SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Genomic islands (GIs) are mobile genetic elements that integrate into host genomes via self-encoded integrases at specific DNA sequences known as attachment (att) sites. The ability to predict the target att site from an integrase's protein sequence is a central challenge in genomics due to the sequence diversity of integrases and the subtlety of their DNA recognition motifs.
Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.
Chemical modifications of DNA and histone proteins impact the organization of chromatin within the nucleus. Changes in these modifications, catalysed by different chromatin-modifying enzymes, influence chromatin organization, which in turn is thought to impact the spatial and temporal regulation of gene expression. While combinations of different histone modifications, the histone code, have been studied in several model species, we know very little about histone modifications in the fungal genus Aspergillus, whose members are generally well studied due to their importance as models in cell and molecular biology as well as their medical and biotechnological relevance. Here, we used phylogenetic analyses in 94 Aspergilli as well as other fungi to uncover the occurrence and evolutionary trajectories of enzymes and protein complexes with roles in chromatin modifications or regulation. We found that these enzymes and complexes are highly conserved in Aspergilli, pointing towards a complex repertoire of chromatin modifications. Nevertheless, we also observed few recent gene duplications or losses, highlighting Aspergillus species to further study the roles of specific chromatin modifications. SET7 (KMT6) and other components of PRC2 (Polycomb Repressive Complex 2), which is responsible for methylation on histone H3 at lysine 27 in many eukaryotes including fungi, are absent in Aspergilli as well as in closely related Penicillium species, suggesting that these lost the capacity for this histone modification. We corroborated our computational predictions by performing untargeted MS analysis of histone post-translational modifications in Aspergillus nidulans. This systematic analysis will pave the way for future research into the complexity of the histone code and its functional implications on genome architecture and gene regulation in fungi.
Allosteric signaling within multidomain proteins is a driver of communication between spatially distant functional sites. Understanding the mechanism of allosteric coupling in large multidomain proteins is the most promising route to achieving spatial and temporal control of the system. The recent explosion of CRISPR-Cas9 applications in molecular biology and medicine has created a need to understand how the atomic level protein dynamics of Cas9, which are the driving force of its allosteric crosstalk, influence its biophysical characteristics. In this study, we used a synergistic approach of nuclear magnetic resonance (NMR) and computation to pinpoint an allosteric hotspot in the HNH domain of the thermostable GeoCas9. We show that mutation of K597 to alanine disrupts a salt-bridge network, which in turn alters the structure, the timescale of allosteric motions, and the thermostability of the GeoHNH domain. This homologous lysine-to-alanine mutation in the extensively studied mesophilic S. pyogenes Cas9 similarly alters the dynamics of the SpHNH domain. We have previously demonstrated that the alteration of allostery via mutations is a source for the specificity enhancement of SpCas9 (eSpCas9). Hence, this may also be true in GeoCas9.
Theranostics are emerging as a pillar of cancer therapy that enable the use of single molecule constructs for diagnostic and therapeutic application. As poly adenosine diphosphate (ADP)-ribose polymerase 1 (PARP-1) is overexpressed in various cancer types, and is localized to the nucleus, PARP-1 can be safely targeted with Auger emitters to induce DNA damage in tumors. Here, we investigated a radioiodinated PARP inhibitor, [125I]KX1, and show drug target specific DNA damage and subsequent killing of BRCA1 and non-BRCA mutant ovarian cancer cells at sub-pharmacological concentrations several orders of magnitude lower than traditional PARP inhibitors. Furthermore, we demonstrated that viable tumor tissue from ovarian cancer patients can be used to screen tumor radiosensitivity ex-vivo, enabling the direct assessment of therapeutic efficacy. Finally, we showed tumors can be imaged by single-photon computed tomography (SPECT) with PARP theranostic, [123I]KX1, in a human ovarian cancer xenograft mouse model. These data support the utility of PARP-1 targeted radiopharmaceutical therapy as a theranostic option for PARP-1 overexpressing ovarian cancers.
We fulfilled all original three aims of the proposal. Following the earlier release (during the first phase of the project at Montana) of software that identifies and fills gaps in the annotation of metabolic proteins within bacterial genomes, we have nearly completed a second gap-filling tool that improves accuracy and explainability. We completed software for alignment-based annotation of protein coding DNA, allowing for coding frameshifts caused by sequencing error. Finally, we completed a neural embedding model for identifying similarities between protein sequences based on amino-wise latent vectors.
The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. Here, in this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.
To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.
Transcription-coupled repair is essential for the removal of DNA lesions from the transcribed genome. The pathway is initiated by CSB protein binding to stalled RNA polymerase II. Mutations impairing CSB function cause severe genetic disease. Yet, the ATP-dependent mechanism by which CSB powers RNA polymerase to bypass certain lesions while triggering excision of others is incompletely understood. Here we build structural models of RNA polymerase II bound to the yeast CSB ortholog Rad26 in nucleotide-free and bound states. This enables simulations and graph-theoretical analyses to define partitioning of this complex into dynamic communities and delineate how its structural elements function together to remodel DNA. We identify an allosteric pathway coupling motions of the Rad26 ATPase modules to changes in RNA polymerase and DNA to unveil a structural mechanism for CSB-assisted progression past less bulky lesions. Our models allow functional interpretation of the effects of Cockayne syndrome disease mutations.
ABSTRACT Cdt1 is a mixed folded protein critical for DNA replication licensing and it also has a “moonlighting” role at the kinetochore via direct binding to microtubules and the Ndc80 complex. However, it is unknown how the structure and conformations of Cdt1 could allow it to participate in these multiple, unique sets of protein complexes. While robust methods exist to study entirely folded or unfolded proteins, structure–function studies of combined, mixed folded/disordered proteins remain challenging. In this work, we employ orthogonal biophysical and computational techniques to provide structural characterization of mitosis‐competent human Cdt1. Thermal stability analyses shows that both folded winged helix domains1 are unstable. CD and NMR show that the N‐terminal and linker regions are intrinsically disordered. DLS shows that Cdt1 is monomeric and polydisperse, while SEC‐MALS confirms that it is monomeric at high concentrations, but without any apparent inter‐molecular self‐association. SEC‐SAXS enabled computational modeling of the protein structures. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble of structures. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with SAXS. The best‐fit models have the N‐terminal and linker disordered regions extended into the solution and the two folded domains close to each other in apparent “folded over” conformations. We hypothesize the best‐fit Cdt1 conformations could be consistent with a function as a scaffold protein that may be sterically blocked without binding partners. Our study also provides a template for combining experimental and computational techniques to study mixed‐folded proteins.
Transcription factor IIH (TFIIH) is a protein assembly essential for transcription initiation and nucleotide excision repair (NER). Yet, understanding of the conformational switching underpinning these diverse TFIIH functions remains fragmentary. TFIIH mechanisms critically depend on two translocase subunits, XPB and XPD. To unravel their functions and regulation, we build cryo-EM based TFIIH models in transcription- and NER-competent states. Using simulations and graph-theoretical analysis methods, we reveal TFIIH’s global motions, define TFIIH partitioning into dynamic communities and show how TFIIH reshapes itself and self-regulates depending on functional context. Our study uncovers an internal regulatory mechanism that switches XPB and XPD activities making them mutually exclusive between NER and transcription initiation. By sequentially coordinating the XPB and XPD DNA-unwinding activities, the switch ensures precise DNA incision in NER. Mapping TFIIH disease mutations onto network models reveals clustering into distinct mechanistic classes, affecting translocase functions, protein interactions and interface dynamics.
Abstract Advancing a microscopic framework that rigorously unveils the underlying topological hallmarks of fractional quantum Hall (FQH) fluids is a prerequisite for making progress in the classification of strongly-coupled topological matter. We present a second-quantization framework that reveals an exact fusion mechanism for particle fractionalization in FQH fluids, and uncovers the fundamental structure behind the condensation of non-local operators characterizing topological order in the lowest-Landau-level. We show the first exact analytic computation of the quasielectron Berry connections leading to its fractional charge and exchange statistics, and perform Monte Carlo simulations that numerically confirm the fusion mechanism for quasiparticles. We express the sequence of (bosonic and fermionic) Laughlin second-quantized states, highlighting the lack of local condensation, and present a rigorous constructive subspace bosonization dictionary for the bulk fluid. Finally, we establish universal long-distance behavior of edge excitations by formulating a conjecture based on the DNA, or root state, of the FQH fluid.
Reactive oxygen species (ROS) oxidize cellular nucleotide pools and cause double strand breaks (DSBs). Non-homologous end-joining (NHEJ) attaches broken chromosomal ends together in mammalian cells. Ribonucleotide insertion by DNA polymerase (pol) μ prepares breaks for end-joining and this is required for successful NHEJ in vivo. We previously showed that pol μ lacks discrimination against oxidized dGTP (8-oxo-dGTP), that can lead to mutagenesis, cancer, aging and human disease. Here we reveal the structural basis for proficient oxidized ribonucleotide (8-oxo-rGTP) incorporation during DSB repair by pol μ. Time-lapse crystallography snapshots of structural intermediates during nucleotide insertion along with computational simulations reveal substrate, metal and side chain dynamics, that allow oxidized ribonucleotides to escape polymerase discrimination checkpoints. Abundant nucleotide pools, combined with inefficient sanitization and repair, implicate pol μ mediated oxidized ribonucleotide insertion as an emerging source of widespread persistent mutagenesis and genomic instability.
This report describes research conducted to use data science and machine learning methods to distinguish targeted genome editing versus natural mutation and sequencer machine noise. Genome editing capabilities have been around for more than 20 years, and the efficiencies of these techniques has improved dramatically in the last 5+ years, notably with the rise of CRISPR-Cas technology. Whether or not a specific genome has been the target of an edit is concern for U.S. national security. The research detailed in this report provides first steps to address this concern. A large amount of data is necessary in our research, thus we invested considerable time collecting and processing it. We use an ensemble of decision tree and deep neural network machine learning methods as well as anomaly detection to detect genome edits given either whole exome or genome DNA reads. The edit detection results we obtained with our algorithms tested against samples held out during training of our methods are significantly better than random guessing, achieving high F1 and recall scores as well as with precision overall.
Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.
Utilizing an ionic liquid strategy, we report crystal structures of salts of free anionic nucleobases and base pairs previously studied only computationally and in the gas phase. Reaction of tetrabutylammonium ([N 4444 ] + ) or tetrabutylphosphonium ([P 4444 ] + ) hydroxide with adenine (HAd) and thymine (HThy) led to hydrated salts of deprotonated adenine, [N 4444 ][Ad]·2H 2 O, and thymine, [P 4444 ][Thy]·2H 2 O, as well as the double salt cocrystal, [P 4444 ] 2 [Ad][Thy]·3H 2 O·2HThy. The cocrystal includes the anionic [Ad-(HThy)] base pair which is a stable formation in the solid state that has previously not even been suggested. It exhibits Watson–Crick connectivity as found in DNA but which is unusual for the free neutral base pairs. The stability of the observed anionic bases and their supramolecular formations and hydrates has also been examined by electronic structure calculations, contributing to more insight into how base pairs can bind when a proton is removed and highlighting mechanisms of stabilization or chemical transformation in the DNA chains.
Excitation energy transfer (EET) is a key photoinduced process in biological chromophoric assemblies. Here we investigate the factors which can drive EET into efficient ultrafast sub-ps regimes. We demonstrate how a coherent transport of electronic population could facilitate this in water solvated NADH coenzyme and uncover the role of an intermediate dark charge-transfer state. High temporal resolution ultrafast optical spectroscopy gives a 54 ± 11 fs time constant for the EET process. Nonadiabatic quantum dynamical simulations computed through the time-evolution of multidimensional wavepackets suggest that the population transfer is mediated by photoexcited molecular vibrations due to strong coupling between the electronic states. The polar aqueous solvent environment leads to the active participation of a dark charge transfer state, accelerating the vibronically coherent EET process in favorably stacked conformers and solvent cavities. Our work demonstrates how the interplay of structural and environmental factors leads to diverse pathways for the EET process in flexible heterodimers and provides general insights relevant for coherent EET processes in stacked multichromophoric aggregates like DNA strands.
Displacive transformations in colloidal crystals may offer a pathway for increasing the diversity of accessible configurations without the need to engineer particle shape or interaction complexity. To date, binary crystals composed of spherically symmetric particles at specific size ratios have been formed that exhibit floppiness and facile routes for transformation into more rigid structures that are otherwise not accessible by direct nucleation and growth. There is evidence that such transformations, at least at the micrometer scale, are kinetically influenced by concomitant solvent motion that effectively induces hydrodynamic correlations between particles. Here, we study quantitatively the impact of such interactions on the transformation of binary bcc-CsCl analog crystals into close-packed configurations. We first employ principal-component analysis to stratify the explorations of a bcc-CsCl crystallite into orthogonal directions according to displacement. We then compute diffusion coefficients along the different directions using several dynamical models and find that hydrodynamic correlations, depending on their range, can either enhance or dampen collective particle motions. These two distinct effects work synergistically to bias crystallite deformations toward a subset of the available outcomes.