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NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

NASA NTRS2023

Microbial Adaptation to Spaceflight Is Correlated With Bacteriophage-Encoded Functions

Evidence from the International Space Station suggests microbial populations are rapidly adapting to the spacecraft environment; however, the mechanism of this adaptation is not understood. Bacteriophages are prolific mediators of bacterial adaptation on Earth. Here we survey 245 genomes sequenced from bacterial strains isolated on the International Space Station for dormant (lysogenic) bacteriophages. Our analysis indicates phage-associated genes are significantly different between spaceflight strains and their terrestrial counterparts. Additionally, we identify 283 complete prophages, those that could initiate bacterial lysis and infect additional hosts, of which 21% are novel. These prophage regions encode functions that correlate with increased persistence in extreme environments, such as spaceflight, to include antimicrobial resistance and virulence, DNA damage repair, and dormancy. Our results correlate microbial adaptation in spaceflight to bacteriophage-encoded functions that may impact human health in spaceflight.

Space Biology↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

space biology↗

NASA NTRSDate not supplied

Differential Gene Expression in A Cross-Feeding Two-Species Model Microbial Community Under Simulated Microgravity and Deep-Space Radiation

A long-term goal of space biology is to understand interspecies microbial interactions in space. Presently, little is known about the combined effect of microgravity and ionizing radiation on bacterial community response when species are interdependent through exchange of metabolites in fluid medium (cross-feeding). Microgravity is expected to slow interspecies mass transfer and growth in cross-feeding communities in the low-shear, diffusion-limited environment, while ionizing radiation may influence stress response to direct (DNA damage) and indirect damage (ROS). Using a well-understood, two-species (Escherichia coli and Salmonella enterica) microbial community engineered to be a model for studying cross-feeding, we simulated galactic cosmic rays (GCRsim) and microgravity to test the hypothesis: exposure to ionizing radiation causes cell damage or stress, altering transcriptomic community responses in metabolically interdependent cells, which is exacerbated by microgravity. We expect to see differential gene expression between cross-feeding and non-cross-feeding communities. We measured GCRsim effects on growth and gene expression in well-mixed versus simulated-microgravity conditions and in cross-feeding and non-cross-feeding medium. Microbial cultures were inoculated into liquid medium in rotating wall vessels (RWV) with different rotation rates: 5 RPM (simulated microgravity) and 50 RPM (well-mixed). The E. coli-S. enterica consortium, under simulated microgravity, were exposed to 500 mGy of Simplified 5-ion Galactic Cosmic Ray Simulation for 2 hours at Brookhaven National Lab. We harvested samples 40 minutes after irradiation for extraction and sequencing (NASA GeneLab). Here we present the differential gene expression analysis results, which reveal altered transcriptomic community responses, even where growth rate differences are not observed. Gene expression of these actively metabolizing microbial communities in GCRsim may illuminate molecular mechanisms of microbial interactions in space. Understanding how microbial community gene expression, metabolism, and other cellular processes are influenced by spaceflight stressors can inform the use of microbes in human life support for low Earth orbit missions and beyond.

microgravity↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

NASA NTRSDate not supplied

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗

NASA NTRSDate not supplied

Development of Genetic Countermeasures for Enhancing Cellular Stress Tolerance on a Lunar Surface Mission

The Lunar Explorer Instrument for space biology Applications (LEIA) LEIA investigates the response to partial gravity and ionizing radiation of: Different DNA damage and stress response pathways and Bioproduction of antioxidants LEIA utilizes: Various strains of the yeast Saccharomyces cerevisiae, which will be desiccated in fluidic cards and rehydrated on the lunar surface LEIA develops: Genetic countermeasures to improve tolerance to the desiccation process and the constraints associated with long duration missions beyond low Earth orbit (LEO)

Neha Lingam↗

NASA NTRSDate not supplied

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

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

Yeast Engineering↗

NASA NTRS1973

Research progress in radiation detectors, pattern recognition programs, and radiation damage determination in DNA

The radiological implications of statistical variations in energy deposition by ionizing radiation were investigated in the conduct of the following experiments: (1) study of the production of secondary particles generated by the passage of the primary radiation through bone and muscle; (2) the study of the ratio of nonreparable to reparable damage in DNA as a function of different energy deposition patterns generated by X rays versus heavy fast charged particles; (3) the use of electronic radiography systems for direct fluoroscopic tomography and for the synthesis of multiple planes and; (4) the determination of the characteristics of systems response to split fields having different contrast levels, and of minimum detectable contrast levels between the halves under realistic clinical situations.

Baily, N. A.↗

DOE OSTI2024

Evaluating the risk of data loss due to particle radiation damage in a DNA data storage system

DNA data storage is a potential alternative to magnetic tape for archival storage purposes, promising substantial gains in information density. Critical to the success of DNA as a storage media is an understanding of the role of environmental factors on the longevity of the stored information. In this paper, we evaluate the effect of exposure to ionizing particle radiation, a cause of data loss in traditional magnetic media, on the longevity of data in DNA data storage pools. We develop a mass action kinetics model to estimate the rate of damage accumulation in DNA strands due to neutron interactions with both nucleotides and residual water molecules, then utilize the model to evaluate the effect several design parameters of a typical DNA data storage scheme have on expected data longevity. Finally, we experimentally validate our model by exposing dried DNA samples to different levels of neutron irradiation and analyzing the resulting error profile. Our results show that particle radiation is not a significant contributor to data loss in DNA data storage pools under typical storage conditions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

DNA-DSB in CHO-K1 cells induced by heavy-ions: Break rejoining and residual damage (GSI)

DNA double strand breaks (DSB's) are the critical lesions involved in cellular effects of ionizing radiation. Therefore, the evaluation of DSB induction in mammalian cells after heavy ion irradiation is an essential task for the assessment of high-LET radiation risk in space. Of particular interest has been the question of how the biological efficiency for the cellular inactivation endpoint relates to the initial lesions (DSBs) at varying LETs. For cell killing, an increased Relative Biological Efficiency (RBE) has been determined for highLET radiation around 100-200 keV/mu m. At higher LET, the RBE's decrease again to values below one for the very heavy particles. At GSI, DSB-induction was measured in CHO-K1 cells following irradiation with accelerated particles covering a wide LET range. The electrophoretic elution of fragmented DNA out of agarose plugs in a constant electrical field was applied for the detection of DSB's. The fraction of DNA retained was determined considering the relative intensities of ethidium bromide fluorescence in the well and in the gel lane. Dose-effect curves were established, from which the RBE for DSB induction was calculated at a fraction of 0.7 of DNA retained In summary, these rejoining studies are in line with an enhanced severity of the DNA DSB's at higher LET's, resulting in a decreased repairability of the induced lesions. However, no information concerning the fidelity of strand breaks rejoining is provided in these studies. To assess correct rejoining of DNA fragments an experimental system involving individual DNA hybridization bands has been set up. In preliminary experiments Sal I generated DNA fragments of 0.9 Mbp were irradiated with xrays and incubated for repair However, restitution of the original signals was not observed, probably due to the high radiation dose necessary for breakage of a fragment of this size. A banding pattern with NotI hybridization signals in a higher MW range (3Mbp) has been obtained by varying the electrophoretic conditions and correct rejoining studies will be further developed in this system.

Taucher-Scholz, G.↗

NASA NTRS2008

Non-DBS DNA Repair Genes Regulate Radiation-induced Cytogenetic Damage Repair and Cell Cycle Progression

Changes of gene expression profile are one of the most important biological responses in living cells after ionizing radiation (IR) exposure. Although some studies have shown that genes up-regulated by IR may play important roles in DNA damage repair, the relationship between the regulation of gene expression by IR, particularly genes not known for their roles in DSB repair, and its impact on cytogenetic responses has not been systematically studied. In the present study, the expression of 25 genes selected on the basis of their transcriptional changes in response to IR was individually knocked down by transfection with small interfering RNA in human fibroblast cells. The purpose of this study is to identify new roles of these selected genes on regulating DSB repair and cell cycle progression , as measured in the micronuclei formation and chromosome aberration. In response to IR, the formation of MN was significantly increased by suppressed expression of 5 genes: Ku70 in the DSB repair pathway, XPA in the NER pathway, RPA1 in the MMR pathway, and RAD17 and RBBP8 in cell cycle control. Knocked-down expression of 4 genes (MRE11A, RAD51 in the DSB pathway, SESN1, and SUMO1) significantly inhibited cell cycle progression, possibly because of severe impairment of DNA damage repair. Furthermore, loss of XPA, P21, or MLH1 expression resulted in both significantly enhanced cell cycle progression and increased yields of chromosome aberrations, indicating that these gene products modulate both cell cycle control and DNA damage repair. Most of the 11 genes that affected cytogenetic responses are not known to have clear roles influencing DBS repair. Nine of these 11 genes were up-regulated in cells exposed to gamma radiation, suggesting that genes transcriptionally modulated by IR were critical to regulate the biological consequences after IR.

Zhang, Ye↗

NASA NTRS2002

Space flight and oxidative stress

Space flight is associated with an increase in oxidative stress after return to 1g. The effect is more pronounced after long-duration space flight. The effects lasts for several weeks after landing. In humans there is increased lipid peroxidation in erythrocyte membranes, reduction in some blood antioxidants, and increased urinary excretion of 8-iso-prostaglandin F(2alpha) and 8-oxo-7,8 dihydro-2 deoxyguanosine. Isoprostane 8-iso-prostaglandin F(2alpha) and 8-oxo-7,8 dihydro-2 deoxyguanosine are markers for oxidative damage to lipids and DNA, respectively. The changes have been attributed to a combination of the energy deficiency that occurs during flight and substrate competition for amino acids occurring between repleting muscle and other tissues during the recovery phase. The observations in humans have been complemented by rodent studies. Most rodent studies showed increased production of lipid peroxidation products postflight and decreased antioxidant enzyme activity postflight. The rodent observations were attributed to the stress associated with reentry into Earth's gravity. Decreasing the imbalance between the production of endogenous oxidant defenses and oxidant production by increasing the supply of dietary antioxidants may lessen the severity of the postflight increase in oxidative stress.

long duration↗

NASA NTRS2006

Electron-Impact Ionization and Dissociative Ionization of Biomolecules

It is well recognized that secondary electrons play an important role in radiation damage to humans. Particularly important is the damage of DNA by electrons, potentially leading to mutagenesis. Molecular-level study of electron interaction with DNA provides information on the damage pathways and dominant mechanisms. Our study of electron-impact ionization of DNA fragments uses the improved binary-encounter dipole model and covers DNA bases, sugar phosphate backbone, and nucleotides. An additivity principle is observed. For example, the sum of the ionization cross sections of the separate deoxyribose and phosphate fragments is in close agreement with the C3(sup prime)- and C5 (sup prime)-deoxyribose-phospate cross sections, differing by less than 5%. Investigation of tandem double lesion initiated by electron-impact dissociative ionization of guanine, followed by proton reaction with the cytosine in the Watson-Crick pair, is currently being studied to see if tandem double lesion can be initiated by electron impact. Up to now only OH-induced tandem double lesion has been studied.

Huo, Winifred M.↗

NASA NTRS2000

Homologous recombination as a potential target for caffeine radiosensitization in mammalian cells: reduced caffeine radiosensitization in XRCC2 and XRCC3 mutants

The radiosensitizing effect of caffeine has been associated with the disruption of multiple DNA damage-responsive cell cycle checkpoints, but several lines of evidence also implicate inhibition of DNA repair. The role of DNA repair inhibition in caffeine radiosensitization remains uncharacterized, and it is unknown which repair process, or lesion, is affected. We show that a radiosensitive cell line, mutant for the RAD51 homolog XRCC2 and defective in homologous recombination repair (HRR), displays significantly diminished caffeine radiosensitization that can be restored by expression of XRCC2. Despite the reduced radiosensitization, caffeine effectively abrogates checkpoints in S and G2 phases in XRCC2 mutant cells indicating that checkpoint abrogation is not sufficient for radiosensitization. Another radiosensitive line, mutant for XRCC3 and defective in HRR, similarly shows reduced caffeine radiosensitization. On the other hand, a radiosensitive mutant (irs-20) of DNA-PKcs with a defect in non-homologous end-joining (NHEJ) is radiosensitized by caffeine to an extent comparable to wild-type cells. In addition, rejoining of radiation-induced DNA DSBs, that mainly reflects NHEJ, remains unaffected by caffeine in XRCC2 and XRCC3 mutants, or their wild-type counterparts. These observations suggest that caffeine targets steps in HRR but not in NHEJ and that abrogation of checkpoint response is not sufficient to explain radiosensitization. Indeed, immortalized fibroblasts from AT patients show caffeine radiosensitization despite the checkpoint defects associated with ATM mutation. We propose that caffeine radiosensitization is mediated by inhibition of stages in DNA DSB repair requiring HRR and that checkpoint disruption contributes by allowing these DSBs to transit into irreparable states. Thus, checkpoints may contribute to genomic stability by promoting error-free HRR.

NASA Discipline Radiation Health↗

NASA NTRS2004

Role of shielding in modulating the effects of solar particle events: Monte Carlo calculation of absorbed dose and DNA complex lesions in different organs

Distributions of absorbed dose and DNA clustered damage yields in various organs and tissues following the October 1989 solar particle event (SPE) were calculated by coupling the FLUKA Monte Carlo transport code with two anthropomorphic phantoms (a mathematical model and a voxel model), with the main aim of quantifying the role of the shielding features in modulating organ doses. The phantoms, which were assumed to be in deep space, were inserted into a shielding box of variable thickness and material and were irradiated with the proton spectra of the October 1989 event. Average numbers of DNA lesions per cell in different organs were calculated by adopting a technique already tested in previous works, consisting of integrating into "condensed-history" Monte Carlo transport codes--such as FLUKA--yields of radiobiological damage, either calculated with "event-by-event" track structure simulations, or taken from experimental works available in the literature. More specifically, the yields of "Complex Lesions" (or "CL", defined and calculated as a clustered DNA damage in a previous work) per unit dose and DNA mass (CL Gy-1 Da-1) due to the various beam components, including those derived from nuclear interactions with the shielding and the human body, were integrated in FLUKA. This provided spatial distributions of CL/cell yields in different organs, as well as distributions of absorbed doses. The contributions of primary protons and secondary hadrons were calculated separately, and the simulations were repeated for values of Al shielding thickness ranging between 1 and 20 g/cm2. Slight differences were found between the two phantom types. Skin and eye lenses were found to receive larger doses with respect to internal organs; however, shielding was more effective for skin and lenses. Secondary particles arising from nuclear interactions were found to have a minor role, although their relative contribution was found to be larger for the Complex Lesions than for the absorbed dose, due to their higher LET and thus higher biological effectiveness. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Non-NASA Center↗

DOE OSTI2025

Processing of DNA single-strand breaks with oxidatively damaged ends by LIG1

Abstract DNA ligase 1 (LIG1) seals broken strand breaks by joining two adjacent ends during DNA replication and repair transactions. We previously reported atomic-level insight into the strategies that LIG1 uses to discriminate mismatches or ribonucleotides. However, how LIG1 processes strand breaks with oxidatively damaged ends in the absence and presence of a “wrong” sugar remains unknown. Here, we determined the crystal structures of LIG1/nick DNA complexes with 3′-8-oxodG and 3′-8-oxorG templating A or C during the pre- and post-catalytic steps of the ligation reaction. Our structures demonstrated differences in the distances at the +1 and +2 nucleotides relative to the 3′-end of the nick and a shift in the template base position to accommodate the oxidative lesion depending on the dual coding potential of 8-oxoG, which forms Hoogsteen or Watson–Crick base pairing in -syn or -anti conformation. Furthermore, these structural adjustments lead to mutagenic ligation or non-mutagenic end joining of the nick substrates. Overall, our findings provide mechanistic insight into how LIG1 processes nicks harboring oxidative damage and ribonucleotides to ensure fidelity at the final ligation step of DNA repair and replication to maintain genome integrity.

Balu, Kanal E [Department of Biochemistry and Mole↗