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Sergio Santa Maria

Publications and source records attributed to Sergio Santa Maria.

16 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Campaign: Telemetry-based Biology for the Artemis Era and Beyond

We call for a major dedicated campaign to develop and fly autonomous biological payloads in lunar orbit and on the lunar surface during the next decade, followed by subsequent expansion to Martian orbit. This ambitious goal will require dedicated effort to develop hardware, biological models and data acquisition and processing techniques. We believe that it would be best achieved as a single comprehensive, NASA-led and funded mission project, analogous to planetary science missions. Furthermore, technological developments should be accompanied by collaborations within and between agencies and a robust program for acquisition and retention of talented scientists and engineers.

Egle Cekanaviciute↗
NASA NTRSDate not supplied

Improving Data Analyses for a Biological Mission to Deep Interplanetary Space

Onboard the Artemis 1 rocket, NASA plans to launch the first deep space bioscience mission past low Earth orbit (LEO) since 1972, BioSentinel, a 6-Unit (6U) biological CubeSat. BioSentinel’s goals are to assess the effect of deep space ionizing radiation (IR) on DNA and cell damage response, using Saccharomyces cerevisiae, or budding yeast, as a model organism. BioSentinel accomplishes this by measuring Optical Density (OD) in addition to metabolic activity using the redox dye alamarBlue, both of which will be read through light emitting diode (LED) lights of differing wavelengths. With the largest and most sophisticated energy-providing solar panels utilized on a biological CubeSat to date, BioSentinel will be equipped with an IR dosimeter to identify what doses of radiation the yeast is exposed to at any point in time, in addition to a transponder to send such data back to NASA Ames’ Multi Mission Operations Center (MMOC). Biology computational programs and data processing scripts are necessary to analyze this complex data once it is received, including automated subroutines to analyze duplication rate, alamarBlue reduction, and time periods when paired against numerous other variables. Overall, we have implemented several VisualBasic biocomputational programs to analyze such data in an organized and efficient manner so that conclusions can be made rapidly. Furthermore, we showcase why efficient analysis of particular parameters is important to better understand the risks that deep space IR poses to astronauts, especially when considering the upcoming Artemis missions.

Bijan Harandi↗
NASA NTRSDate not supplied

Enabling Single Cell Research in Hollow Hydrogel Microparticles

Studying biology at the single cell level enables novel discoveries through ultra-high throughput identification and isolation of rare cells and interesting subpopulations. Encapsulation of single cells in hollow hydrogel microparticles, or PicoShells, enables easy visualization, manipulation, and assaying of single cells. The PicoShell’s porous hydrogel shell allows diffusion of nutrients and wastes into and out of the hollow liquid core, allowing uninhibited cell growth. The porous shell also allows diffusion of assay reagents, enabling solution changes, and multi-step assays. Finally, single cells and their progeny can be tracked through time, for example to measure single cell growth rates. However, PicoShells are fabricated using microfluidic techniques, which require specialized expertise, equipment, and facilities. This limits PicoShell’s widespread utility for single cell biology. For Saccharomyces cerevisiae and other desiccation-tolerant microbes, desiccating PicoShells containing cells of interest offers a solution, enabling those without microfluidic capabilities to obtain dried, shelf-stable PicoShells containing their cells of interest from a specialized microfluidics facility. Researchers could then rehydrate the PicoShells and perform their single cell assays, bypassing the microfluidic steps. Desiccated PicoShells could also be flown in space, where desiccation is already a common practice for microbes (i.e. BioSentinel and BioNutrients), bringing single cell analysis capabilities to space. In this work, we develop a method to desiccate PicoShells containing S. cerevisiae while maintaining characteristics similar to fresh, non-desiccated PicoShells. We show good microparticle morphology and hydrogel pore size as well as high yeast viability in line with previous studies. We also demonstrate sorting of a fast-growing yeast population using size-based filtration, as S. cerevisiae in PicoShells are able to physically stretch the microparticle as they grow, increasing the PicoShell diameter. These efforts contribute to the feasibility of leveraging microparticle PicoShells for single cell space biology research on Earth and in space.

Simon Ng↗
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 NTRSDate not supplied

Tracking Metabolic Changes in Microbial Culture using Redox Measurements

During long-term space missions, microbial cultures accumulate the effects of low-dose radiation, microgravity, and other factors; altered growth and metabolic activity may occur before viability effects. This could affect functionality of bioreactors or other bio-enabled mission systems, as well as shed light on human health. Spaceflight microbiology studies beyond the low Earth orbit exposure afforded by the ISS have been limited. Nanosatellites offer an increasingly popular alternative for deep space missions. However, the communications delay requires biofluidic automation of a pre-defined experimental protocol, and the lack of sample return (reliance on sensors in flight) can significantly limit feasible investigations. Previous biological CubeSats (PharmaSat, O/OREOS, EcAMSat) have used alamarBlue, an off-the-shelf formulation of the redox indicator dye resazurin, to track metabolic activity, as will BioSentinel, the upcoming interplanetary microbiology experiment. A series of ground experiments (see abstracts by Liddell, Santa Maria, and A. Kim) were conducted using a microbial culture system outfitted with an electrochemical sensor array (electrical conductivity, pH, oxidation-reduction potential, and dissolved oxygen) with alamarBlue and the same strain of Saccharomyces cerevisiae as BioSentinel. By improving mapping of measured changes in alamarBlue kinetics to physicochemical changes, and ultimately to biological alterations such as shifted metabolic pathways, this work supplements data analyses from past missions and planning for future missions using alamarBlue to characterize space radiation effects. Initial results indicate that alamarBlue acts like a redox buffer; its presence significantly changes redox kinetics in otherwise identical cultures. The initial color change (blue resazurin reduced to red/pink resorufin) appears as a redox plateau. A second plateau, likely corresponding to the second color transition (resorufin to the colorless hydroresorufin), occurs at a lower redox value. The relationship to carbon source exhaustion, dissolved oxygen depletion, cell death, and measured redox potential is complex and still under study.

Tracking↗
NASA NTRSDate not supplied

AMMPER: Agent-based Model for Microbial Populations Exposed to Radiation

Exposure of microbial populations to galactic cosmic radiation (GCR) in the deep-space radiation environment may lead to intracellular damage that compromises the ability of cells to repair and replicate. While simulation programs of deep-space radiation do exist, they focus primarily on single-cell damage, rather than population-wide effects. In this work, a new application and graphical user interface, Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is presented, which simulates the effects of proton-based GCR on Saccharomyces cerevisiae population growth. AMMPER consists of a 50x50x50 µm simulation space, analogous to an aqueous culture medium with non-limiting nutrient and pH buffering, in a microwell plate or microfluidic culture card. This model utilizes Relativistic Ion Tracks (RITRACKS) to create detailed track structures of the radiation traversals. AMMPER then calculates the radiation dose present at each cell, and subsequently determines the damage (chromosomal aberrations, oxidative stress, etc.) and resulting loss of cell viability from both primary and secondary radiative effects. Through implementing cell replication, repair, damage, and death, the effect of radiation exposure on the population growth can be determined. With AMMPER, long-duration effects of the deep space environment on entire populations can be determined and used to assess the feasibility of sustaining life in space.

Amrita Singh↗
NASA NTRSDate not supplied

Microbial Vessel for Impedance Spectroscopy and Electrochemistry (Mvise): an Extensible, Interoperable Data Acquisition Platform for Liquid Culture Studies in Space Biology Research

The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.

Stephen Lantin↗
NASA NTRSDate not supplied

NASA's Space Health Impacts for the NASA Experience (SHINE) Training Program – Space Radiation Curriculum

In February 2023, the Space Radiation Element of the NASA Human Research Program initiated a virtual, annual space radiation curriculum. The Space Health Impacts for the NASA Experience (SHINE) Space Radiation Didactic Curriculum aims to educate participants not only in the scientific aspects of space radiation but also in the agency’s risk management strategies. SHINE Space Radiation Didactic Curriculum combined weekly seminars by speakers from NASA, other government agencies, academia, and industry, with networking sessions designed to foster collaboration between the competitively selected participants as well as interactions with NASA scientists and HRP funded investigators. The inaugural course ran weekly from February 2023 to August 2023 and was comprised of lectures, less formal coffee hours, and office hours. Each two-hour seminar sessions hosted 1-3 presentations on topics which ranged from the space radiation environment to health effects and countermeasure to granting opportunities. All lectures were recorded and will be published on the THREE (The Health Risks of Extraterrestrial Environments) website for public access (https://three.jsc.nasa.gov/). As a course requirement, participants developed individual or collaborative beam time proposals for real, proposed, or potential experiments at the NASA Space Radiation Laboratory (NSRL) at the Brookhaven National Laboratory. For the 2023 course, 25 participants were selected from a total of 59 applicants. Selected participants were citizens from 8 countries and comprised 5 graduate students, 4 postdocs, 11 scientists and 5 professors/medical doctors. Participants had a wide range of expertise including molecular and cellular biology, microbiology, botany, physiology, engineering, physics, aerospace medicine, planetary science, biostatistics, and modeling. The second annual SHINE training program is scheduled from February to August 2024. In addition, a separate SHINE Space Radiation Practicum session will be held in Fall 2024 at the NSRL. The SHINE Space Radiation Practicum is a unique opportunity that has not been available to the public since the closure of the NASA Space Radiation Summer School in 2017 and will allow a small cohort of participants competitively selected in Fall 2023 to gain hands-on radiation experience.

SHINE↗
NASA NTRSDate not supplied

LEIA: An Investigation of Radiation Risks to Biology at the Lunar South Pole

Radiation and reduced gravity pose biological risks to crewed deep space exploration. At the cellular level, radiation damage can be amplified by reduced gravity. Empirical evidence on cellular responses to beyond low Earth orbit (BLEO) environments is imperative to develop effective countermeasures for crew health and in-space biomanufacturing. The Lunar Explorer Instrument for Space Biology Applications (LEIA) project is developing an instrument suite to be delivered to the south polar region of the Moon by the Commercial Lunar Payload Services (CLPS) program. This presentation will provide an overview of the LEIA hardware, experiments, and mission timeline. The LEIA instruments include the BioSensor, the ARES charged particle detector, and the Mini-FND. The BioSensor is an autonomous light emitting diode (LED)-based spectrophotometer and microfluidic incubator. The BioSensor activates yeast cultures and can measure cell growth, metabolic activity, and carotenoid production. The ARES is a Timepix-based charged particle radiation detector that measures dose, dose rate, and linear energy transfer spectra. The Mini-FND is a fast neutron detector that measures albedo neutron flux and energy spectra. Combined, these instruments will be used for yeast genetics experiments to quantify growth, metabolism, and synthetic biology-enabled production of human nutrients, while taking real time measurements of biologically relevant radiation exposure on the lunar surface. These data will be used to test the importance of selected DNA damage repair and reactive oxygen species defense pathways in mitigating cellular damage from lunar surface radiation.

Yeast↗
NASA NTRSDate not supplied

Use of Tardigrade Proteins for Enhancing Cellular Stress Tolerance on the Moon

With sights set on returning a human presence to the Moon and plans to explore even farther beyond, it is imperative we understand the impact of deep space radiation, partial gravity, and the lunar surface on biology. The need for countermeasures to protect future astronauts from the unique conditions of space is ever-pressing and an assessment of bioproduction capabilities in space is a crucial step for sustaining long-term missions. The Lunar Explorer Instrument for space biology Applications (LEIA) aims to investigate the cell’s response to the lunar environment and test strategies for enhancing cellular tolerance on the Moon, utilizing the budding yeast Saccharomyces cerevisiae as a biosensor. S. cerevisiae serves as an excellent model organism due to its widespread use as an analog for human cells, well-characterized set of genetic tools, and ability to survive desiccation. However, these cells must remain desiccated for up to one year prior to launch and the radiation-sensitive strains designed for LEIA will likely be more vulnerable to desiccation effects. In this work, we introduce tardigrade proteins known for their protective mechanisms into potential LEIA strains to test genetic strategies for improving desiccation and radiation tolerance. Tardigrades are extremotolerant animals well-known for their ability to survive in harsh environments. Notably, they can survive extreme desiccation and radiation due to the upregulation of intrinsically disordered proteins (IDPs). It has been shown that integration of these tardigrade IDPs, such as cytosolic abundant heat-soluble (CAHS) proteins, into yeast can confer increased desiccation tolerance in synergy with trehalose. Our ongoing testing and assessment of bioengineered radiation and desiccation tolerance will help us gain insight into optimizing strain design and selection for protecting LEIA’s biological payload as well as genetic engineering strategies for enhancing bioproduction potential for future missions beyond low Earth orbit.

Genetics↗
NASA NTRSDate not supplied

AMMPER: a user-friendly agent-based model that recapitulates simple metabolic responses of yeast to deep-space radiation

For humans venturing to deep space, radiation exposure poses a major health risk. Fundamental research into the biological effects of space radiation are essential for enabling exploration, and the first experimental organisms we send to deep space will be microbial. Yet there are many ways in which microorganisms are likely to experience the effects of high-energy particle radiation (such as Galactic Cosmic Rays) differently from multicellular animals, partly due to the simple fact that microbes are small and unicellular-- less likely to get hit in the first place, and less likely to communicate damage between cells. Computational modeling can aid in designing experiments and predicting the biological effects of radiation, but thus far particle radiation models have not focused on microbes. Here we present the latest developments in AMMPER, the Agent-based Model for Microbial Populations Exposed to Radiation. Originally written in 2021, AMMPER is a Python-based model that incorporates radiation track data from NASA's RITRACKS software and simulates the growth, damage, and death of yeast cells in 3D. It is now freely available as an open-source package on NASA's GitHub repository. Recent improvements include the ability to simulate the dynamics of alamarBlue, a color-changing redox dye commonly used to track metabolic activity in microbial spaceflight experiments. We demonstrate that a simple blue-pink-clear transition model is able to recapitulate key features observed in empirical data from ground studies. AMMPER also includes a new graphical user interface and introductory tutorial to facilitate ease of use by a wider audience. AMMPER can help us to understand how spatially heterogeneous particle radiation damage at the single-cell level can translate to growth differences at the population level, ultimately allowing us to better interpret experiments using microbes as model organisms and how well their results apply to humans.

yeast↗
NASA NTRSDate not supplied

Yeast Strain Development and Hardware Testing in Preparation of a Lunar BioSensor

With Artemis missions underway, it is clear we are going back to the Moon to stay. Before sending Astronauts for long-duration missions, it is crucial to understand the technological and biomedical countermeasures needed to protect them before they get there. We can use knowledge gained from biological CubeSats to guide the next generation of experiments to support human habitation on the Moon. Lunar Explorer Instrument for space biology Applications (LEIA) is NASA’s latest BioSensor, adapted BioSentinel, the only CubeSat to travel Beyond Low Earth Orbit. BioSentinel launched on Artemis I and is currently >50 million kilometers from Earth (as of July 2024). LEIA aims to identify biological responses to the Lunar environment, which unprotected against would pose a threat to astronauts (cancer, cardiovascular disease, neurological impairment). The suite of instruments within LEIA detects Lunar radiation using two on-board radiation sensors (ARES charged particle detector, Mini-Fast Neutron Detector), then monitors real-time biological responses to the Lunar environment via an autonomous microfluidic system, fit with 3-LED emitter and detector boards and the alamarBlue metabolic indicator dye. LEIA will use a genetic approach in addition to synthetic biology to test counter-measure production in space, with the goal to inform and protect astronauts for future Moon missions. We have conducted preliminary tests in preparation for launch to the anticipated South Pole of the Moon, optimizing the biology (strain down-selection, desiccation tolerance, radiation sensitivity) and improving the hardware (including a blue LED to detect the beta-carotene countermeasure product). Our team will discuss these findings in several parts – an overview of the LEIA mission (Mark Settles), adapting flexible CubeSat platforms for deep-space applications (Sergio Santa Maria, Kira Rienecker), developing new technologies to support LEIA ground studies (Chinmayee Govinda Raj), and yeast strain development and hardware testing in preparation for LEIA (presented here).

synthetic biology↗
NASA NTRSDate not supplied

Yeast strain development to test in-space bioproduction in the Lunar Explorer Instrument for space biology Applications (LEIA) mission

The Lunar Explorer Instrument for space biology Applications (LEIA) is investigating the effects of lunar radiation and gravity on yeast viability, growth, and metabolism. LEIA is part of the CP-22 Commercial Lunar Payload Services (CLPS) surface mission to the south polar region of the Moon. The biological payload will test genetic factors that are likely to influence the tolerance of yeast for deep space and lunar surface radiation. LEIA is also investigating in-space production of β-carotene in bioengineered yeast. This carotenoid is both an antioxidant and pro-vitamin A- an essential human micronutrient. We report progress on engineering carotenoid-expressing strains to test the impacts of strain background and specific genetic variants on growth and production of β-carotene. To test for enhanced sensitivity to the LEIA mission environment, we generated gene knockouts for the RAD51 DNA damage repair locus as well as the SOD1, SOD2, and TSA1 reactive oxygen species (ROS) defense enzymes. We are also generating strains expected to increase tolerance to abiotic stressors and ROS. To be included in the biology payload, each strain needs to satisfy a series of requirements to be compatible with the mission concept of operations. The LEIA mission will conduct experiments using an autonomous light emitting diode optical detection system and microfluidics incubator to quantify growth, metabolism, and carotenoid production. Strains must produce sufficient carotenoids for bioproduction to be detectable with this optical system. Cells will be loaded into microfluidics cards, desiccated, and stored for 8-12 months prior to the initiation of lunar surface operations. The CLPS lander will operate for one lunar day, and strains will need to grow to stationary phase within 96 hours to ensure that telemetry of LEIA data to Earth can be completed. Genetic variants also need to display expected phenotypes within these optical detection, storage, and growth cycle constraints.

Yeast Engineering↗
NASA NTRSDate not supplied

Metabolic Vessel for Impedance Spectroscopy and Electrochemistry (MVISE): The Ground Mapping Unit for the Lunar Explorer Instrument for Space Biology Applications (LEIA)​

The BioSensor payload on the upcoming LEIA platform aboard a CLPS lander will carry yeast to the moon to study response to radiation and lunar gravity. The LEIA BioSensor is designed to monitor metabolic activity using absorbance in conjunction with alamarBlue for measuring colorimetric changes as proxy measurement for redox potential. The science data returned from small spacecraft mission modules like LEIA is limited as it relies solely on optical measurements, necessitating a corresponding ground mapping unit that is equipped with multiple electrochemical sensors for accurate mapping of the optical data and operates fully automatically. This technology development work discusses the extensive design and optimization efforts put into the ground mapping unit, MVISE. MVISE is a custom designed, 3D-printed vessel with an agitation system, with six different electrochemical sensor probes, and ports for sample collection and a pressure release valve. The sensors provide real-time data, with dry absorbance measurements aligning with LEIA flight hardware and wet measurements demonstrating invasive sensor design enabling a comparison between the two setups. The 3D printer resin was tested for mechanical robustness, biocompatibility, and resistance to autoclave sterilization. The inner walls were coated with food-grade epoxy, ensuring a smooth finish to prevent microbial lodging and dye staining. The MVISE has successfully passed a week-long leak test and is now undergoing active biology tests. The MVISE prototype will be prepared for radiation tests, with three identical units being tested for varying radiation levels and culture compositions at the NASA Space Radiation Laboratory in November 2024. The integrated sensor approach proposed in this work will enable the accurate mapping of the BioSentinel/LEIA optical flight data to six sensor parameters on the ground unit for better science data return and will enable the first effort to evaluate classical biochemical sensor measurements by comparing and contrasting their responses.

Chinmayee Govinda Raj↗
NASA NTRSDate not supplied

Microbial Responses to Radiation at the Single-Cell Level

Exploring the biological effects of deep space radiation is crucial for developing protective protocols for humans traveling beyond Earth’s magnetosphere. Saccharomyces cerevisiae, or budding yeast, is an ideal model organism to study the effects of radiation on eukaryotes as it shares several pathways with humans, including DNA repair mechanisms. Here, we used time-lapse imaging of colony growth on agar plates to monitor the effects of radiation exposure on individual yeast cells and their progeny.

Paola J. Maldonado Martinez↗