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Engineered microorganisms such as the probiotic strain Escherichia coli Nissle 1917 (EcN) offer a strategy to sense and modulate the concentration of metabolites or therapeutics in the gastrointestinal tract. Here, we present an approach to regulate the production of the depression-associated metabolite gamma-aminobutyric acid (GABA) in EcN using genetic circuits that implement negative feedback. We engineered EcN to produce GABA by overexpressing glutamate decarboxylase and applied an intracellular GABA biosensor to identify growth conditions that improve GABA biosynthesis. We next employed characterized genetically encoded NOT gates to construct genetic circuits with layered feedback to control the rate of GABA biosynthesis and the concentration of GABA produced. Looking ahead, this approach may be utilized to design feedback control of microbial metabolite biosynthesis to achieve designable smart microbes that act as living therapeutics.

 

Abstract We describe a new transit-detection algorithm designed to detect single-transit events in discontinuous Perkins INfrared Exosatellite Survey (PINES) observations of L and T dwarfs. We use this algorithm to search for transits in 131 PINES light curves and identify two transit candidates: 2MASS J18212815+1414010 (2MASS J1821+1414) and 2MASS J08350622+1953050 (2MASS J0835+1953). We disfavor 2MASS J1821+1414 as a genuine transit candidate due to the known variability properties of the source. We cannot rule out the planetary nature of 2MASS J0835+1953's candidate event and perform follow-up observations in an attempt to recover a second transit. A repeat event has yet to be observed, but these observations suggest that target variability is an unlikely cause of the candidate transit. We perform a Markov Chain Monte Carlo simulation of the light curve and estimate a planet radius ranging from 4.2 − 1.6 + 3.5 R ⊕ to 5.8 − 2.1 + 4.8 R ⊕ , depending on the host’s age. Finally, we perform an injection and recovery simulation on our light-curve sample. We inject planets into our data using measured M-dwarf planet occurrence rates and attempt to recover them using our transit-search algorithm. Our detection rates suggest that, assuming M-dwarf planet occurrence rates, we should have roughly a 1% chance of detecting a candidate that could cause the transit depth we observe for 2MASS J0835+1953. If 2MASS J0835+1953 b is confirmed, it would suggest an enhancement in the occurrence of short-period planets around L and T dwarfs in comparison to M dwarfs, which would challenge predictions from planet formation models. 

Abstract We describe the Perkins INfrared Exosatellite Survey (PINES), a near-infrared photometric search for short-period transiting planets and moons around a sample of 393 spectroscopically confirmed L- and T-type dwarfs. PINES is performed with Boston University’s 1.8 m Perkins Telescope Observatory, located on Anderson Mesa, Arizona. We discuss the observational strategy of the survey, which was designed to optimize the number of expected transit detections, and describe custom automated observing procedures for performing PINES observations. We detail the steps of the PINES Analysis Toolkit ( PAT ), software that is used to create light curves from PINES images. We assess the impact of second-order extinction due to changing precipitable water vapor on our observations and find that the magnitude of this effect is minimized in Mauna Kea Observatories J band. We demonstrate the validity of PAT through the recovery of a transit of WASP-2 b and known variable brown dwarfs, and use it to identify a new variable L/T transition object: the T2 dwarf WISE J045746.08-020719.2. We report on the measured photometric precision of the survey and use it to estimate our transit-detection sensitivity. We find that for our median brightness targets, assuming contributions from white noise only, we are sensitive to the detection of 2.5 R ⊕ planets and larger. PINES will test whether the increase in sub-Neptune-sized planet occurrence with decreasing host mass continues into the L- and T-dwarf regime.