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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

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↗
NASA NTRS1972

Microbial burden prediction model for unmanned planetary spacecraft

The technical development of a computer program for predicting microbial burden on unmanned planetary spacecraft is outlined. The discussion includes the derivation of the basic analytical equations, the selection of a method for handling several random variables, the macrologic of the computer programs and the validation and verification of the model. The prediction model was developed to (1) supplement the biological assays of a spacecraft by simulating the microbial accretion during periods when assays are not taken; (2) minimize the necessity for a large number of microbiological assays; and (3) predict the microbial loading on a lander immediately prior to sterilization and other non-lander equipment prior to launch. It is shown that these purposes not only were achieved but also that the prediction results compare favorably to the estimates derived from the direct assays. The computer program can be applied not only as a prediction instrument but also as a management and control tool. The basic logic of the model is shown to have possible applicability to other sequential flow processes, such as food processing.

Hoffman, A. R.↗
NASA NTRSDate not supplied

Microbial Mutualism in (Modeled) Microgravity: Measuring the Effects of A Spaceflight-Like Fluid Environment on Cross-Feeding Communities

Microorganisms grow differently in spaceflight than they do on Earth. While numerous factors likely contribute, one ubiquitous feature of the space environment is altered gravity - but because microbes are generally considered too small to detect gravity directly, they likely experience the effects of gravity via changes in their fluid environment, primarily a reduction in convective mixing. This theory is supported by evidence that individual microbial strains experience starvation and acid stress in microgravity. If it is true, then microgravity would also have measurable effects on microbes in mixed communities, because many interspecies interactions involve the exchange of soluble metabolites through their medium (cross-feeding). Specifically, cooperative cross-feeding communities would grow more slowly in microgravity, and this effect should be reproducible in ground-based rotational culture systems (rotating wall vessels, RWVs) designed to simulate the quiescent environment of microgravity. Here we present preliminary results of our efforts to test this hypothesis using using a model system of Eschericia coli and Salmonella enterica that grow only when they can exchange methionine and acetate through the medium. We report on the development of a novel laboratory system that allows us measure growth rates and species ratios in real-time using fluorescence spectrometry as the organisms grow in RWVs. We are able to track growth rates of individual species and the co-culture continuously with high temporal resolution for several hours, a substantial improvement over prior RWV systems that require destructive sampling. We vary the fidelity of the microgravity simulation by varying the rotation rate, and find that rotation rate affects growth rates of the community more than that of individual strains, consistent with the claim that RWVs can simulate a microgravity-like quiescent environment. While more work needs to be done to probe the mechanisms of this effect, we hope that our system will ultimately allow us to generate quantitative predictions about the effects of spaceflight on organisms that are tiny but essential to sustaining long-term human space exploration.

microgravity↗
NASA NTRS2005

A Fundamental Mathematical Model of a Microbial Predenitrification System

Space flight beyond Low Earth Orbit requires sophisticated systems to support all aspects of the mission (life support, real-time communications, etc.). A common concern that cuts across all these systems is the selection of information technology (IT) methodology, software and hardware architectures to provide robust monitoring, diagnosis, and control support. Another dimension of the problem space is that different systems must be integrated seamlessly so that communication speed and data handling appear as a continuum (un-interrupted). One such team investigating this problem is the Advanced Integration Matrix (AIM) team whose role is to define the critical requirements expected of software and hardware to support an integrated approach to the command and control of Advanced Life Support (ALS) for future long-duration human space missions, including permanent human presence on the Moon and Mars. A goal of the AIM team is to set the foundation for testing criteria that will assist in specifying tasks, control schemes and test scenarios to validate and verify systems capabilities. This project is to contribute to the goals of the AIM team by assisting with controls planning for ALS. Control for ALS is an enormous problem it involves air revitalization, water recovery, food production, solids processing and crew. In more general terms, these systems can be characterized as involving both continuous and discrete processes, dynamic interactions among the sub-systems, nonlinear behavior due to the complex operations, and a large number of multivariable interactions due to the dimension of the state space. It is imperative that a baseline approach from which to measure performance is established especially when the expectation for the control system is complete autonomous control.

Hoo, Karlene A.↗
NASA NTRS2000

Controlling Microbial Byproducts using Model-Based Substrate Monitoring and Control Strategies

We have developed a computer-controlled bioreactor system to study various aspects of microbially-mediated nitrogen cycling. The system has been used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to N2O and N2) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model-based feed forward control entails prediction of future systems in states and automated regulation of system parameters to achieve desired and avoid undesirable system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of several individual denitrifying species to varying environmental conditions. The system and models are now being applied to mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of a modified Monod organism interaction model was evaluated as a means of achieving more accurate description of the dynamic behavior of the communities. A minimum variance parameter estimation routine was also' used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The feed forward control strategy being developed will increase system autonomy, reduce crew intervention and limit the accumulation of undesirable waste products (NOx).

Smernoff, David T.↗
NASA NTRS2017

Developing Model Benchtop Systems for Microbial Experimental Evolution

Understanding how microbes impact an ecosystem has improved through advances of molecular and genetic tools, but creating complex systems that emulate natural biology goes beyond current technology. In fact, many chemical, biological, and metabolic pathways of even model organisms are still poorly characterized. Even then, standard laboratory techniques for testing microbial impact on environmental change can have many drawbacks; they are time-consuming, labor intensive, and are at risk of contamination. By having an automated process, many of these problems can be reduced or even eliminated. We are developing a benchtop system that can run for long periods of time without the need for human intervention, involve multiple environmental stressors at once, perform real-time adjustments of stressor exposure based on current state of the population, and minimize contamination risks. Our prototype device allows operators to generate an analogue of real world micro-scale ecosystems that can be used to model the effects of disruptive environmental change on microbial ecosystems. It comprises of electronics, mechatronics, and fluidics based systems to control, measure, and evaluate the before and after state of microbial cultures from exposure to environmental stressors. Currently, it uses four parallel growth chambers to perform tests on liquid cultures. To measure the population state, optical sensors (LED/photodiode) are used. Its primary selection pressure is UV-C radiation, a well-studied stressor known for its cell- and DNA-damaging effects and as a mutagen. Future work will involve improving the current growth chambers, as well as implementing additional sensors and environmental stressors into the system. Full integration of multiple culture testing will allow inter-culture comparisons. Besides the temperature and OD sensors, other types of sensors can be integrated such as conductivity, biomass, pH, and dissolved gasses such as CO and O. Additional environmental stressor systems like temperature (extreme heat or cold), metal toxicity, and other forms of radiation will increase the scale and testing range.

Developing↗
NASA NTRS1995

A 'crytic' microbial mat: A new model ecosystem for extant life on Mars

If life were present on Mars today, it would face potentially lethal environmental conditions such as a lack of water, frigid temperatures, ultraviolet radiation, and soil oxidants. In addition, the Viking missions did not detect near-surface organic carbon available for assimilation. Autotrophic organisms that lived under a protective layer of sand or gravel would be able to circumvent the ultraviolet radiation and lack of fixed carbon. Two terrestrial photosynthetic near-surface microbial communities have been identified, one in the inter- and supertidal of Laguna Ojo de Liebere (Baja California Sur, Mexico) and one in the acidic gravel near several small geysers in Yellowstone National Park (Wyoming, U.S.A.). Both communities have been studied with respect to their ability to fix carbon under different conditions, including elevated levels of inorganic carbon. Although these sand communities have not been exposed to the entire suite of Martian environmental conditions simultaneously, such communities can provide a useful model ecosystem for a potential extant Martian biota.

Rothschild, L. J.↗
NASA NTRS1988

The cryptoendolithic microbial environment in the Ross Desert of Antarctica: mathematical models of the thermal regime

Microbial activity in the Antarctic cryptoendolithic habitat is regulated primarily by temperature. Previous field studies have provided some information on the thermal regime in this habitat, but this type of information is limited by the remoteness of the site and the harsh climatic conditions. Therefore, a mathematical model of the endolithic thermal regime was constructed to augment the field data. This model enabled the parameters affecting the horizontal and altitudinal distribution of the community to be examined. The model predicts that colonization should be possible on surfaces with zenith angle less than 15 degrees. At greater zenith angles, colonization should be restricted to surfaces with azimuth angles less than 135 degrees or greater than 225 degrees. The upper elevational limit of the community should be less than 2,500 m. The thermal regime probably does not influence the zonation of the community within a rock.

Non-NASA Center↗
NASA NTRS2009

Microbial Risk Assessment

Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.

Ott, C. M.↗
NASA NTRS2004

Microbial Characterization and Comparison of Isolates During the Mir and ISS Missions

Spacecraft represent a semi-closed ecosystem that provides a unique model of microbial interaction with other microbes, potential hosts, and their environment. Environmental samples from the Mir Space Station (1995-1998) and the International Space Station (ISS) (2000-Present) were collected and processed to provide insight into the characterization of microbial diversity aboard spacecraft over time and assess any potential health risks to the crew. All microbiota were isolated using standard media-based methodologies. Isolates from Mir and ISS were processed using various methods of analysis, including VITEK biochemical analysis, 16s ribosomal identification, and fingerprinting using rep-PCR analysis. Over the first 41 months of habitation, the diversity of the microbiota from air and surface samples aboard ISS increased from an initial six to 53 different bacterial species. During the same period, fungal diversity increased from 2 to 24 species. Based upon rep-PCR analysis, the majority of isolates were unique suggesting the need for increased sampling frequency and a more thorough analysis of samples to properly characterize the ISS microbiota. This limited fungal and bacterial data from environmental samples acquired during monitoring currently do not indicate a microbial hazard to ISS or any trends suggesting potential health risks.

Fontenot, Sondra L.↗
NASA NTRS1979

Analysis and interpretation of Viking labeled release experimental results

The Viking Labeled Release (LR) life detection experiment on the surface of Mars produced data consistent with a biological interpretation. In considering the plausibility of this interpretation, terrestrial life forms were identified which could serve as models for Martian microbial life. Prominent among these models are lichens which are known to survive for years in a state of cryptobiosis, to grow in hostile polar environments, to exist on atmospheric nitrogen as sole nitrogen source, and to survive without liquid water by absorbing water directly from the atmosphere. Another model is derived from the endolithic bacteria found in the dry Antarctic valleys; preliminary experiments conducted with samples of these bacteria indicate that they produce positive LR responses approximating the Mars results. However, because of the hositility of the Martian environment to life, and the failure to find organics on the surface of Mars, a number of nonbiological explanations were advanced to account for the Viking LR data. A reaction of the LR nutrient with putative surface hydrogen peroxide is the leading candidate. Other possibilities raised include reactions caused by or with ultraviolet irradiation, gamma-Fe2O3, metalloperoxides or superoxides.

Levin, G. V.↗
NASA NTRSDate not supplied

Growth Curve Parameterization of Metabolic Activity of Yeast Cells for BioSentinel

The goal of the BioSentinel small satellite payload is to measure the effect of deep space radiation on the growth and metabolic activity of yeast cells. Raw test data is generated by fluidics cards containing yeast cells rehydrated at different periods, with metabolic activity measured by the reduction of alamarBlue. Each card well has a sensor array that measures the amount of red, green, and infrared light transmitted through the yeast culture. This illumination data is then converted to absorbance values, which are further converted into concentrations. The ultimate objective is to convert these concentrations into biologically-relevant metrics that can be compared against one another to determine changes due to differential radiation exposure. Beginning with IR absorbance data (corresponding to cell density) from ground studies, three parameters from a sigmoidal growth curve were extracted and analyzed: 𝜆 (lag phase), 𝜇 (max growth rate), and A (max cell growth). The data was fit to the Gompertz model of microbial growth using non-linear regression (Minitab), as the fit error was reduced compared to the simpler logistic growth curve. Graphs showed that the data contained a discrepancy (drift) in the lag phase that is attributable to a slow, constant loss of moisture. Correcting this discrepancy by fitting the first 25 hours of the data to a power function and subtracting these values from the absorbance readings obtained a better statistical fit to the growth curve in the lag phase. A power fit was selected over a linear fit because it reflected the effects of constant volume loss. This correction to the BioSentinel data analysis pipeline will enable quantitative statistical analysis of the effect of different levels of deep space radiation on yeast cells. Future work includes automation of drift correction and curve modeling to extract these parameters directly from data.

Growth Curve↗
NASA NTRS2022

Biological Oxidation of Fe(II)-Bearing Smectite by Microaerophilic Iron Oxidizer Sideroxydans lithotrophicus Using Dual Mto and Cyc2 Iron Oxidation Pathways

Fe(II) clays are common across many environments, making them a potentially significant microbial substrate, yet clays are not well established as an electron donor. Therefore, we explored whether Fe(II)-smectite supports the growth of Sideroxydans lithotrophicus ES-1, a microaerophilic Fe(II)-oxidizing bacterium (FeOB), using synthesized trioctahedral Fe(II)-smectite and 2% oxygen. S. lithotrophicus grew substantially and can oxidize Fe(II)-smectite to a higher extent than abiotic oxidation, based on X-ray near-edge spectroscopy (XANES). Sequential extraction showed that edge-Fe(II) is oxidized before interior-Fe(II) in both biotic and abiotic experiments. The resulting Fe(III) remains in smectite, as secondary minerals were not detected in biotic and abiotic oxidation products by XANES and Mössbauer spectroscopy. To determine the genes involved, we compared S. lithotrophicus grown on smectite versus Fe(II)-citrate using reverse-transcription quantitative PCR and found that cyc2 genes were highly expressed on both substrates, while mtoA was upregulated on smectite. Proteomics confirmed that Mto proteins were only expressed on smectite, indicating that ES-1 uses the Mto pathway to access solid Fe(II). We integrate our results into a biochemical and mineralogical model of microbial smectite oxidation. This work increases the known substrates for FeOB growth and expands the mechanisms of Fe(II)-smectite alteration in the environment.

smectite↗