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A lymphotropic papovavirus (LPV) archetypal regulatory region was amplified from DNA from the blood of an immunocompromised rhesus monkey. We believe this is the first nonserological evidence of LPV infection in rhesus monkeys.
The dinitrogenase reductase gene ( nifH ) is the most widely established molecular marker for the study of nitrogen-fixing prokaryotes in nature. A large number of PCR primer sets have been developed for nifH amplification, and the effective deployment of these approaches should be guided by a rapid, easy-to-use analysis protocol. Bioinformatic analysis of marker gene sequences also requires considerable expertise. In this study, we advance the state of the art for nifH analysis by evaluating nifH primer set performance, developing an improved amplicon sequencing workflow, and implementing a user-friendly bioinformatics pipeline. Furthermore, the developed amplicon sequencing workflow is a three-stage PCR-based approach that uses established technologies for incorporating sample-specific barcode sequences and sequencing adapters. Based on our primer evaluation, we recommend the Ando primer set be used with a modified annealing temperature of 58°C, as this approach captured the largest diversity of nifH templates, including paralog cluster IV/V sequences. To improve nifH sequence analysis, we developed a computational pipeline which infers taxonomy and optionally filters out paralog sequences. In addition, we employed an empirical model to derive optimal operational taxonomic unit (OTU) cutoffs for the nifH gene at the species, genus, and family levels. A comprehensive workflow script named TaxADivA (TAXonomy Assignment and DIVersity Assessment) is provided to ease processing and analysis of nifH amplicons. Our approach is then validated through characterization of diazotroph communities across environmental gradients in beach sands impacted by the Deepwater Horizon oil spill in the Gulf of Mexico, in a peat moss-dominated wetland, and in various plant compartments of a sugarcane field. IMPORTANCE: Nitrogen availability often limits ecosystem productivity, and nitrogen fixation, exclusive to prokaryotes, comprises a major source of nitrogen input that sustains food webs. The nifH gene, which codes for the iron protein of the nitrogenase enzyme, is the most widely established molecular marker for the study of nitrogen-fixing microorganisms (diazotrophs) in nature. In this study, a flexible sequencing/analysis pipeline, named TaxADivA, was developed for nifH amplicons produced by Illumina paired-end sequencing, and it enables an inference of taxonomy, performs clustering, and produces output in formats that may be used by programs that facilitate data exploration and analysis. Diazotroph diversity and community composition are linked to ecosystem functioning, and our results advance the phylogenetic characterization of diazotroph communities by providing empirically derived nifH similarity cutoffs for species, genus, and family levels. Thus, the utility of our pipeline is validated for diazotroph communities in a variety of ecosystems, including contaminated beach sands, peatland ecosystems, living plant tissues, and rhizosphere soil.
Pontibacter roseus is a member of genus Pontibacter family Cytophagaceae, class Cytophagia. While the type species of the genus Pontibacter actiniarum was isolated in 2005 from a marine environment, subsequent species of the same genus have been found in different types of habitats ranging from seawater, sediment, desert soil, rhizosphere, contaminated sites, solar saltern and muddy water. Here we describe the features of Pontibacter roseus strain SRC-1 T along with its complete genome sequence and annotation from a culture of DSM 17521 T . In conclusion, the 4,581,480 bp long draft genome consists of 12 scaffolds with 4,003 protein-coding and 50 RNA genes and is a part of Genomic Encyclopedia of Type Strains: KMG-I project.
The Hashemite Kingdom of Jordan remains an understudied country for next generation sequencing analysis of SARS-CoV-2 genomes collected during the 2019 pandemic. Here we provide 131 additional reference genomes collected between 2020–2023 from SARS-CoV-2-positive patients across Jordan. Phylogenetic analysis supports existing pandemic narratives of changing clade dominance over time and adds genomes in novel Jordanian locations and timepoints to make Jordan SARS-CoV-2 databases more comprehensive. Samples from the less-sequenced cities of Ajloun, Jaresh, Karak, and Madaba identified previously unreported lineages while Amman, Irbid, and Zarqa have existing sequencing efforts bolstered. Despite many incomplete patient records and a relatively small sample size, we observe interesting symptom patterns that support existing global and Jordanian pandemic narratives. We note how in-country COVID-19 pandemic genomic studies showcase Jordan’s efforts to expand next generation sequencing capabilities, especially through the leveraging of EDGE COVID-19, a bioinformatics platform for performing rapid, batched analysis of SARS-CoV-2 sequencing that streamlines sample processing prepared from a network of hospital locations.
Enterobacter sp. IIT-BT 08 belongs to Phylum: Proteobacteria, Class: Gammaproteobacteria, Order: Enterobacteriales, Family: Enterobacteriaceae. The organism was isolated from the leaves of a local plant near the Kharagpur railway station, Kharagpur, West Bengal, India. It has been extensively studied for fermentative hydrogen production because of its high hydrogen yield. For further enhancement of hydrogen production by strain development, complete genome sequence analysis was carried out. Sequence analysis revealed that the genome was linear, 4.67 Mbp long and had a GC content of 56.01%. The genome properties encode 4,393 protein-coding and 179 RNA genes. Additionally, a putative pathway of hydrogen production was suggested based on the presence of formate hydrogen lyase complex and other related genes identified in the genome. Thus, in the present study we describe the specific properties of the organism and the generation, annotation and analysis of its genome sequence as well as discuss the putative pathway of hydrogen production by this organism.
Motivation: Current advances in DNA synthesis, cloning and sequencing technologies afford high-throughput implementation of artificial sequences into living cells. However, flexible computational tools for multi-objective sequence design are lacking, limiting the potential of these technologies. Results: We developed DNA-Tailor (D-Tailor), a fully extendable software framework, for property-based design of synthetic DNA sequences. D-Tailor permits the seamless integration of multiple sequence analysis tools into a generic Monte Carlo simulation that evolves sequences toward any combination of rationally defined properties. As proof of principle, we show that D-Tailor is capable of designing sequence libraries comprising all possible combinations among three different sequence properties influencing translation efficiency in Escherichia coli. The capacity to design artificial sequences that systematically sample any given parameter space should support the implementation of more rigorous experimental designs.
A new bacterial species belonging to the genus Shewanella is described on the basis of phenotypic characterization and sequence analysis of its 16S rRNA-encoding and gyrase B (gyrB) genes. This organism, isolated from shallow-water marine sediments derived from the Amazon River delta, is a Gram-negative, motile, polarly flagellated, facultatively anaerobic, rod-shaped eubacterium and has a G&C content of 51.7 mol%. Strain SB2BT is exceptionally active in the anaerobic reduction of iron, manganese and sulfur compounds. SB2BT grows optimally at 35 degrees C, with 1-3% NaCl and over a pH range of 7-8. Analysis of the 16S rDNA sequence revealed a clear affiliation between strain SB2BT and members of the gamma subclass of the class Proteobacteria. High similarity values were found with certain members of the genus Shewanella, especially with Shewanella putrefaciens, and this was supported by cellular fatty acid profiles and phenotypic characterization. DNA-DNA hybridization between strain SB2BT and its phylogenetically closest relatives revealed low similarity values (24.6-42.7%) which indicated species status for strain SB2BT. That SB2BT represents a distinct bacterial species within the genus Shewanella is also supported by gyrB sequence analysis. Considering the source of the isolate, the name Shewanella amazonensis sp. nov. is proposed and strain SB2BT (= ATCC 700329T) is designated as the type strain.
DNA sequences are analyzed using latent semantic analysis. A set of nucleotide sequences is received in which the set has a first number of sequences. A set of basis vectors is determined, in which the set has a second number of basis vectors, the second number being smaller than the first number. Each basis vector represents a specific combination of predetermined nucleotide segments. For each of the nucleotide sequences, an approximate representation of the nucleotide sequence is determined based on a combination of the basis vectors. For each pair of nucleotide sequences, a distance between the pair of nucleotide sequences is determined according the distance between the approximate representation of the pair of nucleotide sequences. The set of nucleotide sequences are classified based on the distances between the pairs of nucleotide sequences.
An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.
Background: In addition to gene identification and annotation, repetitive sequence analysis has become an integral part of genome sequencing projects. Identification of repeats is important not only because it improves gene prediction, but also because of the role that repetitive sequences play in determining the structure and evolution of genes and genomes. Several methods using different repeat-finding strategies are available for whole-genome repeat sequence analysis. Four independent approaches were used to identify and characterize the repetitive fraction of the Mycosphaerella graminicola (synonym Zymoseptoria tritici) genome. This ascomycete fungus is a wheat pathogen and its finished genome comprises 21 chromosomes, eight of which can be lost with no obvious effects on fitness so are dispensable. Results: Using a combination of four repeat-finding methods, at least 17% of the M. graminicola genome was estimated to be repetitive. Class I transposable elements, that amplify via an RNA intermediate, account for about 70% of the total repetitive content in the M. graminicola genome. The dispensable chromosomes had a higher percentage of repetitive elements as compared to the core chromosomes. Distribution of repeats across the chromosomes also varied, with at least six chromosomes showing a non-random distribution of repetitive elements. Repeat families showed transition mutations and a CpA → TpA dinucleotide bias, indicating the presence of a repeat-induced point mutation (RIP)-like mechanism in M. graminicola. One gene family and two repeat families specific to subtelomeres also were identified in the M. graminicola genome. A total of 78 putative clusters of nested elements was found in the M. graminicola genome. Several genes with putative roles in pathogenicity were found associated with these nested repeat clusters. This analysis of the transposable element content in the finished M. graminicola genome resulted in a thorough and highly curated database of repetitive sequences. Conclusions: This comprehensive analysis will serve as a scaffold to address additional biological questions regarding the origin and fate of transposable elements in fungi. Future analyses of the distribution of repetitive sequences in M. graminicola also will be able to provide insights into the association of repeats with genes and their potential role in gene and genome evolution.
Ribosomal ribonucleic acids /RNA/ terminal nucleotide sequences analysis based on hydroxyl group enzymatic phosphorylation
Despite their small size, unicellular eukaryotes have complex genomes with a high degree of plasticity that allow them to adapt quickly to environmental changes. Unicellular eukaryotes live with prokaryotes and higher eukaryotes, frequently in symbiotic or parasitic niches. To this day their contribution to the dynamics of the environmental communities remains to be understood. Unfortunately, the vast majority of eukaryotic microorganisms are either uncultured or unculturable, making genome sequencing impossible using traditional approaches. We have developed an approach to isolate unicellular eukaryotes of interest from environmental samples, and to sequence and analyze their genomes and transcriptomes. We have tested our methods with six species: an uncharacterized protist from cellulose-enriched compost identified as Platyophrya, a close relative of P. vorax; the fungus Metschnikowia bicuspidate, a parasite of water flea Daphnia; the mycoparasitic fungi Piptocephalis cylindrospora, a parasite of Cokeromyces and Mucor; Caulochytrium protosteloides, a parasite of Sordaria; Rozella allomycis, a parasite of the water mold Allomyces; and the microalgae Chlamydomonas reinhardtii. Here, we present the four components of our approach: pre-sequencing methods, sequence analysis for single cell genome assembly, sequence analysis of single cell transcriptomes, and genome annotation. This technology has the potential to uncover the complexity of single cell eukaryotes and their role in the environmental samples.
Background: Next-generation sequencing (NGS) technologies have provided researchers with vast possibilities in various biological and biomedical research areas. Efficient data mining strategies are in high demand for large scale comparative and evolutional studies to be performed on the large amounts of data derived from NGS projects. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Methods: We report a novel procedure to analyse NGS data using topic modeling. It consists of four major procedures: NGS data retrieval, preprocessing, topic modeling, and data mining using Latent Dirichlet Allocation (LDA) topic outputs. The NGS data set of the Salmonella enterica strains were used as a case study to show the workflow of this procedure. The perplexity measurement of the topic numbers and the convergence efficiencies of Gibbs sampling were calculated and discussed for achieving the best result from the proposed procedure. Results: The output topics by LDA algorithms could be treated as features of Salmonella strains to accurately describe the genetic diversity of fliC gene in various serotypes. The results of a two-way hierarchical clustering and data matrix analysis on LDA-derived matrices successfully classified Salmonella serotypes based on the NGS data. The implementation of topic modeling in NGS data analysis procedure provides a new way to elucidate genetic information from NGS data, and identify the gene-phenotype relationships and biomarkers, especially in the era of biological and medical big data. Conclusion: The implementation of topic modeling in NGS data analysis provides a new way to elucidate genetic information from NGS data, and identify the gene-phenotype relationships and biomarkers, especially in the era of biological and medical big data.
Bioinformatics is currently faced with very large-scale data sets that lead to computational jobs, especially sequence similarity searches, that can take absurdly long times to run. For example, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST and BLAST+) suite, which is by far the most widely used tool for rapid similarity searching among nucleic acid or amino acid sequences, is highly central processing unit (CPU) intensive. While the BLAST suite of programs perform searches very rapidly, they have the potential to be accelerated. In recent years, distributed computing environments have become more widely accessible and used due to the increasing availability of high-performance computing (HPC) systems. Therefore, simple solutions for data parallelization are needed to expedite BLAST and other sequence analysis tools. However, existing software for parallel sequence similarity searches often requires extensive computational experience and skill on the part of the user. In order to accelerate BLAST and other sequence analysis tools, Divide and Conquer BLAST (DCBLAST) was developed to perform NCBI BLAST searches within a cluster, grid, or HPC environment by using a query sequence distribution approach. Scaling from one (1) to 256 CPU cores resulted in significant improvements in processing speed. Thus, DCBLAST dramatically accelerates the execution of BLAST searches using a simple, accessible, robust, and parallel approach. DCBLAST works across multiple nodes automatically and it overcomes the speed limitation of single-node BLAST programs. DCBLAST can be used on any HPC system, can take advantage of hundreds of nodes, and has no output limitations. Thus, this freely available tool simplifies distributed computation pipelines to facilitate the rapid discovery of sequence similarities between very large data sets.
Various technologies pertaining to computer-executable instruction sequence forensics are described herein. In a general embodiment, an application development framework supports a function library that includes a plurality of recording functions. Calls to these functions are inserted into source code or bytecode of the computer-executable instruction sequence. The source code is then compiled, resulting in formation of instrumented machine code of the computer-executable instruction sequence. Alternately, the runtime environment interprets instrumented bytecode for the instruction sequence. A processor executes the machine code, and the called functions cause the processor to generate forensic data pertaining to portions of the computer-executable instruction sequence that correspond to locations in the source code where the calls were inserted. An execution instance of the computer-executable instruction sequence is visualized based upon the forensic data.
In three years of observations since the beginning of nominal science operations in 2008 August, the Large Area Telescope (LAT) on board the Fermi Gamma-Ray Space Telescope has observed high-energy (∼> 20 MeV) γ-ray emission from 35 gamma-ray bursts (GRBs). Among these, 28 GRBs have been detected above 100 MeV and 7 GRBs above ∼20 MeV. The first Fermi-LAT catalog of GRBs is a compilation of these detections and provides a systematic study of high-energy emission from GRBs for the first time. To generate the catalog, we examined 733 GRBs detected by the Gamma-Ray Burst Monitor (GBM) on Fermi and processed each of them using the same analysis sequence. Details of the methodology followed by the LAT collaboration for the GRB analysis are provided. We summarize the temporal and spectral properties of the LAT-detected GRBs. We also discuss characteristics of LAT-detected emission such as its delayed onset and longer duration compared with emission detected by the GBM, its power-law temporal decay at late times, and the fact that it is dominated by a power-law spectral component that appears in addition to the usual Band model.
Bacillus anthracis, the causative agent of the human disease anthrax, Bacillus cereus, a food-borne pathogen capable of causing human illness, and Bacillus thuringiensis, a well-characterized insecticidal toxin producer, all cluster together within a very tight clade (B. cereus group) phylogenetically and are indistinguishable from one another via 16S rDNA sequence analysis. As new pathogens are continually emerging, it is imperative to devise a system capable of rapidly and accurately differentiating closely related, yet phenotypically distinct species. Although the gyrB gene has proven useful in discriminating closely related species, its sequence analysis has not yet been validated by DNA:DNA hybridization, the taxonomically accepted "gold standard". We phylogenetically characterized the gyrB sequences of various species and serotypes encompassed in the "B. cereus group," including lab strains and environmental isolates. Results were compared to those obtained from analyses of phenotypic characteristics, 16S rDNA sequence, DNA:DNA hybridization, and virulence factors. The gyrB gene proved more highly differential than 16S, while, at the same time, as analytical as costly and laborious DNA:DNA hybridization techniques in differentiating species within the B. cereus group.
Emergence of replicable genetic molecules was one of the marking points in the origin of life, evolution of which can be conceptualized as a walk through the space of all possible sequences. A theoretical concept of fitness landscape helps to understand evolutionary processes through assigning a value of fitness to each genotype. Then, evolution of a phenotype is viewed as a series of consecutive, single-point mutations. Natural selection biases evolution toward peaks of high fitness and away from valleys of low fitness. whereas neutral drift occurs in the sequence space without direction as mutations are introduced at random. Large networks of neutral or near-neutral mutations on a fitness landscape, especially for sufficiently long genomes, are possible or even inevitable. Their detection in experiments, however, has been elusive. Although a few near-neutral evolutionary pathways have been found, recent experimental evidence indicates landscapes consist of largely isolated islands. The generality of these results, however, is not clear, as the genome length or the fraction of functional molecules in the genotypic space might have been insufficient for the emergence of large, neutral networks. Thorough investigation on the structure of the fitness landscape is essential to understand the mechanisms of evolution of early genomes. RNA molecules are commonly assumed to play the pivotal role in the origin of genetic systems. They are widely believed to be early, if not the earliest, genetic and catalytic molecules, with abundant biochemical activities as aptamers and ribozymes, i.e. RNA molecules capable, respectively, to bind small molecules or catalyze chemical reactions. Here, we present results of our recent studies on the structure of the sequence space of RNA ligase ribozymes selected through in vitro evolution. Several hundred thousands of sequences active to a different degree were obtained by way of deep sequencing. Analysis of these sequences revealed several large clusters defined such that every sequence in a cluster can be reached from any other sequence in the same cluster through a series of single point mutations. Sequences in a single cluster appear to adopt more than one secondary structure. The mechanism of refolding within a single cluster was examined. To shed light on possible evolutionary paths in the space of ribozymes, the connectivity between clusters was investigated. The effect of length of RNA molecules on the structure of the fitness landscape and possible evolutionary paths was examined by way of comparing functional sequences of 20 and 80 nucleobases in length. It was found that sequences of different lengths shared secondary structure motifs that were presumed responsible for catalytic activity, with increasing complexity and global structural rearrangements emerging in longer molecules.