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At least 1,171 records · Page 65

Microbial Optical Data Processing: A Key Step in the Metabolic Assessment of Lunar Explorer Instrument for Space Biology Applications (LEIA) and Biosentinel’s Payload Data

The BioSensor payload platform on BioSentinel and LEIA autonomously collects optical data from microbial model organisms in liquid culture. The BioSensor is designed to monitor metabolic activity using absorbance measurements of cell density and alamarBlue, a readily available colorimetric redox indicator dye. BioSentinel, a pioneering NASA CubeSat, uses yeast to study deep space radiation. LEIA investigates radiation and lunar gravity response. The experimental setup includes 16 wells equipped with three LEDs (570, 630, and 850 nm) and their corresponding photodetectors. One well is a calibration control without biology while the rest have desiccated cultures. Autonomous rehydration initiates the experiment. Data from the BioSensor are received from the flight and ground units, enabling comparison to uncover location-based metabolic rate variations. This study presents a Python Jupyter notebook developed for efficient data processing of multiple CSV files containing date and time columns, temperature, and well illumination data. It offers a user-friendly interface while maintaining computational power, automatically recognizing and iteratively processing data files in a user-input path. A Hampel filter with a short window eliminates outlier artifacts from sensor dropout. Because absorbance is a relative measurement, conversion from raw illumination requires defining a “blank” value, so the first data points are averaged to provide the necessary denominator. A cube-root function correction mitigates undesired drift caused by air pockets during the fluidic card filling phase, maintaining optical path length consistency. Beer-Lambert's law is applied to further convert absorbance values to cell and dye form concentrations, the desired science parameters. The processed data are saved and visualized as SVG plots. Future plans include extracting specific science parameters from the processed data like growth rate and metabolic rate, and identification of features corresponding to metabolic and phenotypic shifts such as starvation, shifts from aerobic to anaerobic growth, and osmotic stresses.

Space biology↗

Waste Container Filtration To Minimize Microbial Escape During Long-Term Storage On Mars

In the search for life on Mars, keeping its surface pristine and free of microbes due to human presence is of utmost importance. Astronauts will use emptied logistics containers during their Martian stay to store waste. These containers will be left on the planet’s surface and are a potential source of microbial contamination. It is desired for these containers to be free from leaks for a minimum of 50 years. If leaks do occur a likely location will be at the port. At this location the mating surfaces will be sealed using a flexible gasket material like a thin metal or a polymer. Eventually these seals will fail. To mitigate these effects, a particulate filter can be employed to equilibrate the pressure between the Martin environment and inside the container. To meet planetary protection requirements, the filter can only allow particulates smaller than 0.2 um diameter to pass. This paper discusses why a particulate filter may be needed and how such a filter would be tested to survive and operate in the harsh Martian environment.

Planetary Protection Waste Containment↗

Graphical User Interface (GUI) Implementation for Agent-Based Microbial Radiobiology Model

Sending human life past the Low Earth Orbit (LEO) to explore the Moon and Mars will be challenging. The Earth’s magnetic field naturally protects life from deep-space particle radiation such as Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE); these will pose health risks to humans in deep space. Research has been done to investigate these effects, like BioSentinel, the first biological CubeSat to fly beyond the LEO, designed to culture yeast in a microfluidic device and record optical measurements of growth and metabolism. However, experiments can only report cell damage as bulk growth curves, while deep-space radiation causes damage that is heterogeneous among individual cells. AMMPER is an open-source, agent-based, computational model coded in Python to simulate the effects of deep-space radiation on individual yeast cells (Saccharomyces cerevisiae) to facilitate interpretation of biological radiation experiments. Version 1.0 of the code ran in a command line interface (CLI), limiting use to those familiar with modularization, object-oriented programming, and computational models. Here we present a graphical user interface (GUI) for AMMPER to increase its accessibility. GUI development included converting input points and UI files, designing an application and logo, and expanding program packages. Additionally, we added optical assistance that corresponded with simulation parameters, which included simulation type, cell type, ROS model, and radiation dosage, as well as customizable display and file exportation features. Following a pilot testing period, its structure was updated further to enhance abilities, adding increased runs, video visualization, data plotting, and an educational/tutorial component. Future work will include creating a bit installer and runtime environment for AMMPER. Ultimately, the creation of the GUI has two main goals: to facilitate the integration of computational models into the work of researchers in microbial radiobiology, and to act as an interactive and visual resource for space biology education.

yeast↗

Project Methods to Enhance Wellbore Cement Integrity with Microbially-Induced Calcite Precipitation (MICP) (Final Scientific/Technical Report)

The goal of this project was to develop improved methods for sealing compromised wellbore cement in leaking oil and gas wells, thereby reducing the risk of unwanted upward fluid migration. Novel methods for improving wellbore integrity, such as microbially induced calcite precipitation (MICP), can reduce leakage potential, improve the safety of fossil fuel extraction, improve the public perception of hydraulic fracturing, and promote environmentally-prudent unconventional oil and gas development. Microbes, with the urease enzyme, can catalyze the chemical reaction of urea hydrolysis to induce the precipitation of calcium carbonate which can be used as a cementitious material to seal leakage pathways. In this project, methods to promote robust bio-composite cementitious materials were designed and tested in the laboratory. Scale-up of those methods were tested in meso-scale reactor systems and in field applications. In this report, in Section One, we describe laboratory efforts to develop injection strategies to promote precipitation in wellbore analogs and determine the strength of the bio-composite cements as compared to fine cement. In Section Two, we describe the efforts to scale up the work and study the use of materials that can be used in field application, for example exploring the use of calcium chloride ice melt or urea fertilizer as source chemicals. In Section Three, the three field trials (methods and results) performed as part of the project are described and summarized. At the end of the report is a comprehensive summary and conclusion section which highlights the key findings of the project. The work performed during this project significantly advanced the technology readiness level (TRL) of the MICP wellbore sealing strategy.

02 PETROLEUM↗

Methods to Enhance Wellbore Cement Integrity with Microbially-Induced Calcite Precipitation (MICP) (Final Scientific/ Technical Report)

The goal of this project was to develop improved methods for sealing compromised wellbore cement in leaking oil and gas wells, thereby reducing the risk of unwanted upward fluid migration. Novel methods for improving wellbore integrity, such as microbially induced calcite precipitation (MICP), can reduce leakage potential, improve the safety of fossil fuel extraction, improve the public perception of hydraulic fracturing, and promote environmentally-prudent unconventional oil and gas development. Microbes, with the urease enzyme, can catalyze the chemical reaction of urea hydrolysis to induce the precipitation of calcium carbonate which can be used as a cementitious material to seal leakage pathways. In this project, methods to promote robust bio-composite cementitious materials were designed and tested in the laboratory. Scale-up of those methods were tested in meso-scale reactor systems and in field applications. In this report, in Section One, we describe laboratory efforts to develop injection strategies to promote precipitation in wellbore analogs and determine the strength of the bio-composite cements as compared to fine cement. In Section Two, we describe the efforts to scale up the work and study the use of materials that can be used in field application, for example exploring the use of calcium chloride ice melt or urea fertilizer as source chemicals. In Section Three, the three field trials (methods and results) performed as part of the project are described and summarized. At the end of the report is a comprehensive summary and conclusion section which highlights the key findings of the project. The work performed during this project significantly advanced the technology readiness level (TRL) of the MICP wellbore sealing strategy.

03 NATURAL GAS↗

Automated microbial detection and quantification

A method for automated microbial detection includes collecting air particles into a solid-state sampler, the air particles including microbes, charging the air particles using a plasma field generated by propulsion electrodes, focusing the charged air particles toward a sample well of a microfluidic testing cartridge, tagging the charged air particles with a fluorescence marker, and detecting a quantity of the microbes using a fluorescence detector.

Gilbert, James H.↗

Microbial syringol utilization

Disclosed herein are compositions of non-naturally occurring enzymes to enable microbial syringol utilization with GcoAB.

Beckham, Gregg Tyler↗

Microbial potentiometric sensor array measurements in unsaturated soils

The overarching goal of this study is to demonstrate a novel technology for monitoring changes in electrical potential of unsaturated soils using biofilm-populated electrodes. The novelty of the study stems from the fact that it demonstrates a method for measuring open-circuit potentials (OCP) in environments without the presence of an electrolyte solution. This study also reveals that using a biofilm-populated electrode as a reference in stable environments could successfully be employed to assess and monitor the electrochemical potential generated by plants and microorganisms. The findings imply that long-term (months to years) and real-time measurements of the open-circuit potential in unsaturated soils are possible. Because MPS arrays can directly measure open-circuit potential from the biofilm, the challenges related to locally induced electrochemical changes caused by microorganisms in the soil to achieve optimum physiological levels are eliminated. The simplicity of the technology, which allows for multiple indicator electrodes to be referenced against an “internal” reference electrode, enables spatial-temporal monitoring of the changes in the soil and the generation of 2D- or 3D-signal patterns. Once a signal pattern, generated by an array of sensors, develops (usually after 30 to 90 days), it does not significantly change unless the soil is exposed to external stimuli. The observed OCP phenomena, however, suggests that the change in OCP signal is independent of changes in soil conductivity resulting from the addition of water. In brief, findings suggest that the proposed technology can enable multidimensional profiling and long-term monitoring of changes occurring in unsaturated soils without direct implications of presence of water. The changes in the 2D or 3-D signal patterns, however, can be correlated to other important parameters that characterize soil health.

54 ENVIRONMENTAL SCIENCES↗

Toward FAIR Representations of Microbial Interactions

Despite an ever-growing number of data sets that catalog and characterize interactions between microbes in different environments and conditions, many of these data are neither easily accessible nor intercompatible. These limitations present a major challenge to microbiome research by hindering the streamlined drawing of inferences across studies.

59 BASIC BIOLOGICAL SCIENCES↗