Biophysical analysis of Pseudomonas-phage PaP3 small terminase suggests a mechanism for sequence-spe
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Niazi, Marzia↗
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Results for “sequence analysis”
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A phylogenetic analysis of the myxobacteria: basis for their classification
The primary sequence and secondary structural features of the 16S rRNA were compared for 12 different myxobacteria representing all the known cultivated genera. Analysis of these data show the myxobacteria to form a monophyletic grouping consisting of three distinct families, which lies within the delta subdivision of the purple bacterial phylum. The composition of the families is consistent with differences in cell and spore morphology, cell behavior, and pigment and secondary metabolite production but is not correlated with the morphological complexity of the fruiting bodies. The Nannocystis exedens lineage has evolved at an unusually rapid pace and its rRNA shows numerous primary and secondary structural idiosyncrasies.
Non-NASA Center↗
FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi
mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.
59 BASIC BIOLOGICAL SCIENCES↗
Dynamics of vegetation and soils of oak/saw palmetto scrub after fire: Observations from permanent transects
Ten permanent 15 m transects previously established in two oak/saw palmetto scrub stands burned in December 1986, while two transects remained unburned. Vegetation in the greater than 0.5 m and the less than 0.5 m layers on these transects was sampled at 6, 12, 18, 24, and 36 months postburn and determined structural features of the vegetation (height, percent bare ground, total cover). The vegetation data were analyzed from each sampling by height layer using detrended correspondence analysis ordination. Vegetation data for the greater than 0.5 m layer for the entire time sequence were combined and analyzed using detrended correspondence analysis ordination. Soils were sampled at 6, 12, 18, and 24 months postburn and analyzed for pH, conductivity, organic matter, exchangeable cations (Ca, Mg, K, Na), NO3-N, NH4-N, Al, available metals (Cu, Fe, Mn, Zn), and PO4-P. Shrub species recovered at different rates postfire with saw palmetto reestablishing cover greater than 0.5 m within one year, but the scrub oaks had not returned to preburn cover greater than 0.5 m in 3 years after the fire. These differences in growth rates resulted in dominance shifts after the fire with saw palmetto increasing relative to the scrub oaks. Overall changes in species richness were minor, although changes occurred in species richness by height layers due to different growth rates. Soils of well drained and poorly drained sites differed markedly. Soil responses to the fire appeared minor. Soil pH increased at 6 and 12 months postfire; calcium increased at 6 months postburn. Nitrate-nitrogen increased at 12 months postburn. Low values of conductivity, PO4-P, Mg, K, Na, and Fe at 12 months postburn may be related to heavy rainfall the preceding month. Seasonal variability in some soil parameters appeared to occur.
Schmalzer, Paul A.↗
Combustion Stability Characteristics of the Project Morpheus Liquid Oxygen / Liquid Methane Main Engine
The project Morpheus liquid oxygen (LOX) / liquid methane (LCH4) main engine is a Johnson Space Center (JSC) designed ~5,000 lbf-thrust, 4:1 throttling, pressure-fed cryogenic engine using an impinging element injector design. The engine met or exceeded all performance requirements without experiencing any in- ight failures, but the engine exhibited acoustic-coupled combustion instabilities during sea-level ground-based testing. First tangential (1T), rst radial (1R), 1T1R, and higher order modes were triggered by conditions during the Morpheus vehicle derived low chamber pressure startup sequence. The instability was never observed to initiate during mainstage, even at low power levels. Ground-interaction acoustics aggravated the instability in vehicle tests. Analysis of more than 200 hot re tests on the Morpheus vehicle and Stennis Space Center (SSC) test stand showed a relationship between ignition stability and injector/chamber pressure. The instability had the distinct characteristic of initiating at high relative injection pressure drop at low chamber pressure during the start sequence. Data analysis suggests that the two-phase density during engine start results in a high injection velocity, possibly triggering the instabilities predicted by the Hewitt stability curves. Engine ignition instability was successfully mitigated via a higher-chamber pressure start sequence (e.g., ~50% power level vs ~30%) and operational propellant start temperature limits that maintained \cold LOX" and \warm methane" at the engine inlet. The main engine successfully demonstrated 4:1 throttling without chugging during mainstage, but chug instabilities were observed during some engine shutdown sequences at low injector pressure drop, especially during vehicle landing.
Melcher, John C.↗
Habitable zones around main sequence stars
A mechanism for stabilizing climate on the earth and other earthlike planets is described, and the physical processes that define the inner and outer boundaries of the habitable zone (HZ) around the sun and main sequence stars are discussed. Physical constraints on the HZ obtained from Venus and Mars are taken into account. A 1D climate model is used to estimate the width of the HZ and the continuously habitable zone around the sun, and the analysis is extended to other main sequence stars. Whether other stars have planets and where such planets might be located with respect to the HZ is addressed. The implications of the findings for NASA's SETI project are considered.
Kasting, James F.↗
Genome Sequencing of Cladobotryum protrusum Provides Insights into the Evolution and Pathogenic Mechanisms of the Cobweb Disease Pathogen on Cultivated Mushroom
Cladobotryum protrusum is one of the mycoparasites that cause cobweb disease on cultivated edible mushrooms. However, the molecular mechanisms of evolution and pathogenesis of C. protrusum on mushrooms are largely unknown. Here, we report a high-quality genome sequence of C. protrusum using the single-molecule, real-time sequencing platform of PacBio and perform a comparative analysis with closely related fungi in the family Hypocreaceae. The C. protrusum genome, the first complete genome to be sequenced in the genus Cladobotryum, is 39.09 Mb long, with an N50 of 4.97 Mb, encoding 11,003 proteins. The phylogenomic analysis confirmed its inclusion in Hypocreaceae, with its evolutionary divergence time estimated to be ~170.1 million years ago. The genome encodes a large and diverse set of genes involved in secreted peptidases, carbohydrate-active enzymes, cytochrome P450 enzymes, pathogen–host interactions, mycotoxins, and pigments. Moreover, C. protrusum harbors arrays of genes with the potential to produce bioactive secondary metabolites and stress response-related proteins that are significant for adaptation to hostile environments. Knowledge of the genome will foster a better understanding of the biology of C. protrusum and mycoparasitism in general, as well as help with the development of effective disease control strategies to minimize economic losses from cobweb disease in cultivated edible mushrooms.
60 APPLIED LIFE SCIENCES↗
Exploration of Noncoding Sequences in Metagenomes
Environment-dependent genomic features have been defined for different metagenomes, whose genes and their associated processes are related to specific environments. Identification of ORFs and their functional categories are the most common methods for association between functional and environmental features. However, this analysis based on finding ORFs misses noncoding sequences and, therefore, some metagenome regulatory or structural information could be discarded. In this work we analyzed 23 whole metagenomes, including coding and noncoding sequences using the following sequence patterns: (G+C) content, Codon Usage (Cd), Trinucleotide Usage (Tn), and functional assignments for ORF prediction. Herein, we present evidence of a high proportion of noncoding sequences discarded in common similarity based methods in metagenomics, and the kind of relevant information present in those. We found a high density of trinucleotide repeat sequences (TRS) in noncoding sequences, with a regulatory and adaptive function for metagenome communities. We present associations between trinucleotide values and gene function, where metagenome clustering correlate with microorganism adaptations and kinds of metagenomes. We propose here that noncoding sequences have relevant information to describe metagenomes that could be considered in a whole metagenome analysis in order to improve their organization, classification protocols, and their relation with the environment.
59 BASIC BIOLOGICAL SCIENCES↗
Applications and challenges of forensic proteomics
Mass spectrometry-based proteomics has been a useful tool for addressing numerous questions in basic biology research for many years. This success, combined with the maturity of mass spectrometric instrumentation, the ever-increasing availability of protein sequence databases derived from genome sequencing, and the growing sophistication of data analysis methods, places proteomics in a position to have an important role in biological forensics. Because proteins contain information about genotype (sequence) and phenotype (expression levels), proteomics methods can both identify biological samples and characterize the conditions that produced them. In addition to serving as a valuable orthogonal method to genomic analyses, proteomics can be used in cases where nucleic acids are absent, degraded, or uninformative. Mass spectrometry provides both broad applicability and exquisite specificity, often without customized detection reagents like primers or antibodies. This review briefly introduces proteomics methods, and surveys a variety of forensic applications (including criminal justice, historical, archaeological, and national security areas). Finally, challenges and crucial areas for further research are addressed.
forensics, proteomics, mass spectrometry, protein,↗
The MAVRIC-Shift Sequence in SCALE for Radiation Transport and Shielding Calculations with Automated Variance Reduction and Parallel Computing
A new MAVRIC-Shift sequence has been implemented and tested within the SCALE Code System to provide parallel computing capabilities for radiation transport and shielding analysis with automated variance reduction. This new sequence provides the most widely used capabilities of the MAVRIC sequence and also features the highly scalable Shift Monte Carlo solver, thus enabling faster time-to-solution when run on multiple cores. This report provides a summary of the theory of variance reduction approaches in MAVRIC and the integration of Shift into the MAVRIC sequence of SCALE. Similarities and differences in methodologies between the traditional MAVRIC sequence and the new MAVRIC-Shift sequence are discussed. Validation cases are presented with models of radiation shielding experiments and verification is provided with a series of practical application cases of interest to the US Nuclear Regulatory Commission, the sponsors of this work, including spent nuclear fuel transportation and storage systems.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A new structural analysis/synthesis capability - ACCESS
The creation of an efficient automated capability for minimum weight design of structures is reported. The ACCESS 1 computer program combines finite element analysis techniques and mathematical programming algorithms using an innovative collection of approximation concepts. Design variable linking, constraint deletion techniques and approximate analysis methods are used to generate a sequence of small explicit mathematical programming problems which retain the essential features of the design problem. Organization of the finite element analysis is carefully matched to the design optimization task. The efficiency of the ACCESS 1 program is demonstrated by giving results for several example problems.
Schmit, L. A.↗
Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes
Host-associated microbial communities (microbiomes) play critical roles in human, animal, and plant health and development. However, interactions between the host, members of the microbiome, and invading pathogens are in most cases still poorly understood. Such interactions are multidimensional and can alter the taxonomic composition and/or the functional metabolic activities of the microbiome in response to disease or treatment conditions. For example, after 2 days of antibiotic treatment, the mouse gut microbiome is altered and more susceptible to invasion by the pathogen Clostridioides difficile. Studies of these multidimensional interactions have been fueled by the ability to use high-throughput sequencing of phylogenetic marker genes to profile microbial community composition and shotgun metagenomics to profile functional potential. However, many protein-coding genes predicted from metagenomes are not necessarily expressed under a given condition, and thus, it is difficult to assess the activities and functional interactions in microbial communities based on DNA sequencing data alone. The physiological and pathological processes expressed in these communities under specific conditions are better reflected by the abundances of transcripts or proteins. In this Pearl, we provide a brief introduction to metaproteomics, which is a tool for the large-scale analysis of proteins in microbiomes that allows researchers to address a diversity of questions related to functions and interactions in microbiomes. The term “metaproteomics” was first used in 2004 for “the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time”, and since then, a large array of metaproteomics approaches have been developed. Our objective in this Pearl is to highlight what we feel are 5 essential elements to be considered for a metaproteomics research campaign and to introduce nonexpert readers to the topic without going into too much technical detail.
59 BASIC BIOLOGICAL SCIENCES↗
Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network
Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
59 BASIC BIOLOGICAL SCIENCES↗
The parallelism motifs of genomic data analysis
Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.
59 BASIC BIOLOGICAL SCIENCES↗
Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing
Switchgrass ( Panicum virgatum L.) is an important bioenergy crop widely used for lignocellulosic research. While extensive transcriptomic analyses have been conducted on this species using short read-based sequencing techniques, very little has been reliably derived regarding alternatively spliced (AS) transcripts. Here, we present an analysis of transcriptomes of six switchgrass tissue types pooled together, sequenced using Pacific Biosciences (PacBio) single-molecular long-read technology. Our analysis identified 105,419 unique transcripts covering 43,570 known genes and 8795 previously unknown genes. 45,168 are novel transcripts of known genes. A total of 60,096 AS transcripts are identified, 45,628 being novel. We have also predicted 1549 transcripts of genes involved in cell wall construction and remodeling, 639 being novel transcripts of known cell wall genes. Most of the predicted transcripts are validated against Illumina-based short reads. Specifically, 96% of the splice junction sites in all the unique transcripts are validated by at least five Illumina reads. Comparisons between genes derived from our identified transcripts and the current genome annotation revealed that among the gene set predicted by both analyses, 16,640 have different exon-intron structures. Overall, substantial amount of new information is derived from the PacBio RNA data regarding both the transcriptome and the genome of switchgrass.
09 BIOMASS FUELS↗
Limited genetic diversity across pathogen populations responsible for the global emergence of boxwood blight identified using SSR s
Boxwood blight is an emerging disease of ornamental as well as native boxwood. The disease became widely established in Europe at the beginning of the 21st century, prior to its more recent discovery in North America and Asia. Two sister‐species of fungi cause the disease, Calonectria pseudonaviculata (Cps) and C. henricotiae (Che). Prior efforts to quantify intraspecific genetic polymorphisms of Cps and Che have yielded little information, limiting the ability to understand the evolution and migration of these pathogens. This study describes the development and implementation of simple sequence repeat ( SSR ) markers to analyse genetic diversity from a global collection of Cps and Che isolates, representing major blight outbreaks since the disease was first identified in the UK in the late 1990s. Analysis of the Cps CB 002 genome sequence identified 180 single copy SSR loci using stringent search criteria, 11 of which were polymorphic and used to screen a global sample of 306 isolates. Fourteen multilocus genotypes of Cps and two multilocus genotypes of Che were identified. Twelve of the 14 Cps genotypes differed from each other by a single allele. The most common Cps genotype was found on all continents where boxwood blight is confirmed. Based on measurement of linkage disequilibrium, Cps showed no evidence of sexual recombination. Further in silico analysis identified 1594 SSR s using relaxed SSR definition criteria. Comparison of these SSR ‐containing loci with Cps and Che genome sequences representing three different genotypes demonstrated that single nucleotide polymorphisms might serve as informative genetic markers for future studies.
LeBlanc, N.↗
Predicting the chemical space of fungal polyketides by phylogeny-based bioinformatics analysis of polyketide synthase-nonribosomal peptide synthetase and its modification enzymes
Fungal polyketide synthase (PKS)–nonribosomal peptide synthetase (NRPS) hybrids are key enzymes for synthesizing structurally diverse hybrid natural products (NPs) with characteristic biological activities. Predicting their chemical space is of particular importance in the field of natural product chemistry. However, the unexplored programming rule of the PKS module has prevented prediction of its chemical structure based on amino acid sequences. Here, we conducted a phylogenetic analysis of 884 PKS–NRPS hybrids and a modification enzyme analysis of the corresponding biosynthetic gene cluster, revealing a hidden relationship between its genealogy and core structures. This unexpected result allowed us to predict 18 biosynthetic gene cluster (BGC) groups producing known carbon skeletons (number of BGCs; 489) and 11 uncharacterized BGC groups (171). The limited number of carbon skeletons suggests that fungi tend to select PK skeletons for survival during their evolution. The possible involvement of a horizontal gene transfer event leading to the diverse distribution of PKS–NRPS genes among fungal species is also proposed. This study provides insight into the chemical space of fungal PKs and the distribution of their biosynthetic gene clusters.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A sublaminate analysis method for predicting disbond and delamination loads in composite structures
A method is proposed for assessing the forces that can delaminate composite laminates and bonded structures. The approach employs a higher-order plate theory to represent portions of the laminate. The ply properties are integrated through the thickness in a manner that is consistent with the displacement assumptions in the plate theory, thus providing for accurate representation of the stacking sequence effects. In addition to stress analysis, the method also provides the strain energy release rate for the growth of existing delaminations. The analysis has been incorporated into a computer code, TTSS (through thickness stretching and shear). Application examples, including a double cantilever beam and a curved laminate, are examined.
Flanagan, G.↗