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As engineered microbes are used in increasingly diverse applications across human health and bioproduction, the field of synthetic biology will need to focus on strategies that stabilize and contain the function of these populations within target environments. To this end, recent advancements have created layered sensing circuits that can compute cell survival, genetic contexts that are less susceptible to mutation, burden, and resource control circuits, and methods for population variability reduction. These tools expand the potential for real-world deployment of complex microbial systems by enhancing their environmental robustness and functional stability in the face of unpredictable host response and evolutionary pressure. [Display omitted] • Environmentally responsive survival circuitry enable synthetic cell containment. • Increased genetic stability by engineering sequence and host context. • Control circuits for burden response, resource allocation, and variability reduction. • Tying evolutionary pressure to population production for improved performance. [ABSTRACT FROM AUTHOR]

Synthetic biology has developed sophisticated cellular biosensors to detect and respond to human disease. However, biosensors have not yet been engineered to detect specific extracellular DNA sequences and mutations. Here, we engineered naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells, organoids, and tumors. We characterized the functionality of the biosensors in vitro with coculture assays and then validated them in vivo with sensor bacteria delivered to mice harboring colorectal tumors. We observed horizontal gene transfer from the tumor to the sensor bacteria in our mouse model of CRC. This cellular assay for targeted, CRISPR-discriminated horizontal gene transfer (CATCH) enables the biodetection of specific cell-free DNA. [ABSTRACT FROM AUTHOR]

Introduction: Ross operation provides young adult and pediatric patients a living valve with excellent hemodynamics and no lifelong anticoagulation. However, autograft dilatation is a concern when it leads to aneurysm formation and autograft insufficiency requiring reoperation. Computational simulations of autograft remodeling are potentially effective to predict autograft dilatation, but require zero-pressure geometry and patient-specific material properties for accuracy. Hypothesis: We hypothesized that pulmonary autograft wall stresses estimated from computational simulations using in-vivo imaging would reasonably correlate with the gold standard, wall stresses determined computationally using ex-vivo autograft specimens at zeto-pressure. We recently showed that autograft wall stresses significantly increased immediately after the Ross operation. Our goal was to compare autograft wall stresses based on in-vivo geometry to those based on ex-vivo autografts. Methods: Magnetic resonance imaging (MRI) was obtained in pre-operative Ross patients and used to reconstruct in-vivo autograft geometry. Pre-stress (zero-pressure) geometry was determined. As controls, pulmonary autografts explanted from normal donor hearts underwent micro-computed tomography scans for reconstruction of ex-vivo geometry. Biaxial stretch testing was performed on both intraoperative tissue from Ross patients and on ex-vivo autografts to determine patient-specific material properties. Finite element simulations using LS-DYNA were performed to determine wall stresses. Results: Imaging from ex-vivo pulmonary autografts (n=6) and Ross patients (n=6) were obtained. Peak stresses were 93 kPa for ex-vivo vs. 113 kPa for in-vivo autografts at 25mmHg and 448kPa vs. 558 kPa, respectively at 120mmHg. Conclusions: Wall stresses at pulmonary and systemic systolic pressure predicted by in-vivo MRI imaging reasonably correlated with wall stresses based upon ex-vivo autograft tissue. Computational simulations using in-vivo imaging provides a suitable surrogate for the gold standard simulations using ex-vivo tissue specimens and broadens clinical applicability of computational simulations for patient-specific outcomes. [ABSTRACT FROM AUTHOR]