A partially self-regenerating synthetic cell

Self-regeneration is a fundamental function of all living systems. Here we demonstrate partial molecular self-regeneration in a synthetic cell. By implementing a minimal transcription-translation system within microfluidic reactors, the system is able to regenerate essential protein components from DNA templates and sustain synthesis activity for over a day. By quantitating genotype-phenotype relationships combined with computational modeling we find that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieve simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell. A fundamental function of living systems is regenerating essential components. Here the authors design an artificial cell using a minimal transcription-translation system in microfluidic reactors for sustained regeneration of multiple essential proteins

iSLIM: a comprehensive approach to mapping and characterizing gene regulatory networks

Mapping gene regulatory networks is a significant challenge in systems biology, yet only a few methods are currently capable of systems-level identification of transcription factors (TFs) that bind a specific regulatory element. We developed a microfluidic method for integrated systems-level interaction mapping of TF-DNA interactions, generating and interrogating an array of 423 full-length Drosophila TFs. With integrated systems-level interaction mapping, it is now possible to rapidly and quantitatively map gene regulatory networks of higher eukaryote

A Systems Approach to Measuring the Binding Energy Landscapes of Transcription Factors

A major goal of systems biology is to predict the function of biological networks. Although network topologies have been successfully determined in many cases, the quantitative parameters governing these networks generally have not. Measuring affinities of molecular interactions in high-throughput format remains problematic, especially for transient and low-affinity interactions. We describe a high-throughput microfluidic platform that measures such properties on the basis of mechanical trapping of molecular interactions. With this platform we characterized DNA binding energy landscapes for four eukaryotic transcription factors; these landscapes were used to test basic assumptions about transcription factor binding and to predict their in vivo function

Microfluidic Large-Scale Integration

We developed high-density microfluidic chips that contain plumbing networks with thousands of micromechanical valves and hundreds of individually addressable chambers. These fluidic devices are analogous to electronic integrated circuits fabricated using large-scale integration. A key component of these networks is the fluidic multiplexor, which is a combinatorial array of binary valve patterns that exponentially increases the processing power of a network by allowing complex fluid manipulations with a minimal number of inputs. We used these integrated microfluidic networks to construct the microfluidic analog of a comparator array and a microfluidic memory storage device whose behavior resembles random-access memory

An in vitro microfluidic approach to generating protein-interaction networks

We developed an in vitro protein expression and interaction analysis platform based on a highly parallel and sensitive microfluidic affinity assay, and used it for 14,792 on-chip experiments, which exhaustively measured the protein-protein interactions of 43 Streptococcus pneumoniae proteins in quadruplicate. The resulting network of 157 interactions was denser than expected based on known networks. Analysis of the network revealed previously undescribed physical interactions among members of some biochemical pathways

Rapid cell-free forward engineering of novel genetic ring oscillators

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the 'repressilator,' a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hours. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior

Cell-free gene-regulatory network engineering with synthetic transcription factors

Gene-regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein-protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here, we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and co-operativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription-factor binding-energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene-regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene-regulatory networks and for studying the biophysics of transcriptional regulation

A 1024-sample serum analyzer chip for cancer diagnostics

We present a platform that combines microarrays and microfluidic techniques to measure four protein biomarkers in 1024 serum samples for a total of 4096 assays per device. Detection is based on a surface fluorescence sandwich immunoassay with a limit of detection of similar to 1 pM for most of the proteins measured: PSA, TNF-alpha, IL-1 beta, and IL-6. To validate the utility of our platform, we measured these four biomarkers in 20 clinical human serum samples, 10 from prostate cancer patients and 10 female and male controls. We compared the results of our platform to a conventional ELISA and found a good correlation between them. However, compared to a classical ELISA, our device reduces the total cost of reagents by 4 orders of magnitude while increasing throughput by 2 orders of magnitude. Overall, we demonstrate an integrated approach to perform low-cost and rapid quantification of protein biomarkers from over one thousand serum samples. This new high-throughput technology will have a significant impact on disease diagnosis and management