Influence of Environmental Conditions on the Escape Rates of Biocontained Genetically Engineered Microbes.

The development of genetically engineered microbes (GEMs) has resulted in an urgent need to control their persistence in the environment. The use of biocontainment such as kill switches is a critical approach to prevent the unintended proliferation of GEMs; however, the effectiveness of kill switches─reported as escape rates, i.e.

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia.

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks.

Genetically stable CRISPR-based kill switches for engineered microbes.

Microbial biocontainment is an essential goal for engineering safe, next-generation living therapeutics. However, the genetic stability of biocontainment circuits, including kill switches, is a challenge that must be addressed. Kill switches are among the most difficult circuits to maintain due to the strong selection pressure they impart, leading to high potential for evolution of escape mutant populations.

Engineering ligand-specific biosensors for aromatic amino acids and neurochemicals.

Microbial biosensors have diverse applications in metabolic engineering and medicine. Specific and accurate quantification of chemical concentrations allows for adaptive regulation of enzymatic pathways and temporally precise expression of diagnostic reporters. Although biosensors should differentiate structurally similar ligands with distinct biological functions, such specific sensors are rarely found in nature and challenging to create.

Engineering microbial diagnostics and therapeutics with smart control.

Microbes have become an increasingly powerful chassis for developing diagnostic and therapeutic technologies. While many of the earlier engineering efforts used microbes that expressed relevant proteins constitutively, more microbes are being engineered to express them with region-selectivity and disease-responsiveness through biosensors. Such 'smart' microbes have been developed to diagnose and treat a wide range of disorders and diseases, including bacterial infections, cancers, inflammatory disorders, and metabolic disorders.

Biosensing in Smart Engineered Probiotics.

Engineered microbes are exciting alternatives to current diagnostics and therapeutics. Researchers have developed a wide range of genetic tools and parts to engineer probiotic and commensal microbes. Among these tools and parts, biosensors allow the microbes to sense and record or to sense and respond to chemical and environmental signals in the body, enabling them to report on health conditions of the animal host and/or deliver therapeutics in a controlled manner.

Molecular Toolkit for Gene Expression Control and Genome Modification in Rhodococcus opacus PD630.

Rhodococcus opacus PD630 is a non-model Gram-positive bacterium that possesses desirable traits for lignocellulosic biomass conversion. In particular, it has a relatively rapid growth rate, exhibits genetic tractability, produces high quantities of lipids, and can tolerate and consume toxic lignin-derived aromatic compounds. Despite these unique, industrially relevant characteristics, R.

Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription.

Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest.