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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Lighting up yeast: overview of optogenetics in yeast and their applications to yeast biotechnology

Abstract Optogenetics is an empowering technology that uses light-responsive proteins to control biological processes. Because of its genetic tractability, abundance of genetic tools, and robust culturing conditions, Saccharomyces cerevisiae has served for many years as an ideal platform in which to study, develop, and apply a wide range of optogenetic systems. In many instances, yeast has been used as a steppingstone in which to characterize and optimize optogenetic tools to later be deployed in higher eukaryotes. More recently, however, optogenetic tools have been developed and deployed in yeast specifically for biotechnological applications, including in nonconventional yeasts. In this review, we summarize various optogenetic systems responding to different wavelengths of light that have been demonstrated in diverse yeast species. We then describe various applications of these optogenetic tools in yeast, particularly in metabolic engineering and recombinant protein production. Finally, we discuss emerging applications in yeast cybergenetics—the interfacing of yeast and computers for closed-loop controls of yeast bioprocesses—and the potential impact of optogenetics in other future biotechnological applications.

Biotechnology & Applied Microbiology↗
DOE OSTI2026

Data for Rewiring Yeast Metabolism for Producing 2,3-Butanediol and Two Downstream Applications: Techno-Economic Analysis and Life Cycle Assessment of Methyl Ethyl Ketone (MEK) and Agricultural Biostimulant Production

Rising concerns for sustainability and global climate change have driven the development of sustainable production pathways for biofuels and chemicals from lignocellulosic biomass via integrated biological and chemical processes. We constructed an engineered Saccharomyces cerevisiae capable of producing 2,3-butanediol (2,3-BDO) from glucose without accumulating ethanol and glycerol, which hinder downstream processing of 2,3-BDO, through extensive metabolic reprogramming. Specifically, we introduced heterologous 2,3-BDO biosynthetic enzymes and deleted the major isozymes of ethanol and glycerol biosynthetic enzymes. In addition, we introduced an NAD+ regenerating Pyruvate-Malate (PM) cycle and enhanced the NAD+ regenerating capability of the PM cycle to resolve the redox imbalance from the deletion of ethanol and glycerol production pathways. The resulting engineered yeast produced 109.9 g/L of 2,3-BDO with a productivity of 1.0 g/L/h and a yield of 0.36 g/g glucose in a fed-batch fermentation. We also conducted techno-economic analysis (TEA) and life cycle assessment (LCA) of the production of methyl ethyl ketone (MEK) through catalytic dehydration of 2,3-BDO. A TEA based on the experimental results indicated that the minimum product selling price (MPSP) was estimated to be $1.90/kg. Regarding cradle-to-grave LCA, 100-year global warming potential (GWP100) and fossil energy consumption (FEC) were found to be 0.37 kg CO2 eq/kg and 3.1 MJ/kg, respectively. These results demonstrated the feasibility of cost-competitive and sustainable bio-based MEK production via yeast fermentation. In addition, we explored the possibility of using the fermentation broth containing 2,3-BDO as a biostimulant inducing drought tolerance in plants. As a result, the yeast 2,3-BDO fermentation broth can induce drought tolerance in Arabidopsis thaliana without a complicated purification process.

Economics↗
DOE OSTI2026

Data for Metabolic Engineering of Nonmodel Yeast Issatchenkia orientalis SD108 for 5-Aminolevulinic Acid Production

Biological production of 5‐aminolevulinic acid (5‐ALA) has received growing attentionover theyears.However, thereis the tradeoff between 5‐ALA biosynthesis and cell growth because the fermentation broth will become acidic due to the production of 5‐ALA. To address this limitation, we engineered an acid‐tolerant yeast, Issatchenkia orientalis SD108, for 5‐ALA production. We first discovered that the cell growth rate of I. orientalis SD108 was boosted by 5‐ALA and its endogenous ALA synthetase (ALAS) showed higher activity than those homologs from other yeasts. The titer of 5‐ALA was improved from 28mg/L to 120‐, 150‐, and 300mg/L, by optimizing plasmid design, overexpressing a transporter, and increasing gene copy number, respectively. After redirecting the metabolic flux using the pyruvate decarboxylase (PDC) knockout strain (SD108ΔPDC) and culturing with urea, we increased the titer of 5‐ALA to 510mg/L, a 13‐fold enhancement, proving the importance of the newly identified IoALAS with higher activity and the strategic selection of nitrogen sources for knockout strains. This study demonstrates the acid‐tolerant I. orientalis SD108ΔPDC has a high potential for 5‐ALA production at a large scale in the future.

Bioproducts↗
DOE OSTI2026

Data for Resourceful and Economical Designing of Fermentation Medium for Lab and Commercial Strains of Yeast from Alternative Feedstock: Transgenic Oilcane

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively. An equal ratio of hydrolysate and juice was found optimum for growth and fermentation by lab and commercial strains of Saccharomyces cerevisiae engineered for xylose fermentation. The industrial strain grew and fermented efficiently under low aeration conditions having an ethanol titer, yield, specific and volumetric productivities of 46.96 ± 0.19 g/l, 0.51 ± 0.00 g/g, 0.27 ± 0.02 g/g.h and 1.95 ± 0.01 g/l.h, respectively, while the lab strain grew better under higher aeration conditions having the ethanol titer, yield, specific and volumetric productivities of 24.93 ± 0.09, 0.27 ± 0.00 g/g, 0.17 ± 0.00 g/g.h and 1.04 ± 0.00 g/l.h, respectively. Acclimation of cultures in a blended medium significantly improved the performance of the yeast strains. The addition of transgenic oilcane juice, which is inedible and rich in amino acids, to the hydrolysate averted the need for expensive nutrient supplementation and detoxification steps of hydrolysate. The approach provides an economical solution to reduce the cost of fermentation at an industrial scale for second-generation drop-in fuel production.

Biomass Analytics↗
DOE OSTI2026

Evaluating isoprenol production using the IPP-bypass pathway in the oleaginous yeast Rhodosporidium toruloides

Background To strengthen the national energy supply, there is an increasing demand for domestically generated aviation fuels. Bio-derived advanced aviation fuels offer the opportunity to meet this domestic need while presenting a unique opportunity to investigate the production of novel aviation fuels. Isoprenol, a chemical precursor to such novel fuels, has been shown to be a biologically producible compound in model organisms, but its bio-producibility needs to be further explored in organisms more compatible with industrial bioproduction. Results In this work, we evaluate isoprenol production using the promising bioproduction yeast, Rhodosporidium toruloides. First, we show successful isoprenol production using the IPP-bypass pathways most successful in laboratory strains of E. coli and S. cerevisiae. Next, we demonstrate that increased flux through the mevalonate pathway only modestly increases isoprenol titers. Using proteomics, we identified a potential bottleneck in production at the final step in the IPP-bypass pathway and explored alternative enzymes for this step. Finally, the top three strains of R. toruloides were evaluated in sorghum hydrolysates generated using cholinium lysinate. Through this work, 93.1 mg/L of isoprenol was produced in mock medium and 27.3 mg/L in sorghum hydrolysates. Conclusion Together these results lay the foundation for future work for the production of isoprenol from bioproduction crops.

Advanced aviation fuel↗
NASA NTRS2016

Genomic and Phenotypic Characterization of Yeast Biosensor for Deep-space Radiation

The BioSentinel mission was selected to launch as a secondary payload onboard NASA Exploration Mission 1 (EM-1) in 2018. In BioSentinel, the budding yeast Saccharomyces cerevisiae will be used as a biosensor to measure the long-term impact of deep-space radiation to living organisms. In the 4U-payload, desiccated yeast cells from different strains will be stored inside microfluidic cards equipped with 3-color LED optical detection system to monitor cell growth and metabolic activity. At different times throughout the 12-month mission, these cards will be filled with liquid yeast growth media to rehydrate and grow the desiccated cells. The growth and metabolic rates of wild-type and radiation-sensitive strains in deep-space radiation environment will be compared to the rates measured in the ground- and microgravity-control units. These rates will also be correlated with measurements obtained from onboard physical dosimeters. In our preliminary long-term desiccation study, we found that air-drying yeast cells in 10% trehalose is the best method of cell preservation in order to survive the entire 18-month mission duration (6-month pre-launch plus 12-month full-mission periods). However, our study also revealed that desiccated yeast cells have decreasing viability over time when stored in payload-like environment. This suggests that the yeast biosensor will have different population of cells at different time points during the long-term mission. In this study, we are characterizing genomic and phenotypic changes in our yeast biosensor due to long-term storage and desiccation. For each yeast strain that will be part of the biosensor, several clones were reisolated after long-term storage by desiccation. These clones were compared to their respective original isolate in terms of genomic composition, desiccation tolerance and radiation sensitivity. Interestingly, clones from a radiation-sensitive mutant have better desiccation tolerance compared to their original isolate without losing radiation sensitivity. We employed Next-Generation Sequencing technology to better understand this phenotypic variation. Current effort is focusing on the analysis of high-throughput sequencing data to look for genomic changes in these reisolated clones compared to their original isolate.

yeast↗
NASA NTRS2017

Building Better Biosensors for Exploration into Deep-Space, Using Humanized Yeast

1.BioSentinel is 1 of 13 secondary payloads hitching a ride beyond Low Earth Orbit on Exploration Mission 1 (EM-1), set to launch from NASAs Space Launch System in 2019. EM-1 is our first opportunity to investigate the effects of the deep space environment on a eukaryotic biological system, the budding yeast S. cerevisiae. Though separated by a billion years of evolution we share hundreds of genes important for basic cell function, including responses to DNA damage. Thus, yeast is an ideal biosensor for detecting typesextent of damage induced by deep-space radiation.We will fly desiccated cells, then rehydrate to wake them up when the automated payload is ready to initiate the experiment. Rehydration solution contains SC (Synthetic Complete) media and alamarBlue, an indicator for changes in growth and metabolism. Telemetry of LED readings will then allow us to detect how cells respond throughout the mission. The desiccation-rehydration process can be extremely damaging to cells, and can severely diminish our ability to accurately measure and model cellular responses to deep-space radiation. The aim of this study is to develop a better biosensor: yeast strains that are more resistant to desiccation stress. We will over-express known cellular protectants, including hydrophilin Sip18, the protein disaggregase Hsp104, and thioredoxin Trx2, a responder to oxidative stress, then measure cell viability after desiccation to determine which factors improve stress tolerance. Over-expression of SIP18 in wine yeast starter cultures was previously reported to increase viability following desiccation stress by up to 70. Thus, we expect similar improvements in our space-yeast strains. By designing better yeast biosensors we can better prepare for and mitigate the potential dangers of deep-space radiation for future missions.This work is funded by NASAs AES program.

biosensor↗
NASA NTRSDate not supplied

Single-Cell Analysis of Yeast (Saccharomyces cerevisiae) Using Hydrogel Encapsulation

Space radiation poses a major health risk to astronauts. To fulfill NASA’s mission of exploration beyond Earth, the biological effects of Galactic Cosmic Radiation and gamma radiation must be investigated to elucidate cellular damage mechanisms and inform countermeasure protocols to safely bring humans beyond Earth’s magnetosphere. Budding yeast (Saccharomyces cerevisiae) are commonly used in experiments as a model organism for studying the effects of radiation on eukaryotes. Radiobiology of yeast at the single cell level is poorly understood, yet crucial for informing models to aid in the design and interpretation of experiments. We are using a novel method of microencapsulation in hydrogel particles (PicoShells) to enable analysis of the distribution of radiation-induced damage among yeast cells at the single-cell level, in high throughput. Here we describe the development of methods for culturing, visualization, and quantification of encapsulated yeast. The encapsulated yeast are cultured in Yeast extract-Peptone-Dextrose (YPD) medium, fixed in formaldehyde or ethanol, and stained with DAPI or propidium iodide, then visualized using microscopy or enumerated using flow cytometry, with the aim of developing a protocol to enumerate the distribution of viable cells in each PicoShell. This will allow us to quantify how different forms of radiation can generate different distributions of damage across a population of cells, ultimately providing insight into the biological effects of space-relevant ionizing radiation.

yeast↗
NASA NTRS1995

The growth of solar radiated yeast

This researcher plans to determine if solar radiation affects the growth of yeast. The irradiated yeast was obtained from a sample exposed in space during a Space Shuttle flight of September 9-20, 1994. Further, the control groups were held at: (1) Goddard Space Flight Center (GSFC) in Greenbelt, Maryland; and (2) South Dakota School of Mines and Technology. The procedure used was based on the fact that yeast is most often used in consumable baked goods. Therefore, the yeast was incorporated into a basic Betty Crocker bread recipe. Data was collected by placing measured amounts of dough into sample containers with fifteen minute growth in height measurements collected and recorded. This researcher assumed the viability of yeast to be relative to its ability to produce carbon dioxide gas and cause the dough to rise. As all ingredients and surroundings were equal, this researcher assumed the yeast will produce the only significant difference in data collected. This researcher noted the approximate use date on all sample packages to be prior to arrival and experiment date. All dates equal, it was then assumed each would act in a similar manner of response. This assumption will allow for equally correct data collection.

Kraft, Tyrone↗
NASA NTRSDate not supplied

Investigating Biological Responses to Deep Space Radiation for Missions Beyond Low Earth Orbit (LEO) using Yeast

To enable long-term spaceflight missions and establish habitation on the Moon and Mars, we require a comprehensive understanding of the effects of chronic deep space radiation exposure on humans. BioSentinel is NASA’s first biological CubeSat to venture beyond Low Earth Orbit (LEO). It utilizes Saccharomyces cerevisiae (budding yeast) as a model organism to study biological responses to deep space radiation. Yeast share significant genetic homology with humans, including basic cellular metabolism and DNA repair mechanisms. In addition, unlike human cell cultures, yeast can survive the duration and constraints of a deep space mission. BioSentinel measures biological responses using an optical system and alamarBlue oxidation-reduction (redox) dye. Two strains of yeast are studied - a wild-type and a rad51 mutant strain that is deficient in DNA repair. Changes in metabolism and growth are monitored throughout the nominal 6-month mission. Preliminary tests indicate a significant change in the alamarBlue response to low-dose ionizing radiation (IR). Additionally, rad51 cells have shown an IR dose-dependent decrease in glucose uptake and accumulation of oxidized NADH (NAD+). These biomolecules are involved in reactions responsible for basic cell processes, including growth and development, signaling, and respiration. The current study expanded upon previous data by exposing yeast to deep space-relevant radiation. Glucose and NADH/NAD+ assays were conducted on yeast subjected to varying dosages of high-energy Fe-56 and simulated galactic cosmic rays (GCRs). The resulting data was analyzed using Excel and GraphPad Prism. A particular focus was to identify biomolecules resulting from aerobic respiration, which requires the presence of oxygen, or anaerobic processes. As long-term spaceflight missions draw near, it is increasingly important to characterize biological processes affected by the conditions of deep space. Studying biomolecular damage caused by deep space radiation may enable the development of engineering controls or biomedical therapeutics that mitigate health complications for future astronauts.

Kyra Keenan↗
NASA NTRSDate not supplied

Engineered Yeast to Test Risks for Human Exploration of the Lunar Surface

Jessica W. Chau, Natalie N. Ball, Aditya Hindupur, Sandra T. Vu, Jennifer Gil Acevedo, Lauren C. Liddell, Chinmayee Govinda Raj, Gentry, Sergio R. Santa Maria, A. Mark Settles Crewed exploration of the Moon carries risks of long duration exposure to reduced gravity and to deep space radiation. The Lunar Explorer Instrument for space biology Applications (LEIA) investigates the effects of increased radiation and reduced gravity on yeast viability and growth in a Commercial Lunar Payload Services (CLPS) surface mission to the south polar region. LEIA conducts 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. We have engineered beta-carotene producing yeast strains to test the importance of selected DNA damage repair and reactive oxygen species (ROS) defense pathways in mitigating cellular damage from lunar surface radiation. Carotenoids are important dietary antioxidants, and beta-carotene is pro-vitamin A, which is needed for vision and immune function. Carotenoids are sensitive to ROS produced by ionizing radiation and NASA is testing on-demand production of carotenoids from yeast in the BioNutrients space flight experiments. In LEIA, we test the effects of deep space on carotenoid yield in engineered yeast strains. The LEIA team uses CRISPR-Cas9 to engineer yeast to express carotenoids as well as to generate loss-of-function mutations. We are generating mutations in the RAD51 DNA damage repair locus and three genes that function to reduce oxidative damage to the cell: SOD1, SOD2, and TSA1. These strains are tested for carotenoid production using microfluidics and LED spectroscopy to allow remote sensing of cellular growth and carotenoid levels. Keywords: synthetic biology, oxidative stress tolerance, biosensors, space radiation, beyond low Earth orbit, lunar surface, CRISPR/Cas9, gene editing, desiccation, carotenoids.

synthetic biology↗
DOE OSTI2025

Machine learning reveals genes impacting oxidative stress resistance across yeasts

Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterized the variation in resistance to ROS across the ancient yeast subphylum Saccharomycotina and used machine learning (ML) to identify gene families whose sizes were predictive of ROS resistance.

AI↗
DOE OSTI2024

Exploring Saccharomycotina Yeast Ecology Through an Ecological Ontology Framework

Yeasts in the subphylum Saccharomycotina are found across the globe in disparate ecosystems. A major aim of yeast research is to understand the diversity and evolution of ecological traits, such as carbon metabolic breadth, insect association, and cactophily. This includes studying aspects of ecological traits like genetic architecture or association with other phenotypic traits. Genomic resources in the Saccharomycotina have grown rapidly. Ecological data, however, are still limited for many species, especially those only known from species descriptions where usually only a limited number of strains are studied. Moreover, ecological information is recorded in natural language format limiting high throughput computational analysis. To address these limitations, we developed an ontological framework for the analysis of yeast ecology. A total of 1,088 yeast strains were added to the Ontology of Yeast Environments (OYE) and analyzed in a machine-learning framework to connect genotype to ecology. This framework is flexible and can be extended to additional isolates, species, or environmental sequencing data. Widespread adoption of OYE would greatly aid the study of macroecology in the Saccharomycotina subphylum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites

Mass spectrometry analyses have identified tens of thousands of unknown small molecule-associated peaks in different biological specimens. Notably, even the simplest and best studied organisms like Escherichia coli and Saccharomyces cerevisiae yield thousands of unknown peaks. A key question is how many of these reflect actual novel endogenous metabolites. To explore this, Mahieu and Patti used complete 13 C -labeling in E. coli to credential peaks as biological. This reduced the number of unknowns by more than 90%. Here, we carry out similar uniform 13 C-labeling in the Baker’s yeast S. cerevisiae and two less-studied bioenergy-relevant yeasts Rhodotorula toruloides (lipid producer) and Issatchenkia orientalis (organic acid producer). Identification of unknown metabolite peaks and their molecular formulas is facilitated through software tailored for 13 C labeling data and resulting knowledge of carbon atom count. A classification model evaluates the plausibility of each candidate formula, with peaks lacking plausible candidate formulas unlikely to reflect metabolite molecular ions. This approach prioritizes about one hundred candidate abundant unknown metabolites with logical molecular formulas. Most of these are species-specific rather than conserved across yeasts, and more are found in the nonmodel yeasts than S. cerevisiae. Thus, 13 C-labeling data on unknown metabolites highlights the potential for discovering new metabolites and pathways in nonmodel yeasts.

Carbon↗
DOE OSTI2026

The oleaginous yeast Cutaneotrichosporon oleaginosum modifies corn stover alkali lignin

The current paradigm in synthetic biology for lignin bioconversion platforms includes primarily bacteria and filamentous fungi. Yeast are notoriously understudied for their role in lignin degradation and utilization, despite their ubiquity in saprophytic microbial communities. A few publications report lignin-modifying yeasts, but investigations to date have relied on model aromatic compounds or lignin-containing substrates replete with other carbon sources. In this work, we use a suite of analytical tools to evaluate interactions between corn stover-extracted lignin and the oleaginous yeast Cutaneotrichosporon oleaginosum. Notably, 2D-NMR analysis showed a significant decrease in the H-lignin component as well as resinol (β-β) and phenylcoumaran (β-5) linkages. Using super-resolution fluorescence microscopy, we demonstrated that this yeast may uptake polymeric lignin and/or undertakes interactions at the cellular envelope. To explore mechanisms of lignin modification, transport, and aromatics catabolism, extensive secretomics and proteomics analyses were conducted. Compared to carbon-limited glucose and “No Carbon” controls, several putative laccases, quinone reductases, superoxide dismutases, and glyoxal/oxalate oxidases were upregulated in the lignin condition. Excitingly, two ferric reductases and an oxalate exchanger were only observed in the lignin condition. These results indicate that C. oleaginosum may perform extracellular quinone redox cycling to generate lignin-modifying reactive oxygen species. These findings enhance our understanding of yeast-lignin interactions and provide valuable insights for validation studies and metabolic engineering.

09 BIOMASS FUELS↗
DOE OSTI2025

Switchgrass Steroidal Saponins Reduce Fungal Disease but Decrease Yeast Fermentation Yield

Increasing the production of bioproducts from lignocellulosic feedstocks requires improvement in both field production and biorefinery efficiency. When plant traits arise that improve field production but decrease biofuel yield, these trade-offs can represent challenges in the entire production process. To examine trade-offs between field and production traits, we examined factors underlying switchgrass resistance to fungal rust pathogens in field conditions and factors that impede yeast fermentation in the lab using repeated measurements on a switchgrass genetic diversity panel. We found that the same switchgrass genotypes that showed high fungal pathogen resistance also showed recalcitrance to yeast fermentation. These switchgrass genotypes were mostly from the Atlantic genetic group, which had high levels of specialized metabolites of the saponin class. Among 1589 metabolites identified through metabolomics, we found that saponins were among the most likely to explain variation in both rust infection and fermentation yield using random forest feature selection, and that only four of these were sufficient to explain 57.9% of the variation in rust susceptibility. Through follow-up testing in recalcitrant biomass, we found that the bacterium Zymomonas mobilis does not suffer the same inhibition as the yeast Saccharomyces cerevisiae, and that the addition of ergosterol (thought to be the fungal cellular target of saponin inhibition) rescues yeast fermentation. Several lines of evidence point to a central role for saponins as key metabolites protecting switchgrass from fungal pathogens and interfering with yeast fermentation, underscoring an ongoing need for collaboration between plant breeders and biofuel production scientists.

VanWallendael, Acer [North Carolina State Universi↗
DOE OSTI2025

Unique trajectory of gene family evolution from genomic analysis of nearly all known species in an ancient yeast lineage

Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family evolution differs from that of plants, animals, and filamentous ascomycetes, and is characterized by smaller overall gene numbers yet larger gene family sizes for a given gene number. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses—commensurate with a narrowing of metabolic niche breadth—but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.

Comparative Genomics↗
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↗