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  • Computational Methods  (62)
  • Biotechnology & Synthetic Biology  (41)
  • Oxford University Press  (103)
  • 1
    Publication Date: 2017-01-10
    Description: RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA–protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html .
    Keywords: Computational Methods
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  • 2
    Publication Date: 2016-06-21
    Description: The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P -values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
    Keywords: Computational Methods
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  • 3
    Publication Date: 2016-05-12
    Description: In this study, we isolated 15 endophytic fungi from five Sudanese medicinal plants. Each fungal endophytic strain was identified by sequencing of internal transcribed spacer (ITS) regions of rDNA. Ethyl acetate extracts were prepared from each endophyte cultivated in vitro and tested for their respective antibacterial activities and antiproliferative activities against human cancer cells. Antibacterial screening was carried out against two bacterial strains: Gram-negative Escherichia coli and Gram-positive methicillin-resistant Staphylococcus aureus , by the broth dilution method. Cell viability was evaluated by the MTT procedure after exposure of MCF7 breast cancer cells and HT29 or HCT116 human colon adenocarcinoma cells to each endophytic extract. Of interest, Byssochlamys spectabilis isolated from Euphorbia prostata showed cytotoxicity (IC 50 = 1.51 ± 0.2 μg mL –1 ) against MCF7 cells, but had a low effect against HT29 or HCT116 cells (IC 50 〉 20 μg mL –1 ). Cladosporium cladosporioides 2, isolated from Vernonia amygdalina leaves, showed antiproliferative activities against MCF7 cells (IC 50 = 10.5 ± 1.5 μg mL –1 ) only. On the other hand, B. spectabilis and Alternaria sp. extract had antibacterial activities against the S. aureus strain. The findings of this work revealed that endophytic fungi associated with medicinal plants from Sudan could be considered as an attractive source of new therapeutic compounds.
    Keywords: Biotechnology & Synthetic Biology
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  • 4
    Publication Date: 2016-07-09
    Description: Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine .
    Keywords: Computational Methods
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  • 5
    Publication Date: 2016-07-28
    Description: CCCTC-binding factor (CTCF) is a multi-functional protein that is assigned various, even contradictory roles in the genome. High-throughput sequencing-based technologies such as ChIP-seq and Hi-C provided us the opportunity to assess the multivalent functions of CTCF in the human genome. The location of CTCF-binding sites with respect to genomic features provides insights into the possible roles of this protein. Here we present the first genome-wide survey and characterization of three important functions of CTCF: enhancer insulator, chromatin barrier and enhancer linker. We developed a novel computational framework to discover the multivalent functions of CTCF based on chromatin state and three-dimensional chromatin architecture. We applied our method to five human cell lines and identified ~46 000 non-redundant CTCF sites related to the three functions. Disparate effects of these functions on gene expression were found and distinct genomic features of these CTCF sites were characterized in GM12878 cells. Finally, we investigated the cell-type specificities of CTCF sites related to these functions across five cell types. Our study provides new insights into the multivalent functions of CTCF in the human genome.
    Keywords: Computational Methods
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  • 6
    Publication Date: 2016-04-08
    Description: Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modelling (using the Rosetta protein modelling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism's proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR's predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly, we demonstrate VIPUR's ability to highlight candidate variants associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.
    Keywords: Computational Methods
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  • 7
    Publication Date: 2016-04-08
    Description: Resveratrol is a well-known triphenolic natural product present in red wine. For its contribution to human health, the demand for resveratrol as a food and nutrition supplement has increased significantly. In recent years, the rapid development of synthetic biology has promoted extensive work to increase the production of resveratrol in microbes. However, supplementation of expensive phenylpropanoic precursors was required in current engineered strains. Here, we first utilized the site-specific integration strategy to produce resveratrol in Escherichia coli . The genes tal , 4cl and sts were site-specific integrated into the loci of genes tyrR and trpED in the chromosome of E. coli BW25113 (DE3). The final strain was capable of producing 4.612 mg L –1 of resveratrol from glucose.
    Keywords: Biotechnology & Synthetic Biology
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  • 8
    Publication Date: 2016-04-08
    Description: While extensively studied in several model organisms, the role of small, non-coding RNAs in the stress response remains largely unexplored in Clostridium organisms. About 100 years after the first industrial Acetone–Butanol–Ethanol fermentation process, based on the Weizmann Clostridium acetobutylicum strain, strain tolerance to butanol remains a crucial factor limiting the economics of the process. Several studies have examined the response of this organism to metabolite stress, and several genes have been engaged to impart enhanced tolerance, but no sRNAs have yet been directly engaged in this task. We show that the two stress-responsive sRNAs, 6S and tmRNA, upon overexpression impart tolerance to butanol as assessed by viability assays under process-relevant conditions. 6S overexpression enhances cell densities as well as butanol titres. We discuss the likely mechanisms that these two sRNAs might engage in this tolerance phenotype. Our data support the continued exploration of sRNAs as a basis for engineering enhanced tolerance and enhanced solvent production, especially because sRNA-based strategies impose a minimal metabolic burden on the cells.
    Keywords: Biotechnology & Synthetic Biology
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  • 9
    Publication Date: 2016-07-02
    Description: Ten indole alkaloids were obtained from the marine sponge-associated fungus Neosartorya siamensis KUFA 0017. We studied the antimicrobial properties of these and of three other compounds previously isolated from the soil fungus N. siamensis KUFC 6349. Only neofiscalin A showed antimicrobial activity against Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecalis (VRE); with a minimum inhibitory concentration (MIC) of 8 μg mL –1 against both strains. Another compound, fiscalin C, presented synergistic activity against MRSA when combined with oxacillin, although alone showed no antibacterial effect. Moreover, neofiscalin A, when present at sub-MICs, hampered the ability of both MRSA and VRE strains to form a biofilm. Additionally, the biofilm inhibitory concentration values of neofiscalin A against the MRSA and VRE isolates were 96 and 80 μg mL –1 , respectively. At a concentration of 200 μg mL –1 , neofiscalin A was able to reduce the metabolic activity of the biofilms by ~50%. One important fact is that our results also showed that neofiscalin A had no cytotoxicity against a human brain capillary endothelial cell line.
    Keywords: Biotechnology & Synthetic Biology
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  • 10
    Publication Date: 2016-07-02
    Description: During unconventional protein secretion (UPS), proteins do not pass through the classical endoplasmic reticulum (ER)–Golgi-dependent pathway, but are transported to the cell membrane via alternative routes. One type of UPS is dependent on several autophagy-related (Atg) proteins in yeast and mammalian cells, but mechanisms for unconventional secretion are largely unknown for filamentous fungi. In this study, we investigated whether the autophagy machinery is used for UPS in the filamentous fungus Aspergillus niger . An aspartic protease, which we called PepN, was identified as being likely to be secreted unconventionally, as this protein is highly abundant in culture filtrates during carbon starvation while it lacks a conventional N-terminal secretion sequence. We analysed the presence of PepN in the culture filtrates of carbon starved wild-type, atg1 and atg8 deletion mutant strains by Western blot analysis and by secretome analysis using nanoLC-ESI-MS/MS (wild-type and atg8 deletion mutant). Besides the presence of carbohydrate-active enzymes and other types of proteases, PepN was abundantly found in culture filtrates of both wild-type and atg deletion strains, indicating that the secretion of PepN is independent of the autophagy machinery in A. niger and hence most likely occurs via a different mechanism.
    Keywords: Biotechnology & Synthetic Biology
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  • 11
    Publication Date: 2016-08-27
    Description: Actin-like MreB paralogs play important roles in cell shape maintenance, cell wall synthesis and the regulation of the D,L-endopeptidases, CwlO and LytE. The gram-positive bacteria, Bacillus amyloliquefaciens LL3, is a poly--glutamic acid (-PGA) producing strain that contains three MreB paralogs: MreB, Mbl and MreBH. In B. amyloliquefaciens , CwlO and LytE can degrade -PGA. In this study, we aimed to test the hypothesis that modulating transcript levels of MreB paralogs would alter the synthesis and degradation of -PGA. The results showed that overexpression or inhibition of MreB, Mbl or MreBH had distinct effects on cell morphology and the molecular weight of the -PGA products. In fermentation medium, cells of mreB inhibition mutant were 50.2% longer than LL3, and the -PGA titer increased by 55.7%. However, changing the expression level of mbl showed only slight effects on the morphology, -PGA molecular weight and titer. In the mreBH inhibition mutant, -PGA production and its molecular weight increased by 56.7% and 19.4%, respectively. These results confirmed our hypothesis that suppressing the expression of MreB paralogs might reduce -PGA degradation, and that improving the cell size could strengthen -PGA synthesis. This is the first report of enhanced -PGA production via suppression of actin-like MreB paralogs.
    Keywords: Biotechnology & Synthetic Biology
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  • 12
    Publication Date: 2016-06-08
    Description: Microbial production of acetone and butanol was one of the first large-scale industrial fermentation processes of global importance. During the first part of the 20th century, it was indeed the second largest fermentation process, superseded in importance only by the ethanol fermentation. After a rapid decline after the 1950s, acetone-butanol-ethanol (ABE) fermentation has recently gained renewed interest in the context of biorefinery approaches for the production of fuels and chemicals from renewable resources. The availability of new methods and knowledge opens many new doors for industrial microbiology, and a comprehensive view on this process is worthwhile due to the new interest. This thematic issue of FEMS Microbiology Letters, dedicated to the 100th anniversary of the first industrial exploitation of Chaim Weizmann's ABE fermentation process, covers the main aspects of old and new developments, thereby outlining a model development in biotechnology. All major aspects of industrial microbiology are exemplified by this single process. This includes new technologies, such as the latest developments in metabolic engineering, the exploitation of biodiversity and discoveries of new regulatory systems such as for microbial stress tolerance, as well as technological aspects, such as bio- and down-stream processing.
    Keywords: Biotechnology & Synthetic Biology
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  • 13
    Publication Date: 2016-06-02
    Description: Food-grade lactic acid bacteria, such as lactobacilli, represent good candidates for the development of mucosal vectors. Indeed, they are generally recognized as safe microorganisms and some strains display beneficial effects (probiotics). In this study, we described a new lactobacilli in vivo expression (LIVE) system for the production and delivery of therapeutic molecules at mucosal surfaces. The versatility and functionality of this system was successfully validated in several lactobacilli species; furthermore, we assessed in vivo LIVE system in two different mouse models of human pathologies: (i) a model of therapy against intestinal inflammation (inflammatory bowel diseases) and (ii) a model of vaccination against dental caries. We demonstrated that Lactobacillus gasseri expressing the anti-inflammatory cytokine IL-10 under LIVE system efficiently delivered the recombinant protein at mucosal surfaces and display anti-inflammatory effects. In the vaccination model against caries, LIVE system allowed the heterologous expression of Streptococcus mutans antigen GbpB by L. gasseri , leading to a stimulation of the host immune response.
    Keywords: Biotechnology & Synthetic Biology
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  • 14
    Publication Date: 2016-06-02
    Description: The microbial fermentation process is one of the sustainable and environment-friendly ways to produce 1-butanol and other bio-based chemicals. The success of the fermentation process greatly relies on the choice of bioreactors and the separation methods. In this review, the history and the performance of bioreactors for the acetone–butanol–ethanol (ABE) fermentation is discussed. The subject is then focused on in situ product recovery (ISPR) techniques, particularly for the integrated extraction-gas stripping. The usefulness of this promising hybrid ISPR device is acknowledged by its incorporation with batch, fed-batch and continuous processes to improve the performance of ABE fermentation.
    Keywords: Biotechnology & Synthetic Biology
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  • 15
    Publication Date: 2016-06-03
    Description: The sequential chain of interactions altering the binary state of a biomolecule represents the ‘information flow’ within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein–protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes—network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code ( http://www.NetDecoder.org ) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.
    Keywords: Computational Methods
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  • 16
    Publication Date: 2016-01-29
    Description: Anaerobic Clostridium spp. is an important bioproduction microbial genus that can produce solvents and utilize a broad spectrum of substrates including cellulose and syngas. Genome-scale metabolic (GSM) models are increasingly being put forth for various clostridial strains to explore their respective metabolic capabilities and suitability for various bioconversions. In this study, we have selected representative GSM models for six different clostridia ( Clostridium acetobutylicum , C. beijerinckii , C. butyricum , C. cellulolyticum , C. ljungdahlii and C. thermocellum ) and performed a detailed model comparison contrasting their metabolic repertoire. We also discuss various applications of these GSM models to guide metabolic engineering interventions as well as assessing cellular physiology.
    Keywords: Biotechnology & Synthetic Biology
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  • 17
    Publication Date: 2016-03-02
    Description: Biobutanol is a next-generation liquid biofuel with properties akin to those of gasoline. There is a widespread effort to commercialize biobutanol production from agricultural residues, such as corn stover, which do not compete with human and animal foods. This pursuit is backed by extensive government mandates to expand alternative energy sources. This review provides an overview of research on biobutanol production using corn stover feedstock. Structural composition, pretreatment, sugar yield (following pretreatment and hydrolysis) and generation of lignocellulose-derived microbial inhibitory compounds (LDMICs) from corn stover are discussed. The review also discusses different Clostridium species and strains employed for biobutanol production from corn stover-derived sugars with respect to solvent yields, tolerance to LDMICs and in situ solvent recovery (integrated fermentation). Further, the economics of cellulosic biobutanol production are highlighted and compared to corn starch-derived ethanol and gasoline. As discussed herein, the economic competitiveness of biobutanol production from corn stover largely depends on feedstock processing and fermentation process design.
    Keywords: Biotechnology & Synthetic Biology
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  • 18
    Publication Date: 2016-02-20
    Description: Biological production in heterologous hosts is of interest for the production of the C4 alcohol (butanol) and other chemicals. However, some hurdles need to be overcome in order to achieve an economically viable process; these include avoiding the consumption of butanol and maintaining tolerance to this solvent during production. Pseudomonas putida is a potential host for solvent production; in order to further adapt P. putida to this role, we generated mini-Tn 5 mutant libraries in strain BIRD-1 that do not consume butanol. We analyzed the insertion site of the mini-Tn 5 in a mutant that was deficient in assimilation of butanol using arbitrary PCR followed by Sanger sequencing and found that the transposon was inserted in the malate synthase B gene. Here, we show that in a second round of mutagenesis a double mutant unable to take up butanol had an insertion in a gene coding for a multisensor hybrid histidine kinase. The genetic context of the histidine kinase sensor revealed the presence of a set of genes potentially involved in butanol assimilation; qRT-PCR analysis showed induction of this set of genes in the wild type and the malate synthase mutant but not in the double mutant.
    Keywords: Biotechnology & Synthetic Biology
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  • 19
    Publication Date: 2016-02-20
    Description: The heavy dependence on petroleum-derived fuel has raised concerns about energy sustainability and climate change, which have prompted researchers to explore fuel production from renewable sources. 1-Butanol and isobutanol are promising biofuels that have favorable properties and can also serve as solvents or chemical feedstocks. Microbial production of these alcohols provides great opportunities to access a wide spectrum of renewable resources. In recent years, research has improved the native 1-butanol production and has engineered isobutanol production in various organisms to explore metabolic diversity and a broad range of substrates. This review focuses on progress in metabolic engineering for the production of these two compounds using various resources.
    Keywords: Biotechnology & Synthetic Biology
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  • 20
    Publication Date: 2016-02-20
    Description: Biobased production of butanol promises a more sustainable route for industrial production. However, butanol toxicity remains a barrier for achieving high product titers. Investigation into butanol stress has shed some light on its modes of toxicity. Unfortunately, there still remain significant shortfalls in our understanding of the complex interactions of butanol with cells. To address this knowledge gap, a diverse range of tools have been employed to gain a better understanding of the adverse effects of butanol on the cell. These findings have lead to the identification of possible molecular mechanisms associated with butanol tolerance, which can be harnessed for future strain development efforts. This review focuses on recent efforts to address the toxicity of butanol in microbial producers and offers some perspectives on the future direction of this research sector.
    Keywords: Biotechnology & Synthetic Biology
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  • 21
    Publication Date: 2016-02-25
    Description: Biobutanol outperforms bioethanol as an advanced biofuel, but is not economically competitive in terms of its titer, yield and productivity associated with feedstocks and energy cost. In this work, the synergistic effect of calcium and zinc was investigated in the acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum using glucose, xylose and glucose/xylose mixtures as carbon source(s). Significant improvements associated with enhanced glucose/xylose utilization, cell growth, acids re-assimilation and butanol biosynthesis were achieved. Especially, the maximum butanol and ABE production of 16.1 and 25.9 g L –1 were achieved from 69.3 g L –1 glucose with butanol/ABE productivities of 0.40 and 0.65 g L –1 h –1 compared to those of 11.7 and 19.4 g/L with 0.18 and 0.30 g L –1 h –1 obtained in the control respectively without any supplement. More importantly, zinc was significantly involved in the butanol tolerance based on the improved xylose utilization under various butanol-shock conditions (2, 4, 6, 8 and 10 g L –1 butanol). Under the same conditions, calcium and zinc co-supplementation led to the best xylose utilization and butanol production. These results suggested that calcium and zinc could play synergistic roles improving ABE fermentation by C. acetobutylicum .
    Keywords: Biotechnology & Synthetic Biology
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  • 22
    Publication Date: 2016-03-01
    Description: It is being increasingly realized that nucleosome organization on DNA crucially regulates DNA–protein interactions and the resulting gene expression. While the spatial character of the nucleosome positioning on DNA has been experimentally and theoretically studied extensively, the temporal character is poorly understood. Accounting for ATPase activity and DNA-sequence effects on nucleosome kinetics, we develop a theoretical method to estimate the time of continuous exposure of binding sites of non-histone proteins (e.g. transcription factors and TATA binding proteins) along any genome. Applying the method to Saccharomyces cerevisiae , we show that the exposure timescales are determined by cooperative dynamics of multiple nucleosomes, and their behavior is often different from expectations based on static nucleosome occupancy. Examining exposure times in the promoters of GAL1 and PHO5, we show that our theoretical predictions are consistent with known experiments. We apply our method genome-wide and discover huge gene-to-gene variability of mean exposure times of TATA boxes and patches adjacent to TSS (+1 nucleosome region); the resulting timescale distributions have non-exponential tails.
    Keywords: Computational Methods
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  • 23
    Publication Date: 2016-02-07
    Description: Pseudomonas putida KT2440 is a saprophytic, environmental microorganism that plays important roles in the biodegradation of environmental toxic compounds and production of polymers, chemicals and secondary metabolites. Gene deletion of KT2440 usually involves cloning of the flanking homologous fragments of the gene of interest into a suicide vector followed by transferring into KT2440 via triparental conjugation. Selection and counterselection steps are then employed to generate gene deletion mutant. However, these methods are tedious and are not suitable for the manipulation of multiple genes simultaneously. Herein, a two-step, markerless gene deletion method is presented. First, homologous armsflanked loxP-neo-loxP was knocked-in to replace the gene of interest, then the kanamycin resistance marker is removed by Cre recombinase catalyzed site-specific recombination. Both two-plasmid and one-plasmid gene systems were established. MekR/P mekA regulated gene expression system was found to be suitable for tight Cre expression in one-plasmid deletion system. The straightforward, time saving and highly efficient markerless gene deletion strategy has the potential to facilitate the genetics and functional genomics study of P. putida KT2440.
    Keywords: Biotechnology & Synthetic Biology
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  • 24
    Publication Date: 2016-03-02
    Description: Flow cytometry, in combination with fluorescent staining, was used to evaluate population heterogeneity in acetone-butanol–ethanol fermentation that was carried out with type strain Clostridium beijerinckii NCIMB 8052 and non-type C. pasteurianum NRRL B-598. A combination of propidium iodide (PI) and carboxyfluorescein diacetate (CFDA), PI plus Syto-9 and bis-oxonol (BOX) alone were employed to distinguish between active and damaged cells together with simultaneous detection of spores. These strategies provided valuable information on the physiological state of clostridia. CFDA and PI staining gave the best separation of four distinct subpopulations of enzymatically active cells, doubly stained cells, damaged cells and spores. Proportional representation of cells in particular sub-regions correlated with growth characteristics, fermentation parameters such as substrate consumption and product formation in both species under different cultivation conditions.
    Keywords: Biotechnology & Synthetic Biology
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  • 25
    Publication Date: 2016-02-03
    Description: Simultaneous saccharification and fermentation (SSF) process was applied for biobutanol production by Clostridium saccharobutylicum DSM 13864 from corn stover (CS). The key influential factors in SSF process, including corn steep liquor concentration, dry biomass and enzyme loading, SSF temperature, inoculation size and pre-hydrolysis time were optimized. In 5-L bioreactor with SSF process, butanol titer and productivity of 12.3 g/L and 0.257 g/L/h were achieved at 48 h, which were 20.6% and 21.2% higher than those in separate hydrolysis and fermentation (SHF), respectively. The butanol yield reached 0.175 g/g pretreated CS in SSF, representing 50.9% increase than that in SHF (0.116 g/g pretreated CS). This study proves the feasibility of efficient and economic production of biobutanol from CS by SSF.
    Keywords: Biotechnology & Synthetic Biology
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  • 26
    Publication Date: 2016-03-13
    Description: We previously reported that the β-1,4-Mannanase ( manB ) gene from Bacillus pumilus functions as a good reporter gene in Lactobacillus casei . Two vectors were constructed. One carries the signal peptide of secretion protein Usp45 (SP Usp45 ) from Lactococcus lactis (pELSH), and the other carries the full-length S-layer protein, SlpA, from L. acidophilus (pELWH). In this work, another vector, pELSPH, was constructed to include the signal peptide of protein SlpA (SP SlpA ), and the capacity of all three vectors to drive expression of the manB gene in L. casei was evaluated. The results showed that SP Usp45 is functionally recognized and processed by the L. casei secretion machinery. The SP Usp45 -mediated secretion efficiency was ~87%, and SP SlpA drove the export of secreted ManB with ~80% efficiency. SP SlpA secretion was highly efficient, and expressed SlpA was anchored to the cell wall by an unknown secretion mechanism. Full-length SlpA drove the cell wall-anchored expression of an SlpA-ManB fusion protein but at a much lower level than that of protein SlpA.
    Keywords: Biotechnology & Synthetic Biology
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  • 27
    Publication Date: 2016-03-13
    Description: The porin MspA of Mycobacterium smegmatis is a biological nanopore used for DNA sequencing. The octameric MspA pore can be isolated from M. smegmatis in milligram quantities, is extremely stable against denaturation and rapidly inserts into lipid membranes. Here, we show that MspA pores composed of different Msp subunits are formed in M. smegmatis and that hetero-oligomers of different Msp monomers increase the heterogeneity of MspA pores designed for DNA sequencing. To improve the quality of preparations of mutant MspA proteins, all four msp genes were deleted from the M. smegmatis genome after insertion of an inducible porin gene from M. tuberculosis. In the msp quadruple mutant M. smegmatis ML712 no Msp porins were detected and mutant MspA proteins were produced at wild-type levels. Lipid bilayer experiments demonstrated that MspA pores isolated from ML712 formed functional channels and had a narrower conductance distribution than pores purified from M. smegmatis with background msp expression. Thus, the M. smegmatis msp quadruple mutant improves the homogeneity of MspA pores designed for DNA sequencing and might also facilitate the identification and functional characterization of other mycobacterial pore proteins.
    Keywords: Biotechnology & Synthetic Biology
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  • 28
    Publication Date: 2016-03-19
    Description: The yeast mutant collections are a fundamental tool in deciphering genomic organization and function. Over the last decade, they have been used for the systematic exploration of ~6 000 000 double gene mutants, identifying and cataloging genetic interactions among them. Here we studied the extent to which these data are prone to neighboring gene effects (NGEs), a phenomenon by which the deletion of a gene affects the expression of adjacent genes along the genome. Analyzing ~90,000 negative genetic interactions observed to date, we found that more than 10% of them are incorrectly annotated due to NGEs. We developed a novel algorithm, GINGER, to identify and correct erroneous interaction annotations. We validated the algorithm using a comparative analysis of interactions from Schizosaccharomyces pombe . We further showed that our predictions are significantly more concordant with diverse biological data compared to their mis-annotated counterparts. Our work uncovered about 9500 new genetic interactions in yeast.
    Keywords: Computational Methods
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  • 29
    Publication Date: 2016-03-19
    Description: Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/ .
    Keywords: Computational Methods
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  • 30
    facet.materialart.
    Unknown
    Oxford University Press
    Publication Date: 2016-03-04
    Description: Mostly, butanol is formed as a product by saccharolytic anaerobes, employing the so-called ABE fermentation (for acetone–butanol–ethanol). However, this alcohol can also be produced from gaseous substrates such as syn(thesis) gas (major components are carbon monoxide and hydrogen) by autotrophic acetogens. In view of economic considerations, a biotechnological process based on cheap and abundant gases such as CO and CO 2 as a carbon source is preferable to more expensive sugar or starch fermentation. In addition, any conflict for use of substrates that can also serve as human nutrition is avoided. Natural formation of butanol has been found with, e.g. Clostridium carboxidivorans , while metabolic engineering for butanol production was successful using, e.g. C. ljungdahlii . Production of butanol from CO 2 under photoautotrophic conditions was also possible by recombinant DNA construction of a respective cyanobacterial Synechococcus sp. PCC 7942 strain.
    Keywords: Biotechnology & Synthetic Biology
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  • 31
    Publication Date: 2016-05-20
    Description: Lichen-forming fungi and extracts derived from them have been used as alternative medicine sources for millennia and recently there has been a renewed interest in their known bioactive properties for anticancer agents, cosmetics and antibiotics. Although lichen-forming fungus-derived compounds are biologically and commercially valuable, few studies have been performed to determine their modes of action. This study used chemical-genetic and chemogenomic high-throughput analyses to gain insight into the modes of action of Caloplaca flavoruscens extracts. High-throughput screening of 575 lichen extracts was performed and 39 extracts were identified which inhibited yeast growth. A C. flavoruscens extract was selected as a promising antifungal and was subjected to genome-wide haploinsufficiency profiling and homozygous profiling assays. These screens revealed that yeast deletion strains lacking Rsc8, Pro1 and Toa2 were sensitive to three concentrations (IC 25.5 , IC 25 and IC 50 , respectively) of C. flavoruscens extract. Gene-enrichment analysis of the data showed that C. flavoruscens extracts appear to perturb transcription and chromatin remodeling.
    Keywords: Biotechnology & Synthetic Biology
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  • 32
    Publication Date: 2016-05-20
    Description: Plant lectins, which are proteins/glycoproteins present in a wide range of vegetables, fruits, cereals and beans, are resistant to digestive enzymes and food cooking temperatures. They bind reversibly to specific glycosidic residues expressed on the membrane of intestinal epithelial cells (IEC) and cause anti-nutritional effects in humans and animals. Soybean lectin (SBA) has been detected in poultry diets, and its ability to bind to the intestinal epithelium has been reported. The development of new methods for removing SBA from feeds or to prevent interaction with the intestinal mucosa is of interest. In this study, the in vitro cytotoxicity of SBA on IEC of chicks was demonstrated for the first time. The LD 50 , assessed after 2 h exposure of IEC to SBA, was 6.13 μg mL –1 . The ability of Bifidobacterium infantis CRL1395 to bind SBA on the bacterial envelope was confirmed, and prevention of IEC cytotoxicity by lectin removal was demonstrated. Safety of B. infantis CRL1395, resistance to gastrointestinal stress and adhesion were also determined. It was concluded that the early administration of B. infantis CRL1395 to chicks would effectively reduce the toxicity of SBA. Besides, it would favour the colonization of the gut with a beneficial microbiota.
    Keywords: Biotechnology & Synthetic Biology
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  • 33
    Publication Date: 2016-05-06
    Description: Sequence Logos and its variants are the most commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs. They provide consensus-based summaries of the sequences in the alignment. Consequently, individual sequences cannot be identified in the visualization and covariant sites are not easily discernible. We recently proposed Sequence Bundles , a motif visualization technique that maintains a one-to-one relationship between sequences and their graphical representation and visualizes covariant sites. We here present Alvis, an open-source platform for the joint explorative analysis of MSAs and phylogenetic trees, employing Sequence Bundles as its main visualization method. Alvis combines the power of the visualization method with an interactive toolkit allowing detection of covariant sites, annotation of trees with synapomorphies and homoplasies, and motif detection. It also offers numerical analysis functionality, such as dimension reduction and classification. Alvis is user-friendly, highly customizable and can export results in publication-quality figures. It is available as a full-featured standalone version ( http://www.bitbucket.org/rfs/alvis ) and its Sequence Bundles visualization module is further available as a web application ( http://science-practice.com/projects/sequence-bundles ).
    Keywords: Computational Methods
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  • 34
    Publication Date: 2016-04-08
    Description: Fermentation-based production of butyric acid is robust and efficient. Modern catalytic technologies make it possible to convert butyric acid to important fine chemicals and biofuels. Here, current chemocatalytic and biocatalytic conversion methods are reviewed with a focus on upgrading butyric acid to 1-butanol or butyl-butyrate. Supported Ruthenium- and Platinum-based catalyst and lipase exhibit important activities which can pave the way for more sustainable process concepts for the production of green fuels and chemicals.
    Keywords: Biotechnology & Synthetic Biology
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  • 35
    Publication Date: 2016-04-15
    Description: Clostridium acetobutylicum is an industrially important Gram-positive organism, which is capable of producing economically important chemicals in the ABE (Acetone, Butanol and Ethanol) fermentation process. Renewed interests in the ABE process necessitate the availability of additional genetics tools to facilitate the derivation of a greater understanding of the underlying metabolic and regulatory control processes in operation through forward genetic strategies. In this study, a xylose inducible, mariner -based, transposon system was developed and shown to allow high-efficient random mutagenesis in the model strain ATCC 824. Of the thiamphenicol resistant colonies obtained, 91.9% were shown to be due to successful transposition of the catP- based mini-transposon element. Phenotypic screening of 200 transposon clones revealed a sporulation-defective clone with an insertion in spo0A , thereby demonstrating that this inducible transposon system can be used for forward genetic studies in C. acetobutylicum .
    Keywords: Biotechnology & Synthetic Biology
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  • 36
    Publication Date: 2016-04-15
    Description: Bacteria are becoming increasingly resistant to currently used antibiotics. At the same time, little progress has been made in discovering new antibacterial drugs to combat resistant organisms. History teaches us that ‘high tech’ target-based complex methods are not synonymous with success and a return to simple, systematic screening of natural products against bacteria from traditional and novel resources holds our greatest hope of success.
    Keywords: Biotechnology & Synthetic Biology
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  • 37
    Publication Date: 2016-04-15
    Description: The economic upturn of the past 200 years would not have been conceivable without fossil resources such as coal and oil. However, the fossil-based economy increasingly reaches its limits and displays contradictions. Bioeconomy, strategically combining economy and ecology willing to make biobased and sustainable growth possible, is promising to make a significant contribution towards solving these issues. In this context, microbial bioconversions are promising to support partially the increasing need for materials and fuels starting from fresh, preferably waste, biomass. Butanol is a very attractive molecule finding applications both as a chemical platform and as a fuel. Today it principally derives from petroleum, but it also represents the final product of microbial catabolic pathways. Because of the need to maximize yield, titer and productivity to make the production competitive and viable, the challenge is to transform a robustly regulated metabolic network into the principal cellular activity. However, this goal can only be accomplished by a profound understanding of the cellular physiology, survival strategy and sensing/signalling cascades. Here, we shortly review on the natural cellular pathways and circumstances that lead to n -butanol accumulation, its physiological consequences that might not match industrial needs and on possible solutions for circumventing these natural constraints.
    Keywords: Biotechnology & Synthetic Biology
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  • 38
    facet.materialart.
    Unknown
    Oxford University Press
    Publication Date: 2016-04-20
    Description: Butanol is a very interesting substance both for the chemical industry and as a biofuel. The classical distillation process for the removal of butanol is far too energy demanding, at a factor of 220% of the energy content of butanol. Alternative separation processes studied are hybrid processes of gas-stripping, liquid–liquid extraction and pervaporation with distillation and a novel adsorption/drying/desorption hybrid process. Compared with the energy content of butanol, the resulting energy demand for butanol separation and concentration of optimized hybrid processes is 11%–22% for pervaporation/distillation and 11%–17% for liquid–liquid extraction/distillation. For a novel adsorption/drying/desorption process, the energy demand is 9.4%. But all downstream process options need further proof of industrial applicability.
    Keywords: Biotechnology & Synthetic Biology
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  • 39
    Publication Date: 2016-04-20
    Description: Acetone–butanol–ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation.
    Keywords: Biotechnology & Synthetic Biology
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  • 40
    Publication Date: 2016-02-10
    Description: Cry proteins are pesticidal toxins produced by the bacterium Bacillus thuringiensis (Bt), which aggregate in sporulating cells to form a crystal. Except in a relatively few cases, these crystals are located outside the exosporium that surrounds the spore. Bt2-56 is a strain of Bt that has the relatively uncommon characteristic of locating its Cry protein-containing crystal within the exosporium, and in association with a long, multifiber filament. With the ultimate goal of both understanding and manipulating the localization of Cry proteins within the exosporium, we sought to identify the genes coding for the exosporium-localized Cry proteins in Bt2-56. Herein we show (i) that five cry-like genes are present in the genome of Bt2-56, (ii) that two pairs of these genes show organizational similarity to a relatively uncommon gene configuration that coexpress a cry gene along with a gene whose product aids crystal formation and (iii) that when one of these two gene pairs (cry21A-cdA) is expressed in an acrystalliferous strain of Bt, crystals are formed that localize within the exosporium. In Bt ssp. finitimus , the only other strain in which crystal localization has been studied, a Cry protein needed expression of two non-cry ORFs in order to localize within the exosporium, indicating that there are some mechanistic differences for crystal localization between Bt ssp. finitimus and Bt2-56.
    Keywords: Biotechnology & Synthetic Biology
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  • 41
    Publication Date: 2016-02-12
    Description: The commercialization of the n -butanol bioprocess is largely dependent on the price of feedstocks. Renewable cellulose appears to be an appealing feedstock. The microbial production of n -butanol still remains challenging because of the limited availability of intracellular NADH. To address this issue, an Escherichia coli strain carrying the clostridial CoA-dependent pathway was supplied with heterologous formate dehydrogenase. With the cellulose hydrolysate of rice straw, this single strain produced cellulosic biobutanol with a production yield at 35% of the theoretical and a productivity of 0.093 g L –1  h –1 . In an alternative method, the production involved a co-culture system consisting of two separate strains provided with the full CoA-dependent pathway. This system achieved a production yield and productivity reaching 62.8% of the theoretical and 0.163 g L –1  h –1 , respectively. The result indicates that the E. coli co-culture system is technically promising for the production of cellulosic biobutanol.
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  • 42
    Publication Date: 2016-11-09
    Description: Hepatitis E virus (HEV) is the pathogen causing hepatitis E (HE). It arouses global public health concern since it is a zoonotic disease. The objective of this letter is to report a cost-effective internal control prepared for monitoring procedures of HEV reverse transcriptase (RT)-PCR detection. A selected conserved HEV RNA fragment was integrated into the downstream of the truncated MS2 bacteriophage genome based on Armored RNA technology. The resulting MS2-HEV gene harbored by the pET-28b-MS2-HEV plasmid was transformed into E. coli BL21(DE3) for expression analysis by SDS-PAGE. The expression products were purified and concentrated by ultrasonication and ultrafiltration separation. The morphology and stability properties of the virus-like particles (VLPs) were evaluated by electron microscopy scanning and nuclease challenges, respectively. SDS-PAGE results showed that the constructed MS2-HEV gene expressed efficiently and the purity of the VLPs was highly consistent with the result in electron microscopy. Stability evaluation results demonstrated that the prepared VLPs exhibited strong resistance to DNase I and RNase A attacks and also performed long-lasting protection of coated HEV RNA for at least 4 months at –20°C. These data revealed that the prepared VLPs meet the basic requirements of use as internal control material in the HEV RNA amplification assay.
    Keywords: Biotechnology & Synthetic Biology
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  • 43
    Publication Date: 2016-09-08
    Description: Epigenetics is the study of heritable changes in gene expression without concomitant changes in DNA sequence. Due to its relevance in development, differentiation and human health, epigenetics has recently become an emerging area of science with regard to eukaryotic organisms and has shown enormous potential in synthetic biology. However, significant examples of epigenetic regulation in bacterial synthetic biology have not yet been reported. In the current study, we present the first model of such an epigenetic circuit. We termed the circuit the alternator circuit because parental cells carrying this circuit and their progeny alternate between distinct and heritable cellular fates without undergoing changes in genome sequence. Furthermore, we demonstrated that the alternator circuit exhibits hysteresis because its output depends not only on its present state but also on its previous states.
    Keywords: Biotechnology & Synthetic Biology
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  • 44
    Publication Date: 2016-10-12
    Description: Bacteriophages produce endolysins (peptidoglycan hydrolases) to lyse the host cell from within and release nascent bacteriophage particles. Recombinant endolysins can lyse Gram-positive bacteria when added exogenously. As a potential alternative antimicrobial, we cloned and expressed the enterococcal VD13 bacteriophage endolysin. VD13 endolysin has a CHAP catalytic domain with 92% identity with the bacteriophage IME-EF1 endolysin. The predicted size of VD13 endolysin is ~27 kDa as verified by SDS-PAGE. The VD13 endolysin lyses Enterococcus faecalis strains, but not E. faecium or other non-enterococci. VD13 endolysin has activity from pH 4 to pH 8, with peak activity at pH 5, and exhibits greater activity in the presence of calcium. Optimum activity at pH 5 occurs in the absence of NaCl. VD13 endolysin, in ammonium acetate (C 2 H 3 O 2 NH 4 ) calcium chloride (CaCl 2 ) buffer pH 5, is stimulated to higher activity upon heating at temperatures up to 65°C for 30 min, whereas activity is lost upon heating to 42°C, in pH 7 buffer.
    Keywords: Biotechnology & Synthetic Biology
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  • 45
    Publication Date: 2016-09-08
    Description: Cultivation in a bioreactor of immobilized deep-sea hydrothermal microbial community was tested in order to assess the stability and reactivity of this new system. A community composed of eight hydrothermal strains was entrapped in a polymer matrix that was used to inoculate a continuous culture in a gas-lift bioreactor. The continuous culture was performed for 41 days at successively 60°C, 55°C, 60°C, 85°C and 60°C, at pH 6.5, in anaerobic condition and constant dilution rate. Oxic stress and pH variations were tested at the beginning of the incubation. Despite these detrimental conditions, three strains including two strict anaerobes were maintained in the bioreactor. High cell concentrations (3 x 10 8 cells mL –1 ) and high ATP contents were measured in both liquid fractions and beads. Cloning-sequencing and qPCR revealed that Bacillus sp. dominated at the early stage, and was later replaced by Thermotoga maritima and Thermococcus sp. Acetate, formate and propionate concentrations varied simultaneously in the liquid fractions. These results demonstrate that these immobilized cells were reactive to culture conditions. They were protected inside the beads during the stress period and released in the liquid fraction when conditions were more favorable. This confirms the advantage of immobilization that highlights the resilience capacity of certain hydrothermal microorganisms after a stress period.
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  • 46
    Publication Date: 2016-10-12
    Description: To study the viability of a gyrA S83 stop mutation found in an Escherichia coli J53 ciprofloxacin-resistant strain (J53 CipR27), a pBR322 derivative was constructed with a TAG mutation in the bla gene knocking out ampicillin resistance. Ampicillin resistance was restored, suggesting that the strain contains tRNA suppressor activity able to suppress the UAG codon gyrA and allow viability. The method was applied to 22 unique clinical E. coli isolates, and all were found to have low-level suppressor activity.
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  • 47
    Publication Date: 2016-10-14
    Description: Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.
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  • 48
    Publication Date: 2016-11-17
    Description: Enterotoxigenic Escherichia coli (ETEC) bacteria producing heat-stable toxin (STa) and/or heat-labile toxin (LT) are among top causes of children's diarrhea and travelers’ diarrhea. Currently no vaccines are available for ETEC associated diarrhea. A major challenge in developing ETEC vaccines is the inability to stimulate protective antibodies against the key STa toxin that is potently toxic and also poorly immunogenic. A recent study suggested toxoid fusion 3xSTa N12S -dmLT, which consists of a monomer LT toxoid (LT R192G/L211A ) and three copies of STa toxoid STa N12S , may represent an optimal immunogen inducing neutralizing antibodies against STa toxin [IAI 2014, 82(5):1823-32]. In this study, we immunized mice with this fusion protein following a different parenteral route and using different adjuvants to further characterize immunogenicity of this toxoid fusion. Data from this study showed that 3xSTa N12S -dmLT toxoid fusion induced neutralizing anti-STa antibodies in the mice following subcutaneous immunization, as effectively as in the mice under intraperitoneal route. Data also indicated that double mutant LT (dmLT) can be an effective adjuvant for this toxoid fusion in mice subcutaneous immunization. Results from this study affirmed that toxoid fusion 3xSTa N12S -dmLT induces neutralizing antibodies against STa toxin, suggesting this toxoid fusion is potentially a promising immunogen for ETEC vaccine development.
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  • 49
    Publication Date: 2016-12-01
    Description: Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish ( Danio rerio ), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet ( www.inetbio.org/danionet ), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.
    Keywords: Computational Methods
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  • 50
    Publication Date: 2016-12-04
    Description: Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.
    Keywords: Computational Methods
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  • 51
    Publication Date: 2016-12-17
    Description: A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.
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  • 52
    Publication Date: 2016-12-17
    Description: Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm . Contact: peddada@niehs.nih.gov
    Keywords: Computational Methods
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  • 53
    Publication Date: 2016-12-23
    Description: Carocin D is a bacteriocin produced by Pectobacterium carotovorum subsp. carotovorum Pcc21. Carocin D inhibits the growth of P . carotovorum subsp. carotovorum and closely related strains. Pectobacterium carotovorum subsp. carotovorum is a causative bacterium for soft rot disease and leads to severe economic losses. Bacteriocins recognize and interact with a specific membrane protein of target bacteria as a receptor. To identify the receptor responsible for carocin D recognition, mutants that underwent a phenotypic change from carocin D sensitivity to carocin D insensitivity were screened. Based on Tn 5 insertions, carocin D sensitivity was dependent on expression of the outer membrane protein OmpF. The insensitivity of the mutant (Pcc3MR) to carocin D was complemented with ompF from carocin D-sensitive strains, not from carocin D-resistant strains. The selectivity between sensitive and resistant strains could be attributed to variation in OmpFs in the cell-surface-exposed regions. Based on sequence analysis and complementation assays, it appears that carocin D uses OmpF as a receptor and is translocated by the TonB system. According to previously reported translocation mechanisms of colicins, OmpF works along with the TolA system rather than the TonB system. Therefore, the current findings suggest that carocin D is imported by a unique colicin-like bacteriocin translocation system.
    Keywords: Biotechnology & Synthetic Biology
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  • 54
    Publication Date: 2016-11-17
    Description: Pseudomonas putida KT2440 is a saprophytic and generally recognized as safe microorganism that plays important roles in the biodegradation and production of value-added chemicals. Chromosomal gene deletion of P. putida KT2440 usually involves time-consuming gene cloning, conjugal transfer and counterselection. Recently, we developed a P. putida KT2440 markerless gene deletion method based on recombineering and Cre/ loxP site-specific recombination. PCR-based Red recombineering circumvents the tedious cloning steps and is more amenable to high-throughput manipulation. Here we report an improved scarless gene deletion strategy based on recombineering and intron-encoded homing endonuclease I-SceI-mediated double-strand break repair. Sixteen drug exporter gene(s) were deleted and the minimal inhibition concentrations of the mutants to a variety of antibiotics were determined. The robustness of the procedure was also demonstrated by sequential deletion of five large genomic regions. Up to 59% recombination efficiency was achieved for a 54.8 kb deletion, and the efficiency of RecA-mediated double-strand break repair, which was boosted by Red recombinase, was nearly 100%. The strain with a 3.76% genome reduction showed an improved growth rate and transformation efficiency. The straightforward, time-saving and highly efficient scarless deletion approach has the potential to facilitate the genetic study, and biotechnological and environmental applications of P. putida KT2440.
    Keywords: Biotechnology & Synthetic Biology
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  • 55
    Publication Date: 2016-12-16
    Description: Human health has been seriously endangered by highly prevalent salmonellosis and multidrug-resistant Salmonella strains. Current vaccines suffer from variable immune-protective effects, so more effective ones are needed to control Salmonella infection . Bacterial ghosts have been produced by the expression of lysis gene E from bacteriophage PhiX174 and can be filled with considerable exogenous substances such as DNA or drugs as a novel platform. In this study, Salmonella enteritidis (SE) ghosts were developed and loaded with Neisseria gonorrhoeae porin B (porB) to construct a novel inactive vaccine. Our new studies show that SE ghosts loaded with porB displayed increased production of pro-inflammatory cytokines (IL-1β, IL-6, IL-10 and IL-12p70) in bone marrow-derived dendritic cells (BMDCs), and elicited significantly higher specific systemic and mucosal immune responses to Salmonella than SE ghosts alone. In addition, the novel porB-loaded ghosts conferred higher protective effects on virulent Salmonella challenge. For the first time, we demonstrate that N. gonorrhoeae porB, as a novel adjuvant, can increase the immunogenicity of SE ghosts. Our studies suggested that Salmonella enteritidis ghosts loaded with Neisseria gonorrhoeae porin B might be a useful mucosal Salmonella vaccine candidate for practical use in the future.
    Keywords: Biotechnology & Synthetic Biology
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  • 56
    Publication Date: 2016-12-12
    Description: The food-grade bacterium Lactococcus lactis is increasingly used for heterologous protein expression in therapeutic and industrial applications. The ability of L. lactis to secrete biologically active cytokines may be used for the generation of therapeutic cytokines. Interleukin (IL)-18 enhances the immune response, especially on mucosal surfaces, emphasizing its therapeutic potential. However, it is produced as an inactive precursor and has to be enzymatically cleaved for maturation. We genetically manipulated L. lactis to secrete murine IL-18. The mature murine IL-18 gene was inserted downstream of a nisin promoter in pNZ8149 plasmid and the construct was used to transform L. lactis NZ3900 . The transformants were selected on Elliker agar and confirmed by restriction enzyme digestion and sequencing. The expression and secretion of IL-18 protein was verified by SDS-PAGE, western blotting and ELISA. The biological activity of recombinant IL-18 was determined by its ability to induce interferon (IFN)- production in L. lactis co-cultured with murine splenic T cells. The amounts of IL-18 in bacterial lysates and supernatants were 3–4 μg mL –1 and 0.6–0.7 ng mL –1 , respectively. The successfully generated L. lactis strain that expressed biologically active murine IL-18 can be used to evaluate the possible therapeutic effects of IL-18 on mucosal surfaces.
    Keywords: Biotechnology & Synthetic Biology
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  • 57
    Publication Date: 2015-09-19
    Description: Sequence alignment is a long standing problem in bioinformatics. The Basic Local Alignment Search Tool (BLAST) is one of the most popular and fundamental alignment tools. The explosive growth of biological sequences calls for speedup of sequence alignment tools such as BLAST. To this end, we develop high speed BLASTN (HS-BLASTN), a parallel and fast nucleotide database search tool that accelerates MegaBLAST—the default module of NCBI-BLASTN. HS-BLASTN builds a new lookup table using the FMD-index of the database and employs an accurate and effective seeding method to find short stretches of identities (called seeds) between the query and the database. HS-BLASTN produces the same alignment results as MegaBLAST and its computational speed is much faster than MegaBLAST. Specifically, our experiments conducted on a 12-core server show that HS-BLASTN can be 22 times faster than MegaBLAST and exhibits better parallel performance than MegaBLAST. HS-BLASTN is written in C++ and the related source code is available at https://github.com/chenying2016/queries under the GPLv3 license.
    Keywords: Computational Methods
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  • 58
    Publication Date: 2015-05-29
    Description: Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
    Keywords: Computational Methods
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  • 59
    Publication Date: 2015-05-03
    Description: MicroRNAs (miRNAs) regulate gene expression by binding to partially complementary sequences on target mRNA transcripts, thereby causing their degradation, deadenylation, or inhibiting their translation. Genomic variants can alter miRNA regulation by modifying miRNA target sites, and multiple human disease phenotypes have been linked to such miRNA target site variants (miR-TSVs). However, systematic genome-wide identification of functional miR-TSVs is difficult due to high false positive rates; functional miRNA recognition sequences can be as short as six nucleotides, with the human genome encoding thousands of miRNAs. Furthermore, while large-scale clinical genomic data sets are becoming increasingly commonplace, existing miR-TSV prediction methods are not designed to analyze these data. Here, we present an open-source tool called SubmiRine that is designed to perform efficient miR-TSV prediction systematically on variants identified in novel clinical genomic data sets. Most importantly, SubmiRine allows for the prioritization of predicted miR-TSVs according to their relative probability of being functional. We present the results of SubmiRine using integrated clinical genomic data from a large-scale cohort study on chronic obstructive pulmonary disease (COPD), making a number of high-scoring, novel miR-TSV predictions. We also demonstrate SubmiRine's ability to predict and prioritize known miR-TSVs that have undergone experimental validation in previous studies.
    Keywords: Computational Methods
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  • 60
    Publication Date: 2015-01-24
    Description: Of the ~1.3 million Alu elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which Alu transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq data sets and unique Alu DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual Alu elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci corresponding to detectable transcripts, with ~120 of them expressed in at least three cell lines. In vitro transcription of selected Alu s did not reflect their in vivo expression properties, and required the native 5'-flanking region in addition to internal promoter. We also identified a cluster of expressed Alu Ya5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu -unrelated downstream moiety. Autonomous Pol III transcription was also revealed for Alu s nested within Pol II-transcribed genes. The ability to investigate Alu transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant Alu RNAs and the assessment of Alu expression alteration under pathological conditions.
    Keywords: Computational Methods
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  • 61
    Publication Date: 2015-10-15
    Description: Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro , are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein–protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/
    Keywords: Computational Methods
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  • 62
    Publication Date: 2015-04-21
    Description: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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  • 63
    Publication Date: 2015-02-18
    Description: Protein sequences predicted from metagenomic datasets are annotated by identifying their homologs via sequence comparisons with reference or curated proteins. However, a majority of metagenomic protein sequences are partial-length, arising as a result of identifying genes on sequencing reads or on assembled nucleotide contigs, which themselves are often very fragmented. The fragmented nature of metagenomic protein predictions adversely impacts homology detection and, therefore, the quality of the overall annotation of the dataset. Here we present a novel algorithm called GRASP that accurately identifies the homologs of a given reference protein sequence from a database consisting of partial-length metagenomic proteins. Our homology detection strategy is guided by the reference sequence, and involves the simultaneous search and assembly of overlapping database sequences. GRASP was compared to three commonly used protein sequence search programs (BLASTP, PSI-BLAST and FASTM). Our evaluations using several simulated and real datasets show that GRASP has a significantly higher sensitivity than these programs while maintaining a very high specificity. GRASP can be a very useful program for detecting and quantifying taxonomic and protein family abundances in metagenomic datasets. GRASP is implemented in GNU C++, and is freely available at http://sourceforge.net/projects/grasp-release .
    Keywords: Computational Methods
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  • 64
    Publication Date: 2015-02-18
    Description: Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/ , and the source code is available at https://github.com/diazlab/HiTSelect .
    Keywords: Computational Methods
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  • 65
    Publication Date: 2015-01-24
    Description: Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization. In this study, we demonstrated the utility of Epidaurus in validating hypotheses and generating novel biological insights. In particular, we described the use of Epidaurus to (i) integrate epigenetic data from prostate cancer cell lines to validate the activation function of EZH2 in castration-resistant prostate cancer and to (ii) study the mechanism of androgen receptor ( AR ) binding deregulation induced by the knockdown of FOXA1 . We found that EZH2 's noncanonical activation function was reaffirmed by its association with active histone markers and the lack of association with repressive markers. More importantly, we revealed that the binding of AR was selectively reprogramed to promoter regions, leading to the up-regulation of hundreds of cancer-associated genes including EGFR . The prebuilt epigenetic dataset from commonly used cell lines (LNCaP, VCaP, LNCaP-Abl, MCF7, GM12878, K562, HeLa-S3, A549, HePG2) makes Epidaurus a useful online resource for epigenetic research. As standalone software, Epidaurus is specifically designed to process user customized datasets with both efficiency and convenience.
    Keywords: Computational Methods
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  • 66
    Publication Date: 2015-02-18
    Description: RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ~94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ~83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred .
    Keywords: Computational Methods
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  • 67
    Publication Date: 2015-02-18
    Description: Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.
    Keywords: Computational Methods
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  • 68
    Publication Date: 2015-02-18
    Description: Here we used discriminative training methods to uncover the chromatin, transcription factor (TF) binding and sequence features of enhancers underlying gene expression in individual cardiac cells. We used machine learning with TF motifs and ChIP data for a core set of cardiogenic TFs and histone modifications to classify Drosophila cell-type-specific cardiac enhancer activity. We show that the classifier models can be used to predict cardiac cell subtype cis -regulatory activities. Associating the predicted enhancers with an expression atlas of cardiac genes further uncovered clusters of genes with transcription and function limited to individual cardiac cell subtypes. Further, the cell-specific enhancer models revealed chromatin, TF binding and sequence features that distinguish enhancer activities in distinct subsets of heart cells. Collectively, our results show that computational modeling combined with empirical testing provides a powerful platform to uncover the enhancers, TF motifs and gene expression profiles which characterize individual cardiac cell fates.
    Keywords: Computational Methods
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  • 69
    Publication Date: 2015-09-30
    Description: A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop .
    Keywords: Computational Methods
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  • 70
    Publication Date: 2015-10-31
    Description: Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx .
    Keywords: Computational Methods
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  • 71
    Publication Date: 2015-12-02
    Description: Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.
    Keywords: Computational Methods
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  • 72
    Publication Date: 2015-12-02
    Description: Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions.
    Keywords: Computational Methods
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  • 73
    Publication Date: 2015-03-14
    Description: The rapid discovery of potential driver mutations through large-scale mutational analyses of human cancers generates a need to characterize their cellular phenotypes. Among the techniques for genome editing, recombinant adeno-associated virus (rAAV)-mediated gene targeting is suited for knock-in of single nucleotide substitutions and to a lesser degree for gene knock-outs. However, the generation of gene targeting constructs and the targeting process is time-consuming and labor-intense. To facilitate rAAV-mediated gene targeting, we developed the first software and complementary automation-friendly vector tools to generate optimized targeting constructs for editing human protein encoding genes. By computational approaches, rAAV constructs for editing ~71% of bases in protein-coding exons were designed. Similarly, ~81% of genes were predicted to be targetable by rAAV-mediated knock-out. A Gateway-based cloning system for facile generation of rAAV constructs suitable for robotic automation was developed and used in successful generation of targeting constructs. Together, these tools enable automated rAAV targeting construct design, generation as well as enrichment and expansion of targeted cells with desired integrations.
    Keywords: Computational Methods
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  • 74
    Publication Date: 2015-03-14
    Description: Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
    Keywords: Computational Methods
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  • 75
    Publication Date: 2015-01-10
    Description: Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo -derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/ .
    Keywords: Computational Methods
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  • 76
    Publication Date: 2015-11-17
    Description: Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/ .
    Keywords: Computational Methods
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  • 77
    Publication Date: 2015-07-25
    Description: The cMonkey integrated biclustering algorithm identifies conditionally co-regulated modules of genes (biclusters). cMonkey integrates various orthogonal pieces of information which support evidence of gene co-regulation, and optimizes biclusters to be supported simultaneously by one or more of these prior constraints. The algorithm served as the cornerstone for constructing the first global, predictive Environmental Gene Regulatory Influence Network (EGRIN) model for a free-living cell, and has now been applied to many more organisms. However, due to its computational inefficiencies, long run-time and complexity of various input data types, cMonkey was not readily usable by the wider community. To address these primary concerns, we have significantly updated the cMonkey algorithm and refactored its implementation, improving its usability and extendibility. These improvements provide a fully functioning and user-friendly platform for building co-regulated gene modules and the tools necessary for their exploration and interpretation. We show, via three separate analyses of data for E. coli, M. tuberculosis and H. sapiens , that the updated algorithm and inclusion of novel scoring functions for new data types (e.g. ChIP-seq and transcription factor over-expression [TFOE]) improve discovery of biologically informative co-regulated modules. The complete cMonkey 2 software package, including source code, is available at https://github.com/baliga-lab/cmonkey2 .
    Keywords: Computational Methods
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  • 78
    Publication Date: 2014-12-17
    Description: Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the ‘enhanceosome’ versus the ‘TF collective’ model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary. We developed a motif-pair discovery pipeline to identify motif co-occurrences with preferential distance(s) between motifs in TF-bound regions. Utilizing a compendium of 289 mouse haematopoietic TF ChIP-seq datasets, we demonstrate that haematopoietic-related motif-pairs commonly occur with highly conserved constrained spacing and orientation between motifs. Furthermore, motif clustering revealed specific associations for both heterotypic and homotypic motif-pairs with particular haematopoietic cell types. We also showed that disrupting the spacing between motif-pairs significantly affects transcriptional activity in a well-known motif-pair—E-box and GATA, and in two previously unknown motif-pairs with constrained spacing—Ets and Homeobox as well as Ets and E-box. In this study, we provide evidence for widespread sequence-specific TF pair interaction with DNA that conforms to the ‘enhanceosome’ model, and furthermore identify associations between specific haematopoietic cell-types and motif-pairs.
    Keywords: Computational Methods
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  • 79
    Publication Date: 2014-12-17
    Description: Homologous non-coding RNAs frequently exhibit domain insertions, where a branch of secondary structure is inserted in a sequence with respect to its homologs. Dynamic programming algorithms for common secondary structure prediction of multiple RNA homologs, however, do not account for these domain insertions. This paper introduces a novel dynamic programming algorithm methodology that explicitly accounts for the possibility of inserted domains when predicting common RNA secondary structures. The algorithm is implemented as Dynalign II, an update to the Dynalign software package for predicting the common secondary structure of two RNA homologs. This update is accomplished with negligible increase in computational cost. Benchmarks on ncRNA families with domain insertions validate the method. Over base pairs occurring in inserted domains, Dynalign II improves accuracy over Dynalign, attaining 80.8% sensitivity (compared with 14.4% for Dynalign) and 91.4% positive predictive value (PPV) for tRNA; 66.5% sensitivity (compared with 38.9% for Dynalign) and 57.0% PPV for RNase P RNA; and 50.1% sensitivity (compared with 24.3% for Dynalign) and 58.5% PPV for SRP RNA. Compared with Dynalign, Dynalign II also exhibits statistically significant improvements in overall sensitivity and PPV. Dynalign II is available as a component of RNAstructure, which can be downloaded from http://rna.urmc.rochester.edu/RNAstructure.html .
    Keywords: Computational Methods
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  • 80
    Publication Date: 2014-05-01
    Description: Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on in silico generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ~10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant in situ such as members of the Prevotella genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.
    Keywords: Computational Methods
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  • 81
    Publication Date: 2014-02-11
    Description: Increasing numbers of protein structures are solved each year, but many of these structures belong to proteins whose sequences are homologous to sequences in the Protein Data Bank. Nevertheless, the structures of homologous proteins belonging to the same family contain useful information because functionally important residues are expected to preserve physico-chemical, structural and energetic features. This information forms the basis of our method, which detects RNA-binding residues of a given RNA-binding protein as those residues that preserve physico-chemical, structural and energetic features in its homologs. Tests on 81 RNA-bound and 35 RNA-free protein structures showed that our method yields a higher fraction of true RNA-binding residues (higher precision) than two structure-based and two sequence-based machine-learning methods. Because the method requires no training data set and has no parameters, its precision does not degrade when applied to ‘novel’ protein sequences unlike methods that are parameterized for a given training data set. It was used to predict the ‘unknown’ RNA-binding residues in the C-terminal RNA-binding domain of human CPEB3. The two predicted residues, F430 and F474, were experimentally verified to bind RNA, in particular F430, whose mutation to alanine or asparagine nearly abolished RNA binding. The method has been implemented in a webserver called DR_bind1, which is freely available with no login requirement at http://drbind.limlab.ibms.sinica.edu.tw .
    Keywords: Computational Methods
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  • 82
    Publication Date: 2014-10-10
    Description: Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold , which can determine all RNA sequences whose minimum free energy secondary structure is a user-specified target structure. Using RNAiFold , we design ten cis -cleaving hammerhead ribozymes, all of which are shown to be functional by a cleavage assay. We additionally use RNAiFold to design a functional cis -cleaving hammerhead as a modular unit of a synthetic larger RNA. Analysis of kinetics on this small set of hammerheads suggests that cleavage rate of computationally designed ribozymes may be correlated with positional entropy, ensemble defect, structural flexibility/rigidity and related measures. Artificial ribozymes have been designed in the past either manually or by SELEX (Systematic Evolution of Ligands by Exponential Enrichment); however, this appears to be the first purely computational design and experimental validation of novel functional ribozymes. RNAiFold is available at http://bioinformatics.bc.edu/clotelab/RNAiFold/ .
    Keywords: Computational Methods
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  • 83
    Publication Date: 2014-09-27
    Description: While mRNA stability has been demonstrated to control rates of translation, generating both global and local synonymous codon biases in many unicellular organisms, this explanation cannot adequately explain why codon bias strongly tracks neighboring intergene GC content; suggesting that structural dynamics of DNA might also influence codon choice. Because minor groove width is highly governed by 3-base periodicity in GC, the existence of triplet-based codons might imply a functional role for the optimization of local DNA molecular dynamics via GC content at synonymous sites (GC3). We confirm a strong association between GC3-related intrinsic DNA flexibility and codon bias across 24 different prokaryotic multiple whole-genome alignments. We develop a novel test of natural selection targeting synonymous sites and demonstrate that GC3-related DNA backbone dynamics have been subject to moderate selective pressure, perhaps contributing to our observation that many genes possess extreme DNA backbone dynamics for their given protein space. This dual function of codons may impose universal functional constraints affecting the evolution of synonymous and non-synonymous sites. We propose that synonymous sites may have evolved as an ‘accessory’ during an early expansion of a primordial genetic code, allowing for multiplexed protein coding and structural dynamic information within the same molecular context.
    Keywords: Computational Methods
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  • 84
    Publication Date: 2014-12-17
    Description: The thermophilic fungus Chaetomium thermophilum holds great promise for structural biology. To increase the efficiency of its biochemical and structural characterization and to explore its thermophilic properties beyond those of individual proteins, we obtained transcriptomics and proteomics data, and integrated them with computational annotation methods and a multitude of biochemical experiments conducted by the structural biology community. We considerably improved the genome annotation of Chaetomium thermophilum and characterized the transcripts and expression of thousands of genes. We furthermore show that the composition and structure of the expressed proteome of Chaetomium thermophilum is similar to its mesophilic relatives. Data were deposited in a publicly available repository and provide a rich source to the structural biology community.
    Keywords: Computational Methods
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  • 85
    Publication Date: 2014-05-01
    Description: Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k -mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25 x coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.
    Keywords: Computational Methods
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  • 86
    Publication Date: 2014-09-02
    Description: Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem–loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention.
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  • 87
    Publication Date: 2014-09-02
    Description: Binding of transcription factors to their binding sites in promoter regions is the fundamental event in transcriptional gene regulation. When a transcription factor binding site is located within a nucleosome, the DNA has to partially unwrap from the nucleosome to allow transcription factor binding. This reduces the rate of transcription factor binding and is a known mechanism for regulation of gene expression via chromatin structure. Recently a second mechanism has been reported where transcription factor off-rates are dramatically increased when binding to target sites within the nucleosome. There are two possible explanations for such an increase in off-rate short of an active role of the nucleosome in pushing the transcription factor off the DNA: (i) for dimeric transcription factors the nucleosome can change the equilibrium between monomeric and dimeric binding or (ii) the nucleosome can change the equilibrium between specific and non-specific binding to the DNA. We explicitly model both scenarios and find that dimeric binding can explain a large increase in off-rate while the non-specific binding model cannot be reconciled with the large, experimentally observed increase. Our results suggest a general mechanism how nucleosomes increase transcription factor dissociation to promote exchange of transcription factors and regulate gene expression.
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  • 88
    Publication Date: 2014-08-15
    Description: High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A , a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.
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  • 89
    Publication Date: 2013-09-26
    Description: Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.
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  • 90
    Publication Date: 2013-04-02
    Description: MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5' tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.
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  • 91
    Publication Date: 2013-09-26
    Description: It is a challenge to classify protein-coding or non-coding transcripts, especially those re-constructed from high-throughput sequencing data of poorly annotated species. This study developed and evaluated a powerful signature tool, Coding-Non-Coding Index (CNCI), by profiling adjoining nucleotide triplets to effectively distinguish protein-coding and non-coding sequences independent of known annotations. CNCI is effective for classifying incomplete transcripts and sense–antisense pairs. The implementation of CNCI offered highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan. CNCI software is available at http://www.bioinfo.org/software/cnci .
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  • 92
    Publication Date: 2013-07-16
    Description: The coupling of chromosome conformation capture (3C) with next-generation sequencing technologies enables the high-throughput detection of long-range genomic interactions, via the generation of ligation products between DNA sequences, which are closely juxtaposed in vivo . These interactions involve promoter regions, enhancers and other regulatory and structural elements of chromosomes and can reveal key details of the regulation of gene expression. 3C-seq is a variant of the method for the detection of interactions between one chosen genomic element (viewpoint) and the rest of the genome. We present r3Cseq , an R/Bioconductor package designed to perform 3C-seq data analysis in a number of different experimental designs. The package reads a common aligned read input format, provides data normalization, allows the visualization of candidate interaction regions and detects statistically significant chromatin interactions, thus greatly facilitating hypothesis generation and the interpretation of experimental results. We further demonstrate its use on a series of real-world applications.
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  • 93
    Publication Date: 2012-07-22
    Description: Sequence elements, at all levels—DNA, RNA and protein, play a central role in mediating molecular recognition and thereby molecular regulation and signaling. Studies that focus on measuring and investigating sequence-based recognition make use of statistical and computational tools, including approaches to searching sequence motifs. State-of-the-art motif searching tools are limited in their coverage and ability to address large motif spaces. We develop and present statistical and algorithmic approaches that take as input ranked lists of sequences and return significant motifs. The efficiency of our approach, based on suffix trees, allows searches over motif spaces that are not covered by existing tools. This includes searching variable gap motifs—two half sites with a flexible length gap in between—and searching long motifs over large alphabets. We used our approach to analyze several high-throughput measurement data sets and report some validation results as well as novel suggested motifs and motif refinements. We suggest a refinement of the known estrogen receptor 1 motif in humans, where we observe gaps other than three nucleotides that also serve as significant recognition sites, as well as a variable length motif related to potential tyrosine phosphorylation.
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  • 94
    Publication Date: 2012-07-22
    Description: Cataloging the association of transcripts to genetic variants in recent years holds the promise for functional dissection of regulatory structure of human transcription. Here, we present a novel approach, which aims at elucidating the joint relationships between transcripts and single-nucleotide polymorphisms (SNPs). This entails detection and analysis of modules of transcripts, each weakly associated to a single genetic variant, together exposing a high-confidence association signal between the module and this ‘main’ SNP. To explore how transcripts in a module are related to causative loci for that module, we represent such dependencies by a graphical model. We applied our method to the existing data on genetics of gene expression in the liver. The modules are significantly more, larger and denser than found in permuted data. Quantification of the confidence in a module as a likelihood score, allows us to detect transcripts that do not reach genome-wide significance level. Topological analysis of each module identifies novel insights regarding the flow of causality between the main SNP and transcripts. We observe similar annotations of modules from two sources of information: the enrichment of a module in gene subsets and locus annotation of the genetic variants. This and further phenotypic analysis provide a validation for our methodology.
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  • 95
    Publication Date: 2012-07-22
    Description: Phase variation of surface structures occurs in diverse bacterial species due to stochastic, high frequency, reversible mutations. Multiple genes of Campylobacter jejuni are subject to phase variable gene expression due to mutations in polyC/G tracts. A modal length of nine repeats was detected for polyC/G tracts within C. jejuni genomes. Switching rates for these tracts were measured using chromosomally-located reporter constructs and high rates were observed for cj1139 (G8) and cj0031 (G9). Alteration of the cj1139 tract from G8 to G11 increased mutability 10-fold and changed the mutational pattern from predominantly insertions to mainly deletions. Using a multiplex PCR, major changes were detected in ‘on/off’ status for some phase variable genes during passage of C. jejuni in chickens. Utilization of observed switching rates in a stochastic, theoretical model of phase variation demonstrated links between mutability and genetic diversity but could not replicate observed population diversity. We propose that modal repeat numbers have evolved in C. jejuni genomes due to molecular drivers associated with the mutational patterns of these polyC/G repeats, rather than by selection for particular switching rates, and that factors other than mutational drift are responsible for generating genetic diversity during host colonization by this bacterial pathogen.
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  • 96
    Publication Date: 2012-09-13
    Description: Control of translation in eukaryotes is complex, depending on the binding of various factors to mRNAs. Available data for subsets of mRNAs that are translationally up- and down-regulated in yeast eIF4E-binding protein (4E-BP) deletion mutants are coupled with reported mRNA secondary structure measurements to investigate whether 5'-UTR secondary structure varies between the subsets. Genes with up-regulated translational efficiencies in the caf20 mutant have relatively high averaged 5'-UTR secondary structure. There is no apparent wide-scale correlation of RNA-binding protein preferences with the increased 5'-UTR secondary structure, leading us to speculate that the secondary structure itself may play a role in differential partitioning of mRNAs between eIF4E/4E-BP repression and eIF4E/eIF4G translation initiation. Both Caf20p and Eap1p contain stretches of positive charge in regions of predicted disorder. Such regions are also present in eIF4G and have been reported to associate with mRNA binding. The pattern of these segments, around the canonical eIF4E-binding motif, varies between each 4E-BP and eIF4G. Analysis of gene ontology shows that yeast proteins containing predicted disordered segments, with positive charge runs, are enriched for nucleic acid binding. We propose that the 4E-BPs act, in part, as differential, flexible, polyelectrostatic scaffolds for mRNAs.
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  • 97
    Publication Date: 2012-05-23
    Description: The activation of cryptic 5' splice sites (5' SSs) is often related to human hereditary diseases. The DNA-based mutation screening strategies are commonly used to recognize the cryptic 5' SSs, because features of the local DNA sequence can influence the choice of cryptic 5' SSs. To improve the identification of the cryptic 5' SSs, we developed a structure-based method, named SPO (structure profiles and odds measure), which combines two parameters, the structural feature derived from hydroxyl radical cleavage pattern and odds measure, to assess the likelihood of a cryptic 5' SS activation in competing with its paired authentic 5' SS. Compared to the current tools for identifying activated cryptic 5' SSs, the SPO algorithm achieves higher prediction accuracy than the other methods, including MaxEnt, MDD, Markov model, weight matrix model, Shapiro and Senapathy matrix, R i and G . In addition, the predicted SPO scores from the SPO algorithm exhibited a greater degree of correlation with the strength of cryptic 5' SS activation than that measured from the other seven methods. In conclusion, the SPO algorithm provides an optimal identification of cryptic 5' SSs, can be applied in designing mutagenesis experiments for various splicing events and may be helpful to investigate the relationship between structural variants and human hereditary diseases.
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  • 98
    Publication Date: 2012-10-10
    Description: The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.
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  • 99
    Publication Date: 2012-08-08
    Description: Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues.
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  • 100
    Publication Date: 2012-09-27
    Description: Programmed –1 ribosomal frameshifting is employed in the expression of a number of viral and cellular genes. In this process, the ribosome slips backwards by a single nucleotide and continues translation of an overlapping reading frame, generating a fusion protein. Frameshifting signals comprise a heptanucleotide slippery sequence, where the ribosome changes frame, and a stimulatory RNA structure, a stem–loop or RNA pseudoknot. Antisense oligonucleotides annealed appropriately 3' of a slippery sequence have also shown activity in frameshifting, at least in vitro . Here we examined frameshifting at the U 6 A slippery sequence of the HIV gag/pol signal and found high levels of both –1 and –2 frameshifting with stem–loop, pseudoknot or antisense oligonucleotide stimulators. By examining –1 and –2 frameshifting outcomes on mRNAs with varying slippery sequence-stimulatory RNA spacing distances, we found that –2 frameshifting was optimal at a spacer length 1–2 nucleotides shorter than that optimal for –1 frameshifting with all stimulatory RNAs tested. We propose that the shorter spacer increases the tension on the mRNA such that when the tRNA detaches, it more readily enters the –2 frame on the U 6 A heptamer. We propose that mRNA tension is central to frameshifting, whether promoted by stem–loop, pseudoknot or antisense oligonucleotide stimulator.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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