The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP.

We expanded the mechanistic capability of small RNAs by creating an entirely synthetic mode of regulation: small transcription activating RNAs (STARs). Using two strategies, we engineered synthetic STAR regulators to disrupt the formation of an intrinsic transcription terminator placed upstream of a gene in Escherichia coli. This resulted in a group of four highly orthogonal STARs that had up to 94-fold activation. By systematically modifying sequence features of this group, we derived design principles for STAR function, which we then used to forward engineer a STAR that targets a terminator found in the Escherichia coli genome. Finally, we showed that STARs could be combined in tandem to create previously unattainable RNA-only transcriptional logic gates. STARs provide a new mechanism of regulation that will expand our ability to use small RNAs to construct synthetic gene networks that precisely control gene expression.

There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections.

Growth rate and metabolic state of bacteria have been separately shown to affect antibiotic efficacy 1-3 . However, the two are interrelated as bacterial growth inherently imposes a metabolic burden 4 ; thus, determining individual contributions from each is challenging 5,6 . Indeed, faster growth is often correlated with increased antibiotic efficacy 7,8 ; however, the concurrent role of metabolism in that relationship has not been well characterized. As a result, a clear understanding of the interdependence between growth and metabolism, and their implications for antibiotic Reprints and permissions information is available at www.nature.com/reprints.