Gene-circuit therapy on the horizon: synthetic biology tools for engineered therapeutics

AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks

Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. The emerging field of diverse intelligence investigates the problem-solving capacities of unconventional agents. However, few quantitative tools exist for exploring the competencies of non-conventional systems. Here, we view gene regulatory networks (GRNs) as agents navigating a problem space and develop automated tools to map the robust goal states GRNs can reach despite perturbations. Our contributions include: (1) Adapting curiosity-driven exploration algorithms from AI to discover the range of reachable goal states of GRNs, and (2) Proposing empirical tests inspired by behaviorist approaches to assess their navigation competencies. Our data shows that models inferred from biological data can reach a wide spectrum of steady states, exhibiting various competencies in physiological network dynamics without requiring structural changes in network properties or connectivity. We also explore the applicability of these 'behavioral catalogs' for comparing evolved competencies across biological networks, for designing drug interventions in biomedical contexts and synthetic gene networks for bioengineering. These tools and the emphasis on behavior-shaping open new paths for efficiently exploring the complex behavior of biological networks. For the interactive version of this paper, please visit https://developmentalsystems.org/curious-exploration-of-grn-competencies.

Evaluation of Human Performance Aiding Live Synthetically Engineered Bacteria in a Gut-on-a-Chip

Synbiotics are a new class of live therapeutics employing engineered genetic circuits. The rapid adoption of genetic editing tools has catalyzed the expansion of possible synbiotics, exceeding traditional testing paradigms in terms of both throughput and model complexity. Herein, we present a simplistic gut-chip model using common Caco2 and HT-29 cell lines to establish a dynamic human screening platform for a cortisol sensing tryptamine producing synbiotic for cognitive performance sustainment. The synbiotic, SYN, was engineered from the common probiotic E. coli Nissle 1917 strain. It had the ability to sense cortisol at physiological concentrations, resulting in the activation of a genetic circuit that produces tryptophan decarboxylase and converts bioavailable tryptophan to tryptamine. SYN was successfully cultivated within the gut-chip showing log-phase growth comparable to the wild-type strain. Tryptophan metabolism occurred quickly in the gut compartment when exposed to 5 μM cortisol, resulting in the complete conversion of bioavailable tryptophan into tryptamine. The flux of tryptophan and tryptamine from the gut to the vascular compartment of the chip was delayed by 12 h, as indicated by the detectable tryptamine in the vascular compartment. The gut-chip provided a stable environment to characterize the sensitivity of the cortisol sensor and dynamic range by altering cortisol and tryptophan dosimetry. Collectively, the human gut-chip provided human relevant apparent permeability to assess tryptophan and tryptamine metabolism, production, and transport, enabled host analyses of cellular viability and pro-inflammatory cytokine secretion, and succeeded in providing an efficacy test of a novel synbiotic. Organ-on-a-chip technology holds promise in aiding traditional therapeutic pipelines to more rapidly down select high potential compounds that reduce the failure rate and accelerate the opportunity for clinical intervention.

Genetic physical unclonable functions in human cells

A physical unclonable function (PUF) is a physical entity that provides a measurable output that can be used as a unique and irreproducible identifier for the artifact wherein it is embedded. Popularized by the electronics industry, silicon PUFs leverage the inherent physical variations of semiconductor manufacturing to establish intrinsic security primitives for attesting integrated circuits. Owing to the stochastic nature of these variations, photolithographically manufactured silicon PUFs are impossible to reproduce (thus unclonable). Inspired by the success of silicon PUFs, we sought to create the first generation of genetic PUFs in human cells. We demonstrate that these PUFs are robust (i.e., they repeatedly produce the same output), unique (i.e., they do not coincide with any other identically produced PUF), and unclonable (i.e., they are virtually impossible to replicate). Furthermore, we demonstrate that CRISPR-engineered PUFs (CRISPR-PUFs) can serve as a foundational principle for establishing provenance attestation protocols.