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At least 505 records · Page 28

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. In this paper, we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.

59 BASIC BIOLOGICAL SCIENCES↗

The antibody mining toolbox: An open source tool for the rapid analysis of antibody repertoires

In vitro selection has been an essential tool in the development of recombinant antibodies against various antigen targets. Deep sequencing has recently been gaining ground as an alternative and valuable method to analyze such antibody selections. The analysis provides a novel and extremely detailed view of selected antibody populations, and allows the identification of specific antibodies using only sequencing data, potentially eliminating the need for expensive and laborious low-throughput screening methods such as enzyme-linked immunosorbant assay. The high cost and the need for bioinformatics experts and powerful computer clusters, however, have limited the general use of deep sequencing in antibody selections. Here, we describe the AbMining ToolBox, an open source software package for the straightforward analysis of antibody libraries sequenced by the three main next generation sequencing platforms (454, Ion Torrent, MiSeq). The ToolBox is able to identify heavy chain CDR3s as effectively as more computationally intense software, and can be easily adapted to analyze other portions of antibody variable genes, as well as the selection outputs of libraries based on different scaffolds. The software runs on all common operating systems (Microsoft Windows, Mac OS X, Linux), on standard personal computers, and sequence analysis of 1–2 million reads can be accomplished in 10–15 min, a fraction of the time of competing software. Use of the ToolBox will allow the average researcher to incorporate deep sequence analysis into routine selections from antibody display libraries.

60 APPLIED LIFE SCIENCES↗

Identification and characterization of mono- and bifunctional galactan synthases in the pediatric pathogen Kingella kingae

The emerging pediatric pathogen Kingella kingae elaborates a lipopolysaccharide (LPS) that is extended with a galactofuranose homopolymer called galactan, which is a key virulence determinant that contributes to resistance to complement-mediated and neutrophil-mediated killing. Previous work has demonstrated that the pamABCDE locus is required for galactan synthesis. In this study, mutational studies suggested that the pamC gene product is a UDP-galactofuranose (Galf) transferase and is the galactan synthase. Analysis of genome sequence data revealed two distinct pamC alleles designated pamC1 and pamC2, which correlate with the two galactan structures in K. kingae. Examination of isogenic mutants expressing either pamC1 or pamC2 demonstrated that the pamC alleles are the determinants of galactan structure. Experiments with recombinant PamC1 and PamC2 in vitro established that these proteins are galactan synthases capable of extending synthetic Galf disaccharide acceptors in the presence of UDP-Galf. Homology analysis identified critical amino acids that are essential for PamC1 and PamC2 enzymatic activity both in vitro and in K. kingae. Structural analysis of the in vitro-modified synthetic acceptors implicated PamC1 as a monofunctional enzyme capable of generating a β-(1 → 5) Galf linkage and PamC2 as a bifunctional enzyme capable of generating β-(1 → 3) and β-(1 → 6) Galf linkages. This study advances our understanding of the GT2 family of UDP-galactofuranosyltransferases.

60 APPLIED LIFE SCIENCES↗

A Generalized Bio-inspired Method for Discovering Sequence-based Signatures

Many phenomena that we wish to discover are comprised of sequences of events or event primitives. Often signatures are constructed to identify such phenomena using either distributions or frequencies of attributes, or specific subsequences that are known to correlate to the phenomena. Distribution-based identification does not capture the essence of the sequence of behaviors and therefore may suffer from lack of specificity. At the other extreme, using specific subsequences to identify target phenomena is often too specific and suffers from lower sensitivity when natural variations arise in the phenomena, measuring process, or data analysis. We introduce here a method for discovering signatures for phenomena that are well characterized by sequences of event primitives. In this paper, we describe the steps taken and lessons learned in generalizing a sequence analysis method, BLAST, for use on non-biological datasets including expressing and operating on alphabets of varying length, constructing a reward/penalty model for arbitrary datasets, and discovering low complexity segments in sequence data by extending BLAST’s native low-complexity estimating algorithms. We also present several case studies that demonstrate the utility of this method to discovering signatures in a wide array of applications including network traffic, software analysis, server characterization, and others. Finally, we demonstrate how signatures discovered using this method can be expressed using a variety of model formalisms, each having its own relative benefit.

Signature Science↗

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ~4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using 14C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of 14C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)’s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.

54 ENVIRONMENTAL SCIENCES↗

VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data

Background: Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge. Results: We present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented. Conclusions: VizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/ VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux.

97 MATHEMATICS AND COMPUTING↗

The challenges of modelling antibody repertoire dynamics in HIV infection

Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. In addition, we describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.

59 BASIC BIOLOGICAL SCIENCES↗

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis. Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic reads to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. In conclusion, the algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains. Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.

59 BASIC BIOLOGICAL SCIENCES↗

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

Current diagnostics and clinical management strategies for combat wounds are based on decisions made by expert clinicians. However, even in the hands of experienced surgeons, wounds from combat injuries can exhibit failed healing and complications related to limitations in the rapid and comprehensive generation of diagnostic information. Previous studies have demonstrated the possible use of genomic sequencing approaches to detect microbial signatures involved in combat casualty care. While effective, whole metagenome sequencing is limited by the depth required to confidently detect all relevant signatures. To address this, we developed a targeted capture sequencing panel to detect microbial signatures relevant to wound healing. These targets include known microbial nosocomial pathogens, wound colonizers, and genes involved in virulence and antimicrobial resistance. A bioinformatics pipeline was built to identify genomic regions of interest and over 8,000 oligonucleotide probes were designed for capture. The panel was synthesized and validated using control reference genomes in human background and on wound-effluent samples from a cohort of combat-injured U.S. service members. Our panel was sensitive against wound-colonizing species, Acinetobacter baumannii and Pseudomonas aeruginosa, and was specific in detecting corresponding virulence and antimicrobial-resistance genes as well as other pathogenic species present in microflora mixtures. Random forest feature permutation confirmed the prevalence of Acinetobacter and Pseudomonas in critically colonized wounds and wounds that failed to heal, respectively. Our results demonstrate the capability of targeted sequencing tools and analysis platforms to profile and deliver information on pathogenic factors influencing wound progression, thereby guiding therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗

RNA‐Seq analysis revealed the molecular mechanisms of photobiomodulation effect on human fibroblasts

Abstract Background The photobiomodulation (PBM) effect has been applied to various clinical therapy for a long time. However, the mechanism related to the PBM effect in terms of wavelengths has been lack of in‐depth study, except that ultraviolet radiation has attracted much attention due to its strong cell‐killing effect. Purpose To clarify the principle behind PBM and the main mechanism of improvement. Methods To carry on this study, we created light equipment using three LED chips, which emit 390 nm ultraviolet radiation, 415 nm blue light and 660 nm red light, respectively. We choose human fibroblasts (HF) to be irradiated by three different wavelengths for PBM test. In this study, we used cell counting kit (CCK‐8) test to show the cell proliferation roughly and reported on a systematic RNA sequencing (RNA‐seq) analysis at transcriptional expression levels from HF, which accepted PBM of different wavelengths of light. Results We found that 415 nm blue light inhibited cell proliferation and 660 nm red light stimulated cell proliferation while 390 nm ultraviolet radiation has little influence on cell proliferation. Furthermore, RNA‐seq results showed that CSF1R, PPP3CC, ITGAL, ITGAM, IL2RB, and several other differentially expressed genes (DEGs) are involved in the cell proliferation. Relative DEGs values for matrix metalloproteinases (MMPs) gene family have shown a great difference in blue and red light radiation especially on MMP25, MMP9, MMP21, and MMP13. Conclusion Taken together, the results provide a valuable resource to describe the variation of HFs under PBM of different light at gene level.

Li, Wenqi↗

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping error rates low, as well as offering unique data visualization options.

59 BASIC BIOLOGICAL SCIENCES↗

Correlation of structure, function and protein dynamics in GH7 cellobiohydrolases from Trichoderma atroviride, T. reesei and T. harzianum

The ascomycete fungus Trichoderma reesei is the predominant source of enzymes for industrial conversion of lignocellulose. Its glycoside hydrolase family 7 cellobiohydrolase (GH7 CBH) TreCel7A constitutes nearly half of the enzyme cocktail by weight and is the major workhorse in the cellulose hydrolysis process. The orthologs from Trichoderma atroviride (TatCel7A) and Trichoderma harzianum (ThaCel7A) show high sequence identity with TreCel7A, ~ 80%, and represent naturally evolved combinations of cellulose-binding tunnel-enclosing loop motifs, which have been suggested to influence intrinsic cellobiohydrolase properties, such as endo-initiation, processivity, and off-rate. The TatCel7A, ThaCel7A, and TreCel7A enzymes were characterized for comparison of function. The catalytic domain of TatCel7A was crystallized, and two structures were determined: without ligand and with thio-cellotriose in the active site. Initial hydrolysis of bacterial cellulose was faster with TatCel7A than either ThaCel7A or TreCel7A. In synergistic saccharification of pretreated corn stover, both TatCel7A and ThaCel7A were more efficient than TreCel7A, although TatCel7A was more sensitive to thermal inactivation. Structural analyses and molecular dynamics (MD) simulations were performed to elucidate important structure/function correlations. Moreover, reverse conservation analysis (RCA) of sequence diversity revealed divergent regions of interest located outside the cellulose-binding tunnel of Trichoderma spp. GH7 CBHs. We hypothesize that the combination of loop motifs is the main determinant for the observed differences in Cel7A activity on cellulosic substrates. Fine-tuning of the loop flexibility appears to be an important evolutionary target in Trichoderma spp., a conclusion supported by the RCA data. Our results indicate that, for industrial use, it would be beneficial to combine loop motifs from TatCel7A with the thermostability features of TreCel7A. Furthermore, one region implicated in thermal unfolding is suggested as a primary target for protein engineering.

09 BIOMASS FUELS↗

Magic Angle Spinning NMR Reveals Sequence-Dependent Structural Plasticity, Dynamics, and the Spacer Peptide 1 Conformation in HIV-1 Capsid Protein Assemblies

Maturation of HIV-1 virus into an infectious virion requires cleavage of the Gag polyprotein into its constituent domains and formation of a conical capsid core that encloses viral RNA and a small complement of proteins for replication. The final step of this process is the cleavage of the SP1 peptide from the CA-SP1 maturation intermediate, which triggers the condensation of the CA protein into a conical capsid. The mechanism of this step, including the conformation of the SP1 peptide in CA-SP1, is under intense debate. In this report, we examine the tubular assemblies of CA and the CA-SP1 maturation intermediate using Magic Angle Spinning NMR spectroscopy. At the magnetic fields of 19.9 T and above, tubular CA and CA-SP1 assemblies yield outstanding-quality 2D and 3D MAS NMR spectra, which are amenable to resonance assignments and detailed structural characterization. Dipolar- and scalar-based correlation experiments unequivocally indicate that SP1 peptide is in a random coil conformation and mobile in the assembled CA-SP1. Analysis of two sequence variants reveals that remarkably, the conformation of SP1 tail, of the functionally important CypA loop, and of the loop preceding helix 8 are sequence dependent and modulated by the residue variations at distal sites. These findings challenge the role of SP1 as a conformational switch in the maturation process and establish sequence-dependent conformational plasticity in CA.

Environmental Molecular Sciences Laboratory↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

Analysis of Potential Leakage Pathways and Mineralization within Caprocks for Geologic Storage of CO 2

We used a multifaceted approach to investigate the nature of caprocks above, and the interface between, reservoir-quality rocks that might serve as targets for carbon storage. Fieldwork in southeastern Utah examined the regional- to m-scale nature of faults and fractures across the sedimentiological interfaces. We also used microscopic analyses and mechanical modeling to examine the question as to how the contacts between units interact, and how fractures may allow fluids to move from reservoirs to caprock. Regional-­scale analyses using ASTER data enabled us to identify location of alteration, which led to site-­specific studies of deformation and fluid flow. In the Jurassic Carmel Formation, a seal for the Navajo Sandstone, we evaluated mesoscale variability in fracture density and morphology and variability in elastic moduli in the Jurassic Carmel Formation, a proposed seal to the underlying Navajo Sandstone for CO 2 geosequestration. By combining mechano-stratigraphic outcrop observations with elastic moduli derived from wireline log data, we characterize the variability in fracture pattern and morphology with the observed variability in rock strength within this heterolithic top seal. Outcrop inventories of discontinuities show fracture densities decrease as bed thickness increases and fracture propagation morphology across lithologic interfaces vary with changing interface type. Dynamic elastic moduli, calculated from wireline log data, show that Young’s modulus varies by up to 40 GPa across depositional interfaces, and by an average of 3 GPa across the reservoir/seal interface. We expect that the mesoscale changes in rock strength will affect the distributions of localized stress and thereby influence fracture propagation and fluid flow behavior within the seal. These data provide a means to closely tie outcrop observations to those derived from subsurface data and estimates of subsurface rock strength. We also studied damage zones associated normal faults in the Permian Cedar Mesa Sandstone, southeastern Utah. These faults are characterized by a single slip surfaces and damage zones containing deformation bands, veins, and joints. Field observations include crosscutting relationships, permeability increase, rock strength decrease, and ultraviolet light induced mineral fluorescence within the damage zone. These field observations combined with the interpreted paragenetic sequence from petrographic analysis, suggests a deformation history of reactivation and several mineralization events in an otherwise low-permeability fault. All deformation bands and veins fluoresce under ultraviolet light, suggesting connectivity and a shared mineralization history. Pre-­existing deformation features act as loci for younger deformation and mineralization events, this fault and its damage zone illustrate the importance of the fault damage zone to subsurface fluid flow. We model a simplified stress history in order to understand the importance of rock properties and magnitude of tectonic stress on the deformation features within the damage zone. The moderate confining pressures, possible variations in pore pressure, and the porous, fine-­grained nature of the Cedar Mesa Sandstone results in a fault damage zone characterized by enhanced permeability, subsurface fluid flow, and mineralization. Structural setting greatly influences fracture spacing and orientation. Three structural settings were examined and include fault proximity, a fold limb of constant dip, and a setting proximal to the syncline hinge. Fracture spacing and dominant fracture orientation vary at each setting and distinctions between regional and local paleo-stress directions can be made. Joints on the fold limb strike normal to the fold axis/bedding and are interpreted to be sub-parallel to the maximum regional paleo-stress direction as there is no fold related strain. Joints proximal to faults and the syncline hinge may have formed under local stress conditions associated with folding and faulting, and in some cases, are perpendicular to the maximum regional paleo-stress direction. Macroscale analyses of the Iron Wash fault, which cuts most of the stratigraphy of the reservoir- seal analogs, reveals that seal bypass occurs along faults with mixed lithologic composition. While portions of the fault may be effective seals, when modeled as a whole the fault zone cannot support a high CO 2 column. We adapted oil-field methods to calculate column heights and sealing capacities. Examination of the burial and tectonic histories of the rocks, coupled with field- and micro-­scale studies, allow us to examine the potential for seal failure using basic rock mechanics failure analyses. These studies reveal that the sealing lithologies experienced multiple episodes of deformation that resulted in numerous fractures and small faults. In a stress state based on burial history and overburden loads, we show that most of the seals could fail with normal to slightly excess pore pressures.

58 GEOSCIENCES↗

Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias

Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗