Researchers Develop Genetic Tools to Engineer Common Gut Bacterium
News Jul 10, 2015
MIT's Timothy Lu and his colleagues developed genetic tools based on unique promoter and ribosome-binding sites in the bacterium to be used as sensors, memory switches, and circuits to control bacterial gene expression.
Such tools have been developed for other gut bacteria like Escherichia coliand Lactococcus lactis, but they are only present in the gut at low levels, the researchers noted, while B. thetaiotaomicron is typically more common.
"We wanted to work with strains like B. thetaiotaomicron that are present in many people in abundant levels, and can stably colonize the gut for long periods of time," said Lu, an associate professor of biological engineering, in a statement.
Lu and his colleagues combined certain promoters and ribosome-binding sites to generate parts that could be used to engineer systems in B. thetaiotaomicron.
They first constructed four promoter variants based on the bacterial constitutive promoter sigma factor BT1311 that, when tied to a luciferase reporter gene, exhibited a 20-fold range of gene expression.
By adding these promoters to RBSs of varying strengths, the researchers also developed an RBS library that spans a more than 10,000-fold range of gene expression. To further fine-tune their control of bacterial gene expression, the researchers uncovered a set of eight RBS sequences that yielded a 1,000-fold gene-expression range at about even increments.
"Using these parts, we built four sensors that can be encoded in the bacterium's DNA that respond to a signal to switch genes on and off inside B. thetaiotaomicron," Christopher Voigt, a professor of biological engineering at MIT, said in a statement.
For instance, the researchers took advantage of the B. thetaiotaomicronrhamnose metabolic pathway to generate a rhamnose-inducible system in which RhaR activates transcription at the PBT3763 promoter. To test this system, they paired it with a luciferase reporter gene, and they noted its expression was conditional upon rhamnose concentration.
They also developed inducible systems based on Bacteroides hybrid two-component systems induced by chondroitin sulfate and arabinogalactan, respectively, as well as an isopropyl b-D-1-thiogalactopyranoside-inducible system based on the E. coli LacI system.
Meanwhile, the MIT team also designed a serine integrase-based memory circuit — serine integrases catalyze unidirectional inversion of DNA between two recognition sequences — so that they'd have a signal to indicate when B. thetaiotaomicron encountered certain stimuli of interest, such as inflammation.
After identifying serine integrases that work in B. thetaiotaomicron, the researchers placed one under the control of the rhamnose-inducible promoter to develop an inducible memory switch. This switch, the researchers reported, responded to increasing concentrations of rhamnose.
To develop a more complex gene circuit, the researchers turned to a CRISPR interference-mediated system to knock down gene expression and affect the metabolic capacity of B. thetaiotaomicron and its resistance to certain antimicrobial peptides.
For example, they designed a guide RNA to repress BT1754, which is essential for fructose metabolism, and integrated it into the B. thetaiotaomicron with an IPTG-inducible dCas9 cassette. Neither induction nor repression of BT175 affected growth on glucose media, the researchers reported, but its induction did decrease growth on MM-fructose.
The researchers tested these systems out in the mouse gut, finding signs of luciferase activity in mouse feces when the mice were exposed to system triggers like arabinogalactan. In addition, the memory switch exhibited signs of switching after mice colonized with bacteria containing it were exposed to rhamnose.
These tools, the researchers said, set the stage for microbiome engineering.
They argued that B. thetaiotaomicron could be used to keep an eye on the gut microbiome and serve as a diagnostic or therapeutic tool.
"[W]e want to have high sensitivity and specificity when diagnosing disease with engineered bacteria," Lu said. "To achieve this, we could engineer bacteria to detect multiple biomarkers, and only trigger a response when they are all present."