Search NASA⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20190000295

Automating Microbial Directed Evolution For Bioengineering Applications

Lee, Alonzo·Demachkie, Isabella Siham·Sardesh, Nina·Arismendi, Dillon·Ouandji, Cynthia·Wang, Jonathan·Blaich, Justin·Gentry, Diana
View original source ↗Export metadata ↓

Abstract

From a micro-biology perspective, directed evolution is a technique that uses controlled environmental pressures to select for a desired phenotype. Directed evolution has the distinct advantage over rational design of not needing extensive knowledge of the genome or pathways associated with a microorganism to induce phenotypes. However, there are currently limitations to the applicability of this technique including being time-consuming, error-prone, and dependent on existing assays that may lack selectivity for the given phenotype. The AADEC (Autonomous Adaptive Directed Evolution Chamber) system is a proof-of-concept instrument to automate and improve the technique such that directed evolution can be used more effectively as a general bioengineering tool. A series of tests using the automated system and comparable by-hand survival assay measurements have been carried out using UV-C radiation and Escherichia coli cultures in order to demonstrate the advantages of the AADEC versus traditional implementations of directed evolution such as random mutagenesis. AADEC uses UV-C exposure as both a source of environmental stress and mutagenesis, so in order to evaluate the UV-C tolerance obtained from the cultures, a manual UV-C exposure survival assay was developed alongside the device to compare the survival fractions at a fixed dosage. This survival assay involves exposing E. coli to UV-C radiation using a custom-designed exposure hood to control the flux and dose. Surviving cells are counted then transferred to the next iteration and so on for several iterations to calculate the survival fractions for each exposure iteration.This survival assay primarily serves as a baseline for the AADEC device, allowing quantification of the differences between the AADEC system over the manual approach. The primary data of comparison is survival fractions; this is obtained by optical density and plate counts in the manual assay and by optical density growth curve fits pre- and post-exposure in the automated case. This data can then be compiled to calculate trends over the iterations to characterize increasing UV-C resistance of the E.coli strains. The observed trends are statistically indistinguishable through several iterations from both sources.

Explore related subjects

BioengineeringAutomatingMicrobial Evolution

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lee, Alonzo, Demachkie, Isabella Siham, Sardesh, Nina, Arismendi, Dillon, Ouandji, Cynthia, Wang, Jonathan, Blaich, Justin, Gentry, Diana. 2016-12-12. Automating Microbial Directed Evolution For Bioengineering Applications. https://ntrs.nasa.gov/citations/20190000295

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2018

Influence of Load Profile on Biomechanics of the Squat and Deadlift

Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to counteract the effect reduced gravity has on the body. Astronauts will exercise on a flywheel based device on the second Orion Exploration Mission (EM2). The effect that the flywheel load profile has on biomechanics is unknown when compared to free weights or a simulated free weight profile. The purpose of this evaluation is to compare the differences in lower body kinematics and kinetics between the flywheel and free weight profile. Test subjects were instrumented with reflective markers for motion capture data collection while exercising on the Device for Aerobic and Resistive Training (DART) prototype developed by TDA Research, Inc. of Wheat Ridge, CO. Exercises performed were either the squat while wearing a harness or deadlift while grasping a T-bar, both of which interfaced with the DART through a rope cable. The DART, a motorized device controlled via software, is capable of producing different load profiles. Profiles include simulated free weights with adjustable eccentric overload capability and flywheel. Test variables included the applied device load and the load profile, both set through the DART software interface. Motion capture data was collected with a 12 camera system (Smart-DX, BTS Bioengineering, Brooklyn, NY). Bilateral ground reaction force data were collected with force plates (P6000, BTS Bioengineering). DART cable force was recorded through an internal load cell. Data was collected from a total of four test subjects. The three repetition maximum was determined for each test subject for both squat and deadlift. High, medium and low loads were determined based on this maximum. The test subject performed five repetitions of each exercise at each load and each test trial was repeated twice. Cadence was controlled during exercising. Biomechanical data were used to drive the models utilizing the OpenSim software platform. Subject specific models were scaled to match the anthropometrics of the test subjects and used to estimate the peak joint angle, joint range of motion, the peak joint moment and the joint moment impulse of the lower extremity joints and the lumbar joint.These are preliminary results because the data analysis is ongoing. There was a lot of inter-subject variability, however, in general, there was a greater peak lumbar flexion angle for the flywheel squat exercise. There was a trend towards a greater range of motion at the hip for the squat exercise with free weight. There was also a greater hip extension, lumbar extension and ankle plantar flexion impulse moment during the squat exercise with free weight. During the deadlift exercise, the peak knee flexion angle and peak knee extension moment were greater when using the free weight profile. For deadlift, the hip extension, lumbar extension and ankle plantar flexion impulse moment tended to be greater with the free weight profile. Overall, the kinematic and kinetic outcomes for the flywheel profile were either statistically the same as free weight profile in many cases, significantly reduced in a few cases, and rarely higher.

Bioengineering↗
NASA NTRS2016

Squat Biomechanical Modeling Results from Exercising on the Hybrid Ultimate Lifting Kit

Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. The computational models currently under development utilize the OpenSim software, an open source code for musculoskeletal modeling, with biomechanical input data from test subjects for estimation of muscle and joint loads. The subjects are instrumented with reflective markers for motion capture data collection while exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device. Ground reaction force data is collected with force plates under the feet and device loading is recorded through load cells internal to the HULK. Test variables include applied device load, narrow or wide foot stance, slow or fast cadence and the harness or long bar interface between the test subject and the device. Data is also obtained using free weights for a comparison to the resistively loaded exercise device. This data is input into the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. The focus of this presentation is to summarize the results from the full squat exercises across the different test variables.

Bioengineering↗
NASA NTRS2016

OpenSim Model Improvements to Support High Joint Angle Resistive Exercising

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited. Therefore, compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Rigorous testing of these proposed devices in space flight is difficult so computational modeling provides an estimation of the muscle forces and joint loads during exercise to gain insight on the efficacy to protect the musculoskeletal health of astronauts. The NASA Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) project and the National Space Biomedical Research Institute (NSBRI) funded researchers by developing computational models of exercising with these new advanced exercise device concepts

Bioengineering↗