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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
DOE OSTI2013

A New Genetic Linkage Map of the Zygomycete Fungus Phycomyces blakesleeanus

Phycomyces blakesleeanus is a member of the subphylum Mucoromycotina. A genetic map was constructed from 121 progeny of a cross between two wild type isolates of P. blakesleeanus with 134 markers. The markers were mostly PCRRFLPs. Markers were located on 46 scaffolds of the genome sequence, covering more than 97% of the genome. Analysis of the alleles in the progeny revealed nine or 12 linkage groups, depending on the log of the odds (LOD) score, across 1583.4 cM at LOD 5. The linkage groups were overlaid on previous mapping data from crosses between mutants, aided by new identification of the mutations in primary metabolism mutant strains. The molecular marker map, the phenotype map and the genome sequence are overall congruent, with some exceptions. The new genetic map provides a genome-wide estimate for recombination, with the average of 33.2 kb per cM. This frequency is one piece of evidence for meiosis during zygospore development in Mucoromycotina species. At the same time as meiosis, transmission of non-recombinant chromosomes is also evident in the mating process in Phycomyces. The new map provides scaffold ordering for the genome sequence and a platform upon which to identify the genes in mutants that are affected in traits of interest, such as carotene biosynthesis, phototropism or gravitropism, using positional cloning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Deconstruction of the Ras switching cycle through saturation mutagenesis

Ras proteins are highly conserved signaling molecules that exhibit regulated, nucleotide-dependent switching between active and inactive states. The high conservation of Ras requires mechanistic explanation, especially given the general mutational tolerance of proteins. Here, we use deep mutational scanning, biochemical analysis and molecular simulations to understand constraints on Ras sequence. Ras exhibits global sensitivity to mutation when regulated by a GTPase activating protein and a nucleotide exchange factor. Removing the regulators shifts the distribution of mutational effects to be largely neutral, and reveals hotspots of activating mutations in residues that restrain Ras dynamics and promote the inactive state. Evolutionary analysis, combined with structural and mutational data, argue that Ras has co-evolved with its regulators in the vertebrate lineage. Overall, our results show that sequence conservation in Ras depends strongly on the biochemical network in which it operates, providing a framework for understanding the origin of global selection pressures on proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Time sequence gamma-spectrometry of irradiated salt

Persisted Memory Mapping File (MMF) techniques have developed for the processing and analysis of time-stamped list (TLIST) mode data collected from an irradiated salt sample. This is a new technique that is unique to this research and enables additional information to be obtained from a conventional pulse height analysis (PHA) gamma-spectrometry acquisition. A salt sample was irradiated using a DT neutron generator and immediately measured using TLIST acquisition for 1 month to generate a 22 GB data file. MMF techniques were used to process the file without size restrictions at a rate of 388.5 MB minute-1, with instant access to any position within the file, separating the file into a series of time sequenced spectra suitable for PHA analysis. This enabled 14 activation products to be identified at different time intervals (41Ar, 80Br, 80mBr, 47Ca, 34mCl, 38Cl, 42K, 43K, 56Mn, 22Na, 24Na, 85Sr, 87mSr and 69mZn), and 6 radionuclides (80Br, 47Ca, 34mCl, 56Mn, 24Na and 87mSr) to be definitively confirmed based upon their measured half-life. Using this technique, the detection of 47Ca, and in-growth of its 47Sc progeny, was demonstrated as useful for calculating the time since irradiation.

Burnett, Jonathan L.↗
DOE OSTI2015

Large Scale Sequencing of Dothideomycetes Provides Insights into Genome Evolution and Adaptation

Dothideomycetes is the largest and most diverse class of ascomycete fungi with 23 orders 110 families, 1300 genera and over 19,000 known species. We present comparative analysis of 70 Dothideomycete genomes including over 50 that we sequenced and are as yet unpublished. This extensive sampling has almost quadrupled the previous study of 18 species and uncovered a 10 fold range of genome sizes. We were able to clarify the phylogenetic positions of several species whose origins were unclear in previous morphological and sequence comparison studies. We analyzed selected gene families including proteases, transporters and small secreted proteins and show that major differences in gene content is influenced by speciation.

Haridas, Sajeet↗
DOE OSTI2019

HIV Databases video tutorial on use of the HIV sequence quality control tool

The HIV Databases at LANL (https://www.hiv.lanl.gov) provide many tools for HIV data retrieval and analysis. The quality control tool (https://www.hiv.lanl.gov/content/sequence/QC/index.html) is used to check the quality of new HIV sequence data, help the user determine which subtype of virus belongs to, and prepare the data for submission to the database. This video gives a 10 minute overview of the use of the tool and illustrates results form a sample data set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Final Technical Report to DOE for the Award DE-SC0004601

Understanding the responses, adaptations and feedback mechanisms of biological communities to climate change is critical to project future state of earth and climate systems. Although significant amount of knowledge is available on the feedback responses of aboveground communities to climate change, little is known about the responses of belowground microbial communities due to the challenges in analyzing soil microbial community structure. Thus the goal overall goal of this study is to provide system-level, predictive mechanistic understanding of the temperature sensitivity of soil carbon (C) decomposition to climate warming by using cutting-edge integrated metagenomic technologies. Towards this goal, the following four objectives will be pursued: (i) To determine phylogenetic composition and metabolic diversity of microbial communities in the temperate grassland and tundra ecosystems; (ii) To delineate the responses of microbial community structure, functions and activities to climate change in the temperate grassland and tundra ecosystems; (iii) To determine the temperature sensitivity of microbial respiration in soils with different mixtures of labile versus recalcitrant C, and the underlying microbiological basis for temperature sensitivity of these pools; and (iv) To synthesize all experimental data for revealing microbial control of ecosystem carbon processes in responses to climate change. We have achieved our goals for all four proposed objectives. First, we determined the phylogenetic composition and metabolic diversity of microbial communities in the temperate grassland and tundra ecosystems. For this objective, we have developed a novel phasing amplicon sequencing (PAS) approach for MiSeq sequencing of amplicons. This approach has been used for sequencing various phylogenetic and functional genes related to ecosystem functioning. A comprehensive functional gene array (e.g., GeoChip 5.0) has also been developed and used for soil microbial community analysis in this study. In addition, shot-gun metagenome sequencing along with the above approaches have been used to understand the phylogenetic and functional diversity, composition, and structure of soil microbial communities in both temperature grassland and tundra ecosystems. Second, we determined the response of soil microbial communities to climate warming in both temperate grassland and tundra ecosystems using various methods. Our major findings are: (i) Microorganisms are very rapid to respond to climate warming in the tundra ecosystem, AK, which is vulnerable, too. (ii) Climate warming also significantly shifted the metabolic diversity, composition and structure of microbial communities, and key metabolic pathways related to carbon turnover, such as cellulose degradation (~13%) and CO2 production (~10%), and to nitrogen cycling, including denitrification (~12%) were enriched by warming. (iii) Warming also altered the expression patterns of microbial functional genes important to ecosystem functioning and stability through GeoChip and metatranscriptomic analysis of soil microbial communities at the OK site. Third, we analyzed temperature sensitivity of C decomposition to climate warming for both AK and OK soils through laboratory incubations. Key results include: (i) Alaska tundra soils showed that after one year of incubation, CT in the top 15 cm could be as high as 25% and 15% of the initial soil C content at 25°C and 15°C incubations, respectively. (ii) analysis of 456 incubated soil samples with 16S rRNA gene, ITS and GeoChip hybridization showed that warming shifted the phylogenretic and functional diversity, composition, structure and metabolic potential of soil microbial communities, and at different stages of incubation, key populations and functional genes significantly changed along with soil substrate changes. Functional gene diversity and functional genes for degrading labile C components decrease along incubation when labile C components are exhausting, but the genes related to degrading recalcitrant C increase. These molecular data will be directly used for modeling. Fourth, we have developed novel approaches to integrate and model experimental data to understand microbial control of ecosystem C processes in response to climate change. We compared different methods to calculate Q10 for estimating temperature sensitivity, and new approaches for Q10 calculation and molecular ecological network analysis were also developed. Using those newly developed approaches, our result indicated that Q10s increased with the recalcitrance of C pools, suggesting that longer incubation studies are needed in order to assess the temperature sensitivity of slower C pools, especially at low temperature regimes. This project has been very productive, resulting in 42 papers published or in press, 4 submitted, and 13 in preparation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗
DOE OSTI2015

Primer and platform effects on 16S rRNA tag sequencing

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. In conclusion, beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

16S rRNA gene sequencing↗
DOE OSTI2012

Soil solid phases effects on the proteomic analysis of Cupriavidus metallidurans CH34

Cupriavidus metallidurans CH34 is a completely sequenced soil-borne beta-proteobacterium with known genome and proteome. Comparative 2-D electrophoresis and protein mass spectrometry were used to compare the proteome of C. metallidurans CH34 from liquid culture and after incubation for 1, 3, and 12 days in microcosms containing quartz sand, kaolinite, montmorillonite, or an artificial soil. Results showed that proteome from liquid culture was similar to CH34 proteins extracted from sand and kaolinite, whereas the proteins extracted from artificial soil differed significantly and no proteins were detected from C. metallidurans CH34 incubated in the montmorillonite microcosms. Protein recovery decreased on prolonging incubation time in all microcosms. Mass spectrometry identification showed that the trend of lower recovery upon incubation time was independent on the putative function of protein. These results suggest that the soil solid phase influences the protein recovery and soil proteomic analysis and that distinction between protein recovery and protein expression in soil will be a challenging for soil proteomic researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Quantitative analysis of mammalian translation initiation sites by FACS -seq

An approach combining fluorescence-activated cell sorting and high-throughput DNA sequencing (FACS-seq) was employed to determine the efficiency of start codon recognition for all possible translation initiation sites (TIS) utilizing AUG start codons. Using FACS-seq, we measured translation from a genetic reporter library representing all 65,536 possible TIS sequences spanning the -6 to +5 positions. We found that the motif RYMRMVAUGGC enhanced start codon recognition and translation efficiency. However, dinucleotide interactions, which cannot be conveyed by a single motif, were also important for modeling TIS efficiency. Our dataset combined with modeling allowed us to predict genome-wide translation initiation efficiency for all mRNA transcripts. Additionally, we screened somatic TIS mutations associated with tumorigenesis to identify candidate driver mutations consistent with known tumor expression patterns. Finally, we implemented a quantitative leaky scanning model to predict alternative initiation sites that produce truncated protein isoforms and compared predictions with ribosome footprint profiling data. The comprehensive analysis of the TIS sequence space enables quantitative predictions of translation initiation based on genome sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Bulk segregant and QTL analysis of maltose metabolism in Saccharomyces eubayanus

This study investigates natural variation in maltose utilization among Saccharomyces eubayanus strains isolated from different tree hosts. An F2 population was generated from a cross between strain QC18 (Quercus-associated) and strain CL467.1 (Nothofagus-associated). Bulk segregant analysis (BSA) was performed on the F2 offspring, and QTL mapping was conducted by whole-genome sequencing of two pools of 30 segregants each, representing the lowest and highest growth in high maltose concentrations. For QTL analysis, the parental strains QC18 and CL467.1 were also sequenced.

evolutionary plasticity↗
DOE OSTI2025

Long-read RNA sequencing atlas of human microglia isoforms elucidates disease-associated genetic regulation of splicing

Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. Mapping the genetics of gene expression in human microglia has identified several loci associated with disease-associated genetic variants in microglia-specific regulatory elements. However, identifying genetic effects on splicing is challenging because of the use of short sequencing reads. Here, we present the isoform-centric microglia genomic atlas (isoMiGA), which leverages long-read RNA sequencing to identify 35,879 novel microglia isoforms. We show that these isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ancestry meta-analysis of 555 human microglia short-read RNA sequencing samples from 391 donors, and found associations with genetic risk loci in Alzheimer’s and Parkinson’s disease. We nominate several loci that may act through complex changes in isoform and splice-site usage.

59 BASIC BIOLOGICAL SCIENCES↗