation of the spindle checkpoint. Conformational dimerization of Mad2 is essential to accelerate Cdc20 binding, but it does not modify the equilibrium of the Mad2:Cdc20 interaction, i.e., it is purely catalytic. These results surpass previously formulated objections to the Mad2-template model and predict that the release of Mad2 from Cdc20 is an energy-driven process.

The isolated catalytic hairpin of the Ras-specific guanine nucleotide exchange factor Cdc25Mm retains nucleotide dissociation activity but has impaired nucleotide exchange activity.

Cdc25Mm is a mammalian Ras-specific guanine nucleotide exchange factor (GEF). By homology modeling we show that it shares with Sos-GEF the structure of the putative catalytic HI hairpin where the dominant negative T1184E mutation is located. Similarly to Cdc25MmT1184E, the isolated wild-type and mutant hairpins retain the ability to displace Ras-bound nucleotide, originate a stable Ras/GEF complex and downregulate the Ras pathway in vivo. These results indicate that nucleotide re-entry and Ras/GEF dissociation--final steps in the GEF catalytic cycle--require GEF regions different from the HI hairpin. GEF down-sizing could lead to development of novel Ras inhibitors.