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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Using Numba for GPU acceleration of Neutron Beamline Digital Twins

Digital twins of neutron instruments using Monte Carlo ray tracing have proven to be useful in neutron data analysis and verifying instrument and sample designs. However, these simulations can become quite complex and computationally demanding with tens of billions of neutrons. In this paper, we present a GPU accelerated version of MCViNE using Python and Numba to balance user extensibility with performance. Numba is an open-source just-in-time (JIT) compiler for Python using LLVM to generate efficient machine code for CPUs and GPUs with NVIDIA CUDA. The JIT nature of Numba allowed complex instrument kernels to be generated easily. Initial simulations have shown a speedup between 200-1000x over the original CPU implementation. The performance gain with Numba enables more sophisticated data analysis and impacts neutron scattering science and instrument design.

Kendrick, Coleman↗
DOE OSTI2024

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Complex interactions between day length and diurnal patterns of gene expression drive photoperiodic responses in a perennial C 4 grass

Abstract Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost‐effective 3′‐Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C 4 perennial grass, Panicum hallii . We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine‐scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis ‐regulatory elements and biological processes under short‐ and long‐day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod‐dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well‐known GI‐interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

Weng, Xiaoyu↗
DOE OSTI2018

Pushing the limits of electron ptychography

Here, ptychographic imaging in transmission electron microscopy is based on the detection of a huge number of diffraction patterns generated as an electron-beam probe scans the sample. Unlike conventional diffraction experiments where information about the phase of the scattered beam is lost, by scanning the entire sample and recording the diffraction patterns, an inversion analysis can reconstruct the complex amplitude of the beam and ultimately the atomic positions. Probe beams continue to decrease in size and can be much smaller than the distance between scatterers. The diffraction spots also broaden and interfere with one another (see the figure). Analysis of this interference allows more information to be extracted, such as minute details of nuclei position and electronic structure that define physical properties and enable visualization of subtle details of electric fields, orbital orderings, ferroic behavior, and perhaps local spins. Ptychography and related techniques are poised to revolutionize the field of electron microscopy, in much the same way as they have in x-ray crystallography (1), and as aberration correction has achieved for imaging, provided that some key challenges can be met.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Root system architecture and environmental flux analysis in mature crops using 3D root mesocosms

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of full-sized plant root systems in 3-dimensions, we developed customized mesocosm growth containers. While highly scalable, the design presented here uses an internal volume of 45 ft 3 (1.27 m 3 ), suitable for large crop and bioenergy grass root systems to grow largely unconstrained. Furthermore, they allow for the excavation and preservation of 3-dimensional root system architecture (RSA), and facilitate the collection of time-resolved subterranean environmental data. Sensor arrays monitoring matric potential, temperature and CO 2 levels are buried in a grid formation at various depths to assess environmental fluxes at regular intervals. Methods of 3D data visualization of fluxes were developed to allow for comparison with root system architectural traits. Following harvest, the recovered root system can be digitally reconstructed in 3D through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. We developed a pipeline to extract features from the 3D point clouds, or from derived skeletons that include point cloud voxel number as a proxy for biomass, total root system length, volume, depth, convex hull volume and solidity as a function of depth. Ground-truthing these features with biomass measurements from manually dissected root systems showed a high correlation. We evaluated switchgrass, maize, and sorghum root systems to highlight the capability for species wide comparisons. We focused on two switchgrass ecotypes, upland (VS16) and lowland (WBC3), in identical environments to demonstrate widely different root system architectures that may be indicative of core differences in their rhizoeconomic foraging strategies. Finally, we imposed a strong physiological water stress and manipulated the growth medium to demonstrate whole root system plasticity in response to environmental stimuli. Hence, these new “3D Root Mesocosms” and accompanying computational analysis provides a new paradigm for study of mature crop systems and the environmental fluxes that shape them.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Unraveling design principles of protein landscapes in photosynthetic membranes in plant chloroplasts

The supramolecular organization of proteins within photosynthetic membranes is crucial for energy conversion in plants. Here, we introduce an analytical and computational pipeline that integrates high-resolution cryo–scanning electron microscopy, biochemical quantification, advanced Monte Carlo computer simulations, and statistical methods to elucidate the elusive protein landscapes of grana membranes in intact Arabidopsis leaves. Our integrated analysis challenges the prevailing view that particles on the exoplasmic fracture faces in freeze-fracture samples represent photosystem II exclusively. Instead, these particles also include cytochrome b 6 f complexes. Furthermore, our steric clash analysis demonstrates that stacked membranes contain a mixture of larger PSII supercomplexes (C 2 S 2 M 2 and C 2 S 2 ) in addition to a smaller complex (C 2 ). This suggests that in vivo PSII supercomplexes exist in an equilibrium distribution of differing sizes. Furthermore, we discovered that, although size exclusion effects govern the global protein arrangement, local packing exhibits orientational order indicative of lateral attractive protein-protein interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Soil Carbon and Nitrogen Elemental Analysis and Middle Infrared Spectroscopy from the Kougarok Fire Complex, Seward Peninsula, Alaska, 2022

In September and October of 2022, soil samples were collected at the Kougarok Fire Complex near mile marker 86 of the Nome-Taylor Highway on the Seward Peninsula of Alaska. This study site was chosen due to its unique fire history, as the Kougarok Fire Complex has experienced multiple wildfires since 1971. As the Arctic warms, the risk of Arctic tundra fires continues to increase due to warmer summer temperatures and higher frequency of lightning. Burned soil carbon or pyrogenic carbon (PyC) is an important component of C cycling after wildfire, and one that is often overlooked in tundra systems where wildfires are historically rare. To better understand PyC signatures and quantify PyC presence in post-regeneration permafrost regions, soils were sampled from soil pits within the 1971, 2002, and 2019 burn sites, as well as two unburned control sites. At each site, three soil pits were dug to the permafrost table. Soil samples were collected with a trowel from the face of each pit at 10 cm increments down to the permafrost table. Thaw depth, maximum vegetation height, vegetation species composition, and O horizon depth were also collected at each soil pit. An HS2 Hydrosense II Handheld Soil Moisture Sensor was used to collect volumetric soil moisture content at each 10 cm sampling increment. This dataset includes one *.csv of middle infrared spectroscopy measurements of soil samples, one *.csv of field observations, one *.csv of carbon and nitrogen analysis of soil samples, and one *.kml of sampling locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measurement bias in self-heating x-ray free electron laser experiments from diffraction studies of phase transformation in titanium

X-ray self-heating is a common by-product of X-ray Free Electron Laser (XFEL) techniques that can affect targets, optics, and other irradiated materials. Diagnosis of heating and induced changes in samples may be performed using the x-ray beam itself as a probe. However, the relationship between conditions created by and inferred from x-ray irradiation is unclear and may be highly dependent on the material system under consideration. Here, we report on a simple case study of a titanium foil irradiated, heated, and probed by a MHz XFEL pulse train at 18.1 keV delivered by the European XFEL using measured x-ray diffraction to determine temperature and finite element analysis to interpret the experimental data. We find a complex relationship between apparent temperatures and sample temperature distributions that must be accounted for to adequately interpret the data, including beam averaging effects, multivalued temperatures due to sample phase transitions, and jumps and gaps in the observable temperature near phase transformations. The results have implications for studies employing x-ray probing of systems with large temperature gradients, particularly where these gradients are produced by the beam itself. Finally, this study shows the potential complexity of studying nonlinear sample behavior, such as phase transformations, where biasing effects of temperature gradients can become paramount, precluding clear observation of true transformation conditions.

Crystallography↗
DOE OSTI2021

Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry

Single quadrupole mass spectrometry (MS) with enhanced in-source multiple fragment ion monitoring was designed to perform high sensitivity quantitative mass analyses. Enhanced in-source fragmentation amplifies fragmentation from traditional soft electrospray ionization producing fragment ions that have been found to be identical to those generated in tandem MS. We have combined enhanced in-source fragmentation data with criteria established by the European Union Commission Directive 2002/657/EC for electron ionization single quadrupole quantitative analysis to perform quantitative analyses. These experiments were performed on multiple types of complex samples that included a mixture of 50 standards, as well as cell and plasma extracts. The dynamic range for these quantitative analyses was comparable to triple quadrupole multiple reaction monitoring (MRM) analyses at up to 5 orders of magnitude with the cell and plasma extracts showing similar matrix effects across both platforms. Amino acid and fatty acid measurements performed from certified NIST 1950 plasma with isotopically labeled standards demonstrated accuracy in the range of 91–110% for the amino acids, 76–129% for the fatty acids, and good precision (coefficient of variation <10%). To enhance specificity, a newly developed correlated ion monitoring algorithm was designed to facilitate these analyses. This algorithm autonomously processes, aligns, filters, and compiles multiple ions within one chromatogram enabling both precursor and in-source fragment ions to be correlated within a single chromatogram, also enabling the detection of coeluting species based on precursor and fragment ion ratios. Single quadrupole instrumentation can provide MRM level quantitative performance by monitoring/correlating precursor and fragment ions facilitating high sensitivity analysis on existing single quadrupole instrumentation that are generally inexpensive, easy to operate, and technically less complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Rapid monitoring of fermentations: a feasibility study on biological 2,3-butanediol production

2,3-butanediol (2,3-BDO) is an economically important platform chemical that can be produced by the fermentation of sugars using an engineered strain of Zymomonas mobilis . These fermentations require continuous monitoring and modification of fermentation conditions to maximize 2,3-BDO yields and minimize the production of the undesired coproducts glycerol and acetoin. Because of the time required for sampling and off-line chromatographic measurement of fermentation samples, the ability of fermentation scientists to modify fermentation conditions in a timely manner is limited. The goal of this study was to test if near-infrared spectroscopy (NIRS) along with multivariate statistics could reduce the time needed for this analysis and enable real-time monitoring and control of the fermentation. In this work we developed partial least squares (PLS) calibration models to predict the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol in fermentations via NIRS using two different spectrometers and two different spectroscopy modalities. We first evaluated the feasibility of rapid NIRS monitoring through experiments where we measured the signals from each analyte of interest and built NIRS-based PLS models using spectra from synthetic samples containing uncorrelated concentrations of these analytes. All analytes showed unique spectral signatures, and this initial modeling showed that all analytes could be detected simultaneously. We then began work with samples from laboratory fermentation experiments and tested the feasibility of regression model development across two spectral collection modalities (at-line and on-line) and two instruments: a laboratory-grade instrument and a low-cost instrument with a more limited spectral range. All modalities showed promise in the ability to monitor Z. mobilis fermentations of glucose and xylose to 2,3-BDO. The low-cost instrument displayed a lower signal-to-noise ratio than the laboratory-grade instrument, which led to comparatively lower performance overall, but still provided sufficient accuracy to monitor fermentation trends. While the ease of use of on-line monitoring systems was favored as compared to at-line systems due to the lack of sampling required and potential for automated process control, we observed some decrease in performance due to the additional complexity of the sample matrix. We have demonstrated that NIRS combined with multivariate analysis can be used for at-line and on-line monitoring of the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol during Z. mobilis fermentations. The decrease in signal-to-noise ratio when using a low-cost spectrometer led to greater prediction error than the laboratory-grade spectrometer for at-line monitoring. The on-line monitoring modality showed great promise for real time process control via NIRS.

09 BIOMASS FUELS↗
DOE OSTI2021

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation, and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to ‘omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Furthermore, thus far, BP4NTA group members have aimed to establish consensus on NTA-related terms and concepts, and to create consistency in reporting practices by providing resources on a public website, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Simultaneous Determination of Halogens and Metals in Waste Plastic Pyrolysis Oil by Inductively Coupled Plasma Mass Spectrometry

A major barrier to integrating pyrolysis-derived oil into conventional refinery technology is the presence of impurities, particularly halogens and metals, that can deactivate catalysts. This study presents a novel, cost-effective approach for the simultaneous analysis of a subset of halogens, metals, nonmetals, and metalloids in complex, industrially relevant distilled pyrolysis oil samples, this was previously achievable only through multiple techniques. Excellent results were obtained using a widely accessible inductively coupled plasma mass spectrometry (ICP-MS) method with helium gas mode and standard laboratory consumables, enabling high-throughput analysis and efficient evaluation of adsorbent performance. Sample preparation is straightforward, requiring only dilution in a compatible matrix, and provides accurate and precise quantification, with 75%–137% spike recovery for Be, Ti, V, Cr, Fe, Ni, Co, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, and 62%–65% spike recovery for Cl and 109%–133% spike recovery for Br. Additionally, an enhanced version of the method using ICP-MS/MS and hydrogen gas is described, which has higher accuracy with 69%–112% spike recovery for Be, B, Ti, V, Fe, Co, Ni, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, with 85%–102% spike recovery for Cl and 63%–93% spike recovery for Br. Helium mode detection limits for industrially relevant elements (V, Fe, Ni, Cu, As, and Pb) are less than 1.7 µg/kg, and less than 0.2 mg/kg for Br and Cl. Furthermore, this methodology facilitates rapid systematic evaluation of adsorption capacities of materials under time-on-stream conditions and supports robust comparisons across diverse operating environments.

Lazarcik, James [University of Wisconsin-Madison, ↗
DOE OSTI2021

Exploration of multifidelity UQ sampling strategies for computer network applications.

Network modeling is a powerful tool to enable rapid analysis of complex systems that can be challenging to study directly using physical testing. Here, two approaches are considered: emulation and simulation. The former runs real software on virtualized hardware, while the latter mimics the behavior of network components and their interactions in software. Although emulation provides an accurate representation of physical networks, this approach alone cannot guarantee the characterization of the system under realistic operative conditions. Operative conditions for physical networks are often characterized by intrinsic variability (payload size, packet latency, etc.) or a lack of precise knowledge regarding the network configuration (bandwidth, delays, etc.); therefore uncertainty quantification (UQ) strategies should be also employed. UQ strategies require multiple evaluations of the system with a number of evaluation instances that roughly increases with the problem dimensionality, i.e., the number of uncertain parameters. It follows that a typical UQ workflow for network modeling based on emulation can easily become unattainable due to its prohibitive computational cost. In this paper, a multifidelity sampling approach is discussed and applied to network modeling problems. The main idea is to optimally fuse information coming from simulations, which are a low-fidelity version of the emulation problem of interest, in order to decrease the estimator variance. By reducing the estimator variance in a sampling approach it is usually possible to obtain more reliable statistics and therefore a more reliable system characterization. Several network problems of increasing difficulty are presented. For each of them, the performance of the multifidelity estimator is compared with respect to the single fidelity counterpart, namely, Monte Carlo sampling. For all the test problems studied in this work, the multifidelity estimator demonstrated an increased efficiency with respect to MC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A single column separation method for barium isotope analysis of geologic and hydrologic materials with complex matrices

Abstract The increasing significance of barium (Ba) in environmental and geologic research in recent years has led to interest in the application of the Ba isotopic composition as a tracer for natural materials with complex matrices. Most Ba isotope measurement techniques require separation of Ba from the rest of sample prior to analysis. This paper presents a method using readily available materials and disposable columns that effectively separates Ba from a range of geologic and hydrologic materials, including carbonate minerals, silicate rocks, barite, river water, and fluids with high total dissolved solids and organic content such as oil and gas brines, rapidly and without need for an additional cleanup column. The technique involves off-the-shelf columns and cation exchange resin and a two-reagent elution that uses 2.5 N HCl followed by addition of 2.0 N HNO 3 . We present data to show that major matrix elements from almost any natural material are separated from Ba in a single column pass, and that the method also effectively reduces or eliminates isobaric interferences from lanthanum and cerium.

Matecha, R. M.↗
DOE OSTI2019

Implementation and assessment of resolution-dependent elastic incoherent neutron scattering measurements at a backscattering spectrometer for probing relaxations in complex systems

We introduce the use of a higher-order reflection, Si(333), of the silicon analyzer crystals at a backscattering spectrometer to implement analysis of the relaxation dynamics in the samples. Here, this is achieved by monitoring the temperature dependence of the neutron scattering intensity perceived as elastic when measured using Si(111), Si(311), and Si(333) reflections. As a test case, we use a sample with well-characterized, but complex, relaxation pattern, where the non-Lorentzian relaxation function is known to exhibit a set of parameters specific to each temperature point and scattering momentum transfer (Q) value. Even for this very general relaxation pattern, characterized by no constrains on the relaxation function parameters, we successfully map the relaxation times measured using the present approach onto those previously obtained from the full analysis of the quasielastic neutron scattering signal. Analysis of the Q-specific activation energies becomes possible for the Q values accessible simultaneously through Si(111), Si(311), and Si(333) reflections (in the present case, 0.9 Å –1 < Q < 1.9 Å –1 ). While the dedicated neutron spectrometers for this type of analysis are yet to be constructed, we show that the present-day backscattering spectrometers can be employed, under certain conditions, to analyze temperature dependence of the relaxation time in the samples not amenable to traditional full analysis of the quasielastic neutron scattering signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time-consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in-part from our in silico Chemical Library Engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency’s (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence, and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multi-attribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally-derived libraries for building evidence for the presence of molecules in complex samples.

Nunez, Jamie↗
DOE OSTI2024

Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Tracking HIV-1 recombination to resolve its contribution to HIV-1 evolution in natural infection

Recombination in HIV-1 is well documented, but its importance in the low-diversity setting of within-host diversification is less understood. Here we develop a novel computational tool (RAPR (Recombination Analysis PRogram)) to enable a detailed view of in vivo viral recombination during early infection, and we apply it to near-full-length HIV-1 genome sequences from longitudinal samples. Recombinant genomes rapidly replace transmitted/founder (T/F) lineages, with a median half-time of 27 days, increasing the genetic complexity of the viral population. We identify recombination hot and cold spots that differ from those observed in inter-subtype recombinants. Furthermore, RAPR analysis of longitudinal samples from an individual with well-characterized neutralizing antibody responses shows that recombination helps carry forward resistance-conferring mutations in the diversifying quasispecies. These findings provide insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis and have implications for studies of HIV transmission and evolution in vivo.

59 BASIC BIOLOGICAL SCIENCES↗