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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Preliminary Examination of Particles Recovered from the Surface of the Asteroid Itokawa by the Hayabusa Mission

The Hayabusa spacecraft arrived at S-type Asteroid 25143 Itokawa in November 2006, and reveal astounding features of the small asteroid (535 x 294 x 209 m). Near-infrared spectral shape indicates that the surface of this body has an olivinerich mineral assemblage potentially similar to that of LL5 or LL6 chondrites with different degrees of space weathering. Based on the surface morphological features observed in high-resolution images of Itokawa s surface, two major types of boulders were distinguished: rounded and angular boulders. Rounded boulders seem to be breccias, while angular boulders seem to have severe impact origin. Although the sample collection did not be made by normal operations, it was considered that some amount of samples, probably small particles of regolith, was collected from MUSES-C regio on the Itokawa s surface. The sample capsule was successfully recovered on the earth on June 13, 2010, and was opened at curation facility of JAXA (Japan Aerospace Exploration Agency), Sagamihara, Japan. A large number of small particles were found in the sample container. Preliminary analysis with SEM/EDX at the curation facility showed that at least more than 1500 grains were identified as rocky particles, and most of them were judged to be of extraterrestrial origin, and definitely from Asteroid Itokawa. Minerals (olivine, low-Ca pyroxene, high-Ca pyroxene, plagioclase, Fe sulfide, Fe-Ni metal, chromite, Ca phosphate), roughly estimated mode the minerals and rough measurement of the chemical compositions of the silicates show that these particles are roughly similar to LL chondrites. Although their size are mostly less than 10 m, some larger particles of about 100 m or larger were also identified. A part of the sample (probably several tens particles) will be selected by Hayabusa sample curation team and examined preliminary in Japan within one year after the sample recovery in prior to detailed analysis phase. Hayabusa Asteroidal Sample Preliminary Examination Team (HASPET) has been preparing for the preliminary examination with close cooperation with the curation team.

Tsuchiyama, A.↗
NASA NTRS2014

NASA's Astromaterials Database: Enabling Research Through Increased Access to Sample Data, Metadata and Imagery

The Astromaterials Acquisition & Curation Office at NASA's Johnson Space Center (JSC) is the designated facility for curating all of NASA's extraterrestrial samples. Today, the suite of collections includes the lunar samples from the Apollo missions, cosmic dust particles falling into the Earth's atmosphere, meteorites collected in Antarctica, comet and interstellar dust particles from the Stardust mission, asteroid particles from Japan's Hayabusa mission, solar wind atoms collected during the Genesis mission, and space‐exposed hardware from several missions. To support planetary science research on these samples, JSC's Astromaterials Curation Office hosts NASA's Astromaterials Curation digital repository and data access portal [http://curator.jsc.nasa.gov/], providing descriptions of the missions and collections, and critical information about each individual sample. Our office is designing and implementing several informatics initiatives to better serve the planetary research community. First, we are re‐hosting the basic database framework by consolidating legacy databases for individual collections and providing a uniform access point for information (descriptions, imagery, classification) on all of our samples. Second, we continue to upgrade and host digital compendia that summarize and highlight published findings on the samples (e.g., lunar samples, meteorites from Mars). We host high resolution imagery of samples as it becomes available, including newly scanned images of historical prints from the Apollo missions. Finally we are creating plans to collect and provide new data, including 3D imagery, point cloud data, micro CT data, and external links to other data sets on selected samples. Together, these individual efforts will provide unprecedented digital access to NASA's Astromaterials, enabling preservation of the samples through more specific and targeted requests, and supporting new planetary science research and collaborations on the samples.

Evans, Cindy↗
NASA NTRS2015

Comprehensive Non-Destructive Conservation Documentation of Lunar Samples Using High-Resolution Image-Based 3D Reconstructions and X-Ray CT Data

Established contemporary conservation methods within the fields of Natural and Cultural Heritage encourage an interdisciplinary approach to preservation of heritage material (both tangible and intangible) that holds "Outstanding Universal Value" for our global community. NASA's lunar samples were acquired from the moon for the primary purpose of intensive scientific investigation. These samples, however, also invoke cultural significance, as evidenced by the millions of people per year that visit lunar displays in museums and heritage centers around the world. Being both scientifically and culturally significant, the lunar samples require a unique conservation approach. Government mandate dictates that NASA's Astromaterials Acquisition and Curation Office develop and maintain protocols for "documentation, preservation, preparation and distribution of samples for research, education and public outreach" for both current and future collections of astromaterials. Documentation, considered the first stage within the conservation methodology, has evolved many new techniques since curation protocols for the lunar samples were first implemented, and the development of new documentation strategies for current and future astromaterials is beneficial to keeping curation protocols up to date. We have developed and tested a comprehensive non-destructive documentation technique using high-resolution image-based 3D reconstruction and X-ray CT (XCT) data in order to create interactive 3D models of lunar samples that would ultimately be served to both researchers and the public. These data enhance preliminary scientific investigations including targeted sample requests, and also provide a new visual platform for the public to experience and interact with the lunar samples. We intend to serve these data as they are acquired on NASA's Astromaterials Acquisistion and Curation website at http://curator.jsc.nasa.gov/. Providing 3D interior and exterior documentation of astromaterial samples addresses the increasing demands for accessability to data and contemporary techniques for documentation, which can be realized for both current collections as well as future sample return missions.

Blumenfeld, E. H.↗
NASA NTRS2017

50th Anniversary of the World's First Extraterrestrial Sample Receiving Laboratory: The Apollo Program's Lunar Receiving Laboratory

The Apollo program's Lunar Receiving Laboratory (LRL), building 37 at NASA's Manned Spaceflight Center (MSC), now Johnson Space Center (JSC), in Houston, TX, was the world's first astronaut and extraterrestrial sample quarantine facility (Fig. 1). It was constructed by Warrior Construction Co. and Warrior-Natkin-National at a cost of $8.1M be-tween August 10, 1966 and June 26, 1967. In 1969, the LRL received and curated the first collection of extra-terrestrial samples returned to Earth; the rock and soil samples of the Apollo 11 mission. This year, the JSC Astromaterials Acquisition and Curation Office (here-after JSC curation) celebrates 50 years since the opening of the LRL and its legacy of laying the foundation for modern curation of extraterrestrial samples.

Calaway, M. J.↗
NASA NTRS2020

Adapting Apollo-Era Instrumentation for Cold Sample Processing While Maintaining Curatorial Standard Practices

The goal of the Apollo Next Generation Sample Analysis (ANGSA) Program is to study “specially curated samples,” that is, unstudied Apollo samples that have been preserved under unique conditions. A subset of the funded ANGSA work includes the study of Apollo samples stored under cold conditions since their return from the Moon. Ongoing ANGSA processing and future returned samples require cold curation strategies to preserve the integrity of organic and other temperature-sensitive constituents within those samples. Standard Apollo curation processing hardware and procedures are designed for room temperature operations, not cold conditions. This abstract details the major modifications of a heritage lunar cabinet in preparation for the first cold curation processing at Johnson Space Center. Future publications will provide greater detail on the low temperature materials and operation procedures. This work not only supports Apollo but also future cold sample return missions.

Amick, Cecilia L.↗
NASA NTRSDate not supplied

Clean is not Sterile: A Planetary Science and Planetary Protection Perspective on Cleanroom Microbiology at NASA

The Astromaterials Acquisition and Curation Office at NASA is responsible for the curation of extraterrestrial samples from NASA’s past and future sample return missions. Our office curates samples from the moon, meteorites, comets, asteroids, cosmic dust and solar wind particles. All these samples are kept in cleanrooms to limit particulate and trace metal contamination, but none of these cleanrooms are specifically designed to control microbial contamination. During the early Apollo missions NASA scientists were very concerned with protecting the Earth from potential microbial contamination from the moon and with protecting the lunar samples from terrestrial microbes. NASA developed specialized equipment and clean rooms to keep these collections pristine. However, as we learned more about the lunar environment our concerns about microbial contamination lessened. Today none of the existing collections have microbial contamination requirements because they are not considered susceptible to microbial alteration under curation conditions (e.g. solar wind samples, and lunar samples) or have already been contaminated by terrestrial biology (meteorites collected in Antarctica). However, NASA’s OSIRIS-REx mission will land in 2023 with samples from a carbon rich asteroid that will be susceptible to microbial alteration. The Perseverance rover on Mars will begin to collect and cache samples that will be returned to Earth as soon as 2031. Martian samples may contain signs of extraterrestrial life and will have to be treated like the early Apollo samples. Martian samples will be isolated to protect the Earth, and must also be protected from terrestrial contamination. I will present microbial monitoring data from existing NASA cleanrooms and discuss how NASA is planning to use techniques from the pharmaceutical industry and academia to design new laboratories and equipment that will protect astromaterials and the earth from unwanted microbial contamination. I will also discuss a project to sample the external microbiome of the International Space Station. Results from this research will be used to design facilities for use on Mars that limit the amount of contamination associated with crewed missions.

Aaron B Regberg↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗
NASA NTRSDate not supplied

Managing Multi-Instrument Data Streams in Secure Environments

The capture and curation of all primary instrument data is a potentially valuable source of added insight into experiments or diagnostics in laboratory experiments. The data can, when properly curated, enable analysis beyond the current practice that uses just a subset of the as-measured data. Complete curated data can also be input for machine learning and other data exploration tools. Conveniently storing and accessing instrument data requires that the instruments are connected to databases and users through a networking infrastructure. This infrastructure needs to accommodate a wide array of instruments which can range from single laboratory mounted probes for environment monitoring to computers managing multiple instruments. These resources may also include mobile devices on which researchers record instrument and experiment state related notes. These varied data sources bring with them the challenges of different communications capabilities and protocols as well as the primary data typically being produced in proprietary formats. These challenges are further compounded when the instruments need to operate in secure environments such as required in national laboratories. We will discuss the SmartLab, an ongoing effort to set up a system for instrument and simulation data curation at NASA Langley Research Center. We will outline the challenges faced in managing the data sources required for ongoing research activities and the solutions that are being considered and implemented to address those challenges.

instrument data management↗
NASA NTRSDate not supplied

Assessing the Oxygen Permeability of Candidate Asteroid Sample Containers With Optochemical Sensors

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center currently curates 500 mg (10%) of carbonaceous asteroid Ryugu regolith collected by the Japan Aerospace and Exploration Agency’s Hayabusa II spacecraft and returned to Earth in 2021. In September 2023, NASA’s OSIRIS-REx spacecraft returned at least 70 grams of regolith collected from the surface of Carbonaceous Asteroid Bennu. These new astromaterials collections are stored and handled in gloveboxes and desiccators that are continuously purged with ultrapure nitrogen in order to minimize contamination and alteration of extraterrestrial samples from terrestrial environments, e.g., reaction with terrestrial oxygen and water. Ito et al. have previously reported on the development of containers to transport samples between facilities in inert, sealed environments; Hayabusa2 samples allocated to investigators by JAXA’s Extraterrestrial Sample Curation Center (ESCuC) are shipped in these Facility-to-Facility Transfer Containers (FFTCs). NASA curation has also been investigating sealed containers for storage, transportation, and allocation of Bennu and Ryugu regolith in sealed anoxic environments. In order to assess the ability of candidate sample containers to maintain nitrogen environments, we have utilized optochemical sensors to measure trace oxygen levels within sealed volumes.

C J Snead↗
NASA NTRSDate not supplied

NASA GeneLab: Open Science for Life in Space

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 350 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab Sequencing Lab. The GLDS contains rich metadata about each experiment and has integrated radiation dosimetry data from experiments flown on the Space Shuttle, International Space Station, and Free Flying spacecrafts. With the increasing amount and complexity of omics data being generated, GeneLab utilizes community-defined, common models for metadata and terminology so that omics data and results are discoverable and reliably reproducible. GeneLab uses the ISA-Tab specification and semantic model for organizing and representing omics metadata. In addition to metadata standards, data files must be open-source file or common exchange formats to ensure accessibility and usability by all users. To ease data ingestion and transfer, the web-based submission tool allows PIs a user-friendly user interface to curate, organize, and publish their space relevant omics data. In the more recent years, data curation and submission portal has incorporated the FAIR principles making data findable, accessible, interoperable, and reusable. To increase reusability of data, GeneLab has implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 200 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. To train the next generation of scientists, NASA offers training programs such as GeneLab 4 High School (GL4HS) and GeneLab 4 Universities. NLM Curation at a Scale Workshop 2022 | NASA GeneLab (GL4U) to teach students bioinformatics and computational biology methods to analyze omics data. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

GeneLab↗
NASA NTRSDate not supplied

Trace Oxygen Measurements of Asteroid Sample Storage Desiccators

The Astromaterials Curation facility at the NASA Johnson Space Center is currently curating more than 120 g of carbonaceous asteroid Bennu material as well as over 500 mg of asteroid Ryugu [1 and 2]. These astromaterials are stored in isolating desiccators and gloveboxes under a continuous purge of pure (<1 ppm O 2 ) gaseous nitrogen. The oxygen and moisture concentrations in our OSIRIS-REx sample processing gloveboxes are continuously monitored via integrated sensors; however, our sample storage desiccators lack integrated oxygen and humidity sensors. In previous studies, we used PreSens Fibox 4 trace oxygen meters and optochemical PSt9 spot sensors to measure the oxygen concentrations in candidate asteroid sample containers that had been sealed in nitrogen; we determined that Eagle stainless steel containers inhibit the ingress of external oxygen for several weeks [3]. This optochemical sensor technology allowed us to take precise, contactless measurements within a trace range of 0 to 200 ppmv O 2 . The effectiveness of the trace oxygen sensors in our container experiments inspired us to utilize them to assess the performance of our desiccators that previously lacked trace oxygen monitoring. In this study, our goal was to determine the quality of the nitrogen purge in the isolating desiccator under normal operating conditions by measuring the trace oxygen content. Utilizing optochemical sensor technology, we determined how long the oxygen concentration takes to reach an equilibrium in the desiccator; that is, determine the rate at which the oxygen diffusion into the desiccator equals the rate at which oxygen diffuses out of the desiccator via N2 purge. Additionally, we wanted to determine the oxygen concentration at this equilibrium, the state in which our desiccators are in during normal operating conditions. We tested a custom three chamber desiccator manufactured by Germfree using a PSt9 trace oxygen sensor spot that was mounted into a ¼” National Pipe Tapered (NPT) metal flow-through cell and attached it to the desiccator exhaust. The desiccator consists of top, middle, and bottom isolating chambers. The top chamber door was opened for several minutes to simulate a sample exchange, it was sealed, and then purged ~15 Standard Cubic Feet per Hour (SCFH). Oxygen measurements were automatically recorded via the Fibox 4 trace oxygen meter in 5-minute intervals over the course of a 24-hour period. Our results indicate the desiccator reached an equilibrium value of 10-15 ppm O 2 after ~5 hours (Fig. 1). This data allows us to explore standards for purging and exchange protocols that can be applied to similar types of desiccators in Hayabusa2, OSIRIS-REx, and for sample return collections. The assessment of the internal gaseous compositions of desiccators also allows us to share with the community the N 2 environment in which many of our asteroid samples and hardware are securely curated. Future measurements will include other nitrogen flow rates and measuring the trace oxygen concentration as a function of time for the levels of the previous commercial desiccator in which the Hayabusa2 sample collection was stored. We will also analyze how long the desiccators hold N2 after being disconnected from their N2 source, an extended measurement for sample security reassurance.

Curation↗
NASA NTRS2026

The NASA OSIRIS-REx Sample Catalog: Samples Returned from Investigators

OSIRIS-REx is a sample return mission that collected carbon-rich material from B-type asteroid Bennu. After landing on September 24th, 2023, the science canister was transported to NASA Johnson Space Center (JSC) in Houston, Texas where it was opened and samples were processed by the curation team in pristine sample nitrogen gloveboxes. As the sample analysis phase of the OSIRIS-REx mission concludes, the Sample Analysis Team (SAT) has returned the majority of mission samples to NASA JSC curation and will return the remaining samples on a defined timetable. The curation team processed and documented as many of these samples as possible to include in the spring 2026 catalog update and are steadily working to process hundreds of more samples to include in the fall 2026 catalog update.

OSIRIS-REx↗
DOE OSTI2022

Comparison of Machine Learning and Deep Learning for View Identification from Cardiac Magnetic Resonance Images

Background: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep learning (DL) and classical machine learning (ML) techniques without user input. We aimed to compare the accuracy of ML and DL for CMR view classification and to identify potential pitfalls during training and testing of the algorithms. Methods: To train our DL and ML algorithms, we first established datasets by retrospectively selecting 200 CMR cases. The models were trained using two different cohorts (passively and actively curated) and applied data augmentation to enhance training. Once trained, the models were validated on an external dataset, consisting of 20 cases acquired at another center. We then compared accuracy metrics and applied class activation mapping (CAM) to visualize DL model performance. Results: The DL and ML models trained with the passively-curated CMR cohort were 99.1% and 99.3% accurate on the validation set, respectively. However, when tested on the CMR cases with complex anatomy, both models performed poorly. After training and testing our models again on all 200 cases (active cohort), validation on the external dataset resulted in 95% and 90% accuracy, respectively. The CAM analysis depicted heat maps that demonstrated the importance of carefully curating the datasets to be used for training. Conclusions: Both DL and ML models can accurately classify CMR images, but DL outperformed ML when classifying images with complex heart anatomy.

artificial intelligence↗
DOE OSTI2022

Training data selection for accuracy and transferability of interatomic potentials

Abstract Advances in machine learning (ML) have enabled the development of interatomic potentials that promise the accuracy of first principles methods and the low-cost, parallel efficiency of empirical potentials. However, ML-based potentials struggle to achieve transferability, i.e., provide consistent accuracy across configurations that differ from those used during training. In order to realize the promise of ML-based potentials, systematic and scalable approaches to generate diverse training sets need to be developed. This work creates a diverse training set for tungsten in an automated manner using an entropy optimization approach. Subsequently, multiple polynomial and neural network potentials are trained on the entropy-optimized dataset. A corresponding set of potentials are trained on an expert-curated dataset for tungsten for comparison. The models trained to the entropy-optimized data exhibited superior transferability compared to the expert-curated models. Furthermore, the models trained to the expert-curated set exhibited a significant decrease in performance when evaluated on out-of-sample configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strategies for community-sourced biocuration in bioinformatics: a case study on MIBiG 4.0

Biocuration is essential to transform molecular sequence data into standardized, machine-readable resources. Such curated datasets enable comparative analysis, predictive modeling, and data integration across bioinformatics platforms. While professional biocuration is resource-intensive and usually limited to institutional settings, community-driven approaches can mobilize large-scale annotation of specialized datasets and are more resilient to disruptions in scientific funding. Here, we present a model for community-powered curation applied to the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) repository. Through a framework of workflows for metadata capture, annotation validation, and contributor coordination, the MIBiG 4.0 initiative recruited 267 scientists across 178 institutions from 33 countries, volunteering an estimated 4000 h of work. These efforts expanded the MIBiG repository by 22% and enhanced its usability in downstream molecular data analyses in comparative genomic analyses, natural product discovery, and machine learning applications. We provide strategies and actionable lessons for adopting this model, supporting the sustainability of curated bioinformatics resources central to nucleic acid research and related fields.

biocuration↗
DOE OSTI2024

Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning

Abstract Motivation Creating knowledge bases and ontologies is a time consuming task that relies on manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not able to populate arbitrarily complex nested knowledge schemas. Results Here we present Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES), a Knowledge Extraction approach that relies on the ability of Large Language Models (LLMs) to perform zero-shot learning and general-purpose query answering from flexible prompts and return information conforming to a specified schema. Given a detailed, user-defined knowledge schema and an input text, SPIRES recursively performs prompt interrogation against an LLM to obtain a set of responses matching the provided schema. SPIRES uses existing ontologies and vocabularies to provide identifiers for matched elements. We present examples of applying SPIRES in different domains, including extraction of food recipes, multi-species cellular signaling pathways, disease treatments, multi-step drug mechanisms, and chemical to disease relationships. Current SPIRES accuracy is comparable to the mid-range of existing Relation Extraction methods, but greatly surpasses an LLM’s native capability of grounding entities with unique identifiers. SPIRES has the advantage of easy customization, flexibility, and, crucially, the ability to perform new tasks in the absence of any new training data. This method supports a general strategy of leveraging the language interpreting capabilities of LLMs to assemble knowledge bases, assisting manual knowledge curation and acquisition while supporting validation with publicly-available databases and ontologies external to the LLM. Availability and implementation SPIRES is available as part of the open source OntoGPT package: https://github.com/monarch-initiative/ontogpt.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Accurate and complete genomes from metagenomes

Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ExaWorks software development kit: a robust and scalable collection of interoperable workflows technologies

Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be mapped, scheduled, and launched on different computing. That requires a software stack that enables users to code their workflows and automate resource management and workflow execution. Currently, there are many workflow technologies with diverse levels of robustness and capabilities, and users face difficult choices of software that can effectively and efficiently support their use cases on HPC machines, especially when considering the latest exascale platforms. We contributed to addressing this issue by developing the ExaWorks Software Development Kit (SDK). The SDK is a curated collection of workflow technologies engineered following current best practices and specifically designed to work on HPC platforms. We present our experience with (1) curating those technologies, (2) integrating them to provide users with new capabilities, (3) developing a continuous integration platform to test the SDK on DOE HPC platforms, (4) designing a dashboard to publish the results of those tests, and (5) devising an innovative documentation platform to help users to use those technologies. Our experience details the requirements and the best practices needed to curate workflow technologies, and it also serves as a blueprint for the capabilities and services that DOE will have to offer to support a variety of scientific heterogeneous workflows on the newly available exascale HPC platforms.

97 MATHEMATICS AND COMPUTING↗