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NASA NTRS2014

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗

NASA NTRS2008

Web Based Tool for Mission Operations Scenarios

A conventional practice for spaceflight projects is to document scenarios in a monolithic Operations Concept document. Such documents can be hundreds of pages long and may require laborious updates. Software development practice utilizes scenarios in the form of smaller, individual use cases, which are often structured and managed using UML. We have developed a process and a web-based scenario tool that utilizes a similar philosophy of smaller, more compact scenarios (but avoids the formality of UML). The need for a scenario process and tool became apparent during the authors' work on a large astrophysics mission. It was noted that every phase of the Mission (e.g., formulation, design, verification and validation, and operations) looked back to scenarios to assess completeness of requirements and design. It was also noted that terminology needed to be clarified and structured to assure communication across all levels of the project. Attempts to manage, communicate, and evolve scenarios at all levels of a project using conventional tools (e.g., Excel) and methods (Scenario Working Group meetings) were not effective given limitations on budget and staffing. The objective of this paper is to document the scenario process and tool created to offer projects a low-cost capability to create, communicate, manage, and evolve scenarios throughout project development. The process and tool have the further benefit of allowing the association of requirements with particular scenarios, establishing and viewing relationships between higher- and lower-level scenarios, and the ability to place all scenarios in a shared context. The resulting structured set of scenarios is widely visible (using a web browser), easily updated, and can be searched according to various criteria including the level (e.g., Project, System, and Team) and Mission Phase. Scenarios are maintained in a web-accessible environment that provides a structured set of scenario fields and allows for maximum visibility across the project. One key aspect is that the tool was built for a scenario process that accounts for stakeholder input, review, comment, and concurrence. By creating well-designed opportunities for stakeholder input and concurrence and by making the scenario content easily accessible to all project personnel, we maximize the opportunities for stakeholders to both understand and agree on the concepts for how their mission is to be carried out.

Boyles, Carole A.↗

NASA NTRS2018

EVA Swab Tool to Support Planetary Protection and Astrobiology Evaluations

When we send humans to search for life on other planets, we'll need to know what we brought with us versus what may already be there. To ensure our crewed systems meet planetary protection requirements-and to protect our science from human contamination-we'll need to assess whether microorganisms may be leaking or venting from our spacecraft. Microbial sample collection outside of a pressurized spacecraft is complicated by temperature extremes, low pressures that preclude the use of laboratory standard (wetted) swabs, and operation either in bulky spacesuits or with robotic assistance. Engineers at the National Aeronautics and Space Administration (NASA) recently developed a swab kit for use in collecting microbial samples from the external surfaces of crewed spacecraft, including spacesuits. The Extravehicular Activity (EVA) Swab Kit consists of a single swab tool handle and an eight-canister sample caddy. The design team minimized development cost by re-purposing a heritage Space Shuttle tile repair handle that was designed to quickly snap into different tool attachments by engaging a mating device in each attachment. This allowed the tool handle to snap onto a fresh swab attachment much like popular shaving razor handles can snap onto a disposable blade cartridge. To disengage the handle from a swab, the user performs two independent functions, which can be done with a single hand. This dual operation mitigates the risk that a swab will be inadvertently released and lost in microgravity. Each swab attachment is fitted with commercially available foam swab tips, vendor-certified to be sterile for Deoxyribonucleic Acid (DNA). A microbial filter installed in the bottom of each sample container allows the container to outgas and repressurize without introducing microbial contaminants to internal void spaces. Extensive ground testing, post-test handling, and sample analysis confirmed the design is able to maintain sterile conditions as the canister moves between various pressure environments. To further minimize cost, the design team acquired extensive ground test experience in a relevant flight environment by piggy-backing onto suited crew training runs. These training runs allowed the project to validate tool interfaces with pressurized EVA gloves and collect user feedback on the tool design and function, as well as characterize baseline microbial data for different types of spacesuits. In general, test subjects found the EVA Swab Kit relatively straightforward to operate, but identified a number of design improvements that will be incorporated into the final design. Although originally intended to help characterize human forward contaminants, this tool has other potential applications, such as for collecting and preserving space-exposed materials to support astrobiology experiments.

Rucker, Michelle A.↗

NASA NTRS2018

EVA Swab Tool to Support Planetary Protection and Astrobiology Evaluations

When we send humans to search for life on other planets, we'll need to know what we brought with us versus what may already be there. To ensure our crewed systems meet planetary protection requirements-and to protect our science from human contamination-we'll need to assess whether microorganisms may be leaking or venting from our spacecraft. Microbial sample collection outside of a pressurized spacecraft is complicated by temperature extremes, low pressures that preclude the use of laboratory standard (wetted) swabs, and operation either in bulky spacesuits or with robotic assistance. A team at the National Aeronautics and Space Administration (NASA) recently developed a swab kit for use in collecting microbial samples from the external surfaces of crewed spacecraft, including spacesuits. The Extravehicular Activity (EVA) Swab Kit consists of a single swab tool handle and an eight-canister sample caddy. The design team minimized development cost by re-purposing a heritage Space Shuttle tile repair handle that was designed to quickly snap into different tool attachments by engaging a mating device in each end effector. This allowed the tool handle to snap onto a fresh swab end effector much like popular shaving razor handles can snap onto a disposable blade cartridge. To disengage the handle from a swab, the user performs two independent functions, which can be done with a single hand. This dual operation mitigates the risk that a swab will be inadvertently released and lost in microgravity. Each swab end effector is fitted with commercially available foam swab tips, vendor-certified to be sterile for Deoxyribonucleic Acid (DNA). A microbial filter installed in the bottom of each sample container allows the container to outgas and re-pressurize without introducing microbial contaminants to internal void spaces. Extensive ground testing, post-test handling, and sample analysis confirmed the design is able to maintain sterile conditions as the canister moves between various pressure environments. To further minimize cost, the design team acquired extensive ground test experience in a relevant flight environment by piggy-backing onto suited crew training runs. These training runs allowed the project to validate tool interfaces with pressurized EVA gloves and collect user feedback on the tool design and function, as well as characterize baseline microbial data for different types of spacesuits. In general, test subjects found the EVA Swab Kit relatively straightforward to operate, but identified a number of design improvements that will be incorporated into the final design. Although originally intended to help characterize human forward contaminants, this tool has other potential applications, such as for collecting and preserving space-exposed materials to support astrobiology experiments.

Rucker, Michelle A.↗

NASA NTRS2017

Designing and Developing Web-Based Administrative Tools for Program Management

The task assigned for this internship was to develop a new tool for tracking projects, their subsystems, the leads, backups, and other employees assigned to them, as well as all the relevant information related to the employee (WBS (time charge) codes, time distribution, certifications, and assignments). Currently, this data is tracked manually using a number of different spreadsheets and other tools simultaneously by a number of different people; some of these documents are then merged into one large document. This often leads to inconsistencies and loss in data due to human error. By simplifying the process of tracking this data and aggregating it into a single tool, it is possible to significantly decrease the potential for human error and time spent collecting and checking this information. II. Objective The main objective of this internship is to develop a web-based tool using Ruby on Rails to serve as a method of easily tracking projects, subsystems, and points of contact, along with employees, their assignments, time distribution, certifications, and contact information. Additionally, this tool must be capable of generating a number of different reports based on the data collected. It was important that this tool deliver all of this information using a readable and intuitive interface.

Material↗

NASA NTRS2018

EVA Swab Tool to Support Planetary Protection and Astrobiology Evaluations

When we send humans to search for life on other planets, we'll need to know what we brought with us versus what may already be there. To ensure our crewed systems meet planetary protection requirements?and to protect our science from human contamination?we'll need to assess whether microorganisms may be leaking or venting from our spacecraft. Microbial sample collection outside of a pressurized spacecraft is complicated by temperature extremes, low pressures that preclude the use of laboratory standard (wetted) swabs, and operation either in bulky spacesuits or with robotic assistance. A team at the National Aeronautics and Space Administration (NASA) recently developed a swab kit for use in collecting microbial samples from the external surfaces of crewed spacecraft, including spacesuits. The Extravehicular Activity (EVA) Swab Kit consists of a single swab tool handle and an eight-canister sample caddy. The design team minimized development cost by re-purposing a heritage Space Shuttle tile repair handle that was designed to quickly snap into different tool attachments by engaging a mating device in each end effector. This allowed the tool handle to snap onto a fresh swab end effector much like popular shaving razor handles can snap onto a disposable blade cartridge. To disengage the handle from a swab, the user performs two independent functions, which can be done with a single hand. This dual operation mitigates the risk that a swab will be inadvertently released and lost in microgravity. Each swab end effector is fitted with commercially available foam swab tips, vendor-certified to be sterile for Deoxyribonucleic Acid (DNA). A microbial filter installed in the bottom of each sample container allows the container to outgas and re-pressurize without introducing microbial contaminants to internal void spaces. Extensive ground testing, post-test handling, and sample analysis confirmed the design is able to maintain sterile conditions as the canister moves between various pressure environments. To further minimize cost, the design team acquired extensive ground test experience in a relevant flight environment by piggy-backing onto suited crew training runs. These training runs allowed the project to validate tool interfaces with pressurized EVA gloves and collect user feedback on the tool design and function, as well as characterize baseline microbial data for different types of spacesuits. In general, test subjects found the EVA Swab Kit relatively straightforward to operate, but identified a number of design improvements that will be incorporated into the final design. Although originally intended to help characterize human forward contaminants, this tool has other potential applications, such as for collecting and preserving space-exposed materials to support astrobiology experiments.

planetary protection↗

NASA NTRS2020

SISO Space Reference FOM - Tools and Testing

The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE.

Möller, Björn↗

NASA NTRS2020

Enabling Space Exploration Medical System Development Using a Tool Ecosystem

The NASA Human Research Program’s (HRP) Exploration Medical Capability (ExMC) Element is utilizing a Model Based Systems Engineering (MBSE) approach to enhance the development of systems engineering products that will be used to advance medical system designs for exploration missions beyond Low Earth Orbit. In support of future missions, the team is capturing content such as system behaviors, functional decompositions, architecture, system requirements and interfaces, and recommendations for clinical capabilities and resources in Systems Modeling Language (SysML) models. As these products mature, SysML models provide a way for ExMC to capture relationships among the various products, which includes supporting more integrated and multi-faceted views of future medical systems. In addition to using SysML models, HRP and ExMC are developing supplementary tools to support two key functions: 1) prioritizing current and future research activities for exploration missions in an objective manner; and 2) enabling risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This paper will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include dynamic Probabilistic Risk Assessment (PRA) capabilities, additional SysML models, a database of system component options, and data visualizations. It also includes a review of an initial Pilot Project focused on enabling medical system trade studies utilizing data that is coordinated across tools for consistent outputs (e.g., mission risk metrics that are associated with medical system mass values and medical conditions addressed). This first Pilot Project demonstrated successful operating procedures and integration across tools. Finally, the paper will also cover a second Pilot Project that utilizes tool enhancements such as medical system optimization capabilities, post-processing, and visualization of generated data for subject matter expert review, and increased integration amongst the tools themselves.

Amador, Jennifer R.↗

NASA NTRS2020

Enabling Space Exploration Medical System Development Using a Tool Ecosystem

The NASA Human Research Program's (HRP) Exploration Medical Capability (ExMC) Element is utilizing a Model Based Systems Engineering (MBSE) approach to enhance the development of systems engineering products that will be used to advance medical system designs for exploration missions beyond Low Earth Orbit. In support of future missions, the team is capturing content such as system behaviors, functional decompositions, architecture, system requirements and interfaces, and recommendations for clinical capabilities and resources in Systems Modeling Language (SysML) models. As these products mature, SysML models provide a way for ExMC to capture relationships among the various products, which includes supporting more integrated and multi-faceted views of future medical systems. In addition to using SysML models, HRP and ExMC are developing supplementary tools to support two key functions: 1) prioritizing current and future research activities for exploration missions in an objective manner; and 2) enabling risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This paper will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include dynamic Probabilistic Risk Assessment (PRA) capabilities, additional SysML models, a database of system component options, and data visualizations. It also includes a review of an initial Pilot Project focused on enabling medical system trade studies utilizing data that is coordinated across tools for consistent outputs (e.g., mission risk metrics that are associated with medical system mass values and medical conditions addressed). This first Pilot Project demonstrated successful operating procedures and integration across tools. Finally, the paper will also cover a second Pilot Project that utilizes tool enhancements such as medical system optimization capabilities, post-processing, and visualization of generated data for subject matter expert review, and increased integration amongst the tools themselves.

Amador, Jennifer R.↗

NASA NTRS2019

Development of a Design for Manufacturing Tool for Automated Fiber Placement Structures

Existing design processes for laminates constructed with automated fiber placement lack significant integration between the various software tools that compose the process. Tools for finite element analysis, computer aided drafting, stress analysis, tool path simulation, and manufacturing defect prediction are all critical parts of the design process. With traditional hand-layup laminates, the analysis performed with each of these tools could be fairly well decoupled from one another. However, for laminates generated by automated fiber placement, the disciplines can become significantly coupled, especially on structures with curvature. This gives rise to a need for integrated “design for manufacturing” software tools that are able to balance the competing objectives from each discipline. This paper describes the preliminary development of such a tool.

Noevere, August T.↗

NASA NTRS2021

Topic Modeling Tool for PeTaL (Periodic Table of Life)

A topic modeling tool is constructed for the purpose of providing insights from biology to the engineer within the framework of PeTaL (Periodic Table of Life). The machine learning text mining tools–latent Dirichlet allocation (LDA) and nonnegative matrix factorization (NMF) with Kullback-Leibler (KL) divergence—are used to provide topic clusters to the user. Topic clusters are the underlying themes of a paper. For the text modeling problem, NMF-KL is the equivalent of probabilistic latent semantic analysis. Both LDA and NMF-KL are top-performing modeling tools. These tools are used to identify biological specimens relevant to the user. Various organisms solve a particular survival problem in nature differently. The topic clusters allow people without domain expertise to find these cross-topic themes in the body of documents and then branch out and examine papers whose target organisms solve the engineer’s problem. Abstracts from the Journal of Experimental Biology were used as input for the clustering tool in addition to a curated set of articles for validation. The tool is able to accept alternate input sources.

Machine learning↗

NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗

NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

Small Spacecraft↗

NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗

NASA NTRS2023

Flight Mechanics Analysis Tools Interoperability and Component Sharing

As multiple flight mechanics (FM) analysis tools are developed to meet the unique scientific and operational requirements of NASA missions, sharing data, transferring models and trajectory information between tools can be complicated. The NESC recently explored ways that increase interoperability of three mission analysis tools: Copernicus, General Mission Analysis Tool (GMAT), and Mission-Analysis Operations Navigation Toolkit Environment (MONTE). These tools are used to generate a variety of products throughout all phases of a mission including: maneuver planning, trajectory optimization and design, orbit determination, performance and error analysis, trade studies and sizing. Establishing a framework to share models, component data and trajectory information is an efficient way to leverage the benefits of an analysis tool without expending development costs to duplicate functionality.

Flight Mechanics Simulation↗

NASA NTRSDate not supplied

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

NASA NTRSDate not supplied

Machine Learning Tools for Runway Configuration Decision Support

Runway Configuration Management↗

NASA NTRSDate not supplied

Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗