PEPR: pipelines for evaluating prokaryotic references.
Ontology highlight
ABSTRACT:
SUBMITTER: Olson ND
PROVIDER: S-EPMC4819933 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Multiprotein complexes catalyze vital biological functions in the cell. A paramount objective of the SPINE2 project was to address the structural molecular biology of these multiprotein complexes, by enlisting and developing enabling technologies for their study. An emerging key prerequisite for studying complex biological specimens is their recombinant overproduction. Novel reagents and streamlined protocols for rapidly assembling co-expression constructs for this purpose have been designed and validated. The high-throughput pipeline implemented at IGBMC Strasbourg and the ACEMBL platform at the EMBL Grenoble utilize recombinant overexpression systems for heterologous expression of proteins and their complexes. Extension of the ACEMBL platform technology to include eukaryotic hosts such as insect and mammalian cells has been achieved. Efficient production of large multicomponent protein complexes for structural studies using the baculovirus/insect cell system can be hampered by a stoichiometric imbalance of the subunits produced. A polyprotein strategy has been developed to overcome this bottleneck and has been successfully implemented in our MultiBac baculovirus expression system for producing multiprotein complexes.
| S-EPMC7128143 | biostudies-literature
Project description:BACKGROUND:Structural variations (SVs) account for about 1% of the differences among human genomes and play a significant role in phenotypic variation and disease susceptibility. The emerging nanopore sequencing technology can generate long sequence reads and can potentially provide accurate SV identification. However, the tools for aligning long-read data and detecting SVs have not been thoroughly evaluated. RESULTS:Using four nanopore datasets, including both empirical and simulated reads, we evaluate four alignment tools and three SV detection tools. We also evaluate the impact of sequencing depth on SV detection. Finally, we develop a machine learning approach to integrate call sets from multiple pipelines. Overall SV callers' performance varies depending on the SV types. For an initial data assessment, we recommend using aligner minimap2 in combination with SV caller Sniffles because of their speed and relatively balanced performance. For detailed analysis, we recommend incorporating information from multiple call sets to improve the SV call performance. CONCLUSIONS:We present a workflow for evaluating aligners and SV callers for nanopore sequencing data and approaches for integrating multiple call sets. Our results indicate that additional optimizations are needed to improve SV detection accuracy and sensitivity, and an integrated call set can provide enhanced performance. The nanopore technology is improving, and the sequencing community is likely to grow accordingly. In turn, better benchmark call sets will be available to more accurately assess the performance of available tools and facilitate further tool development.
| S-EPMC6857234 | biostudies-literature
Project description:The arcuate fasciculi are white-matter pathways that connect frontal and temporal lobes in each hemisphere. The arcuate plays a key role in the language network and is believed to be left-lateralized, in line with left hemisphere dominance for language. Measuring the arcuate in vivo requires diffusion magnetic resonance imaging-based tractography, but asymmetry of the in vivo arcuate is not always reliably detected in previous studies. It is unknown how the choice of tractography algorithm, with each method's freedoms, constraints, and vulnerabilities to false-positive and -negative errors, impacts findings of arcuate asymmetry. Here, we identify the arcuate in two independent datasets using a number of tractography strategies and methodological constraints, and assess their impact on estimates of arcuate laterality. We test three tractography methods: a deterministic, a probabilistic, and a tractography-evaluation (LiFE) algorithm. We extract the arcuate from the whole-brain tractogram, and compare it to an arcuate bundle constrained even further by selecting only those streamlines that connect to anatomically relevant cortical regions. We test arcuate macrostructure laterality, and also evaluate microstructure profiles for properties such as fractional anisotropy and quantitative R1. We find that both tractography choice and implementing the cortical constraints substantially impact estimates of all indices of arcuate laterality. Together, these results emphasize the effect of the tractography pipeline on estimates of arcuate laterality in both macrostructure and microstructure.
| S-EPMC6679767 | biostudies-literature
Project description:BackgroundSystematic reviews involve searching multiple bibliographic databases to identify eligible studies. As this type of evidence synthesis is increasingly pursued, the use of various electronic platforms can help researchers improve the efficiency and quality of their research. We examined the accuracy and efficiency of commonly used electronic methods for flagging and removing duplicate references during this process.MethodsA heterogeneous sample of references was obtained by conducting a similar topical search in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO databases. References were de-duplicated via manual abstraction to create a benchmark set. The default settings were then used in Ovid multifile search, EndNote desktop, Mendeley, Zotero, Covidence, and Rayyan to de-duplicate the sample of references independently. Using the benchmark set as reference, the number of false-negative and false-positive duplicate references for each method was identified, and accuracy, sensitivity, and specificity were determined.ResultsWe found that the most accurate methods for identifying duplicate references were Ovid, Covidence, and Rayyan. Ovid and Covidence possessed the highest specificity for identifying duplicate references, while Rayyan demonstrated the highest sensitivity.ConclusionThis study reveals the strengths and weaknesses of commonly used de-duplication methods and provides strategies for improving their performance to avoid unintentionally removing eligible studies and introducing bias into systematic reviews. Along with availability, ease-of-use, functionality, and capability, these findings are important to consider when researchers are selecting database platforms and supporting software programs for conducting systematic reviews.
| S-EPMC7827976 | biostudies-literature
Project description:BackgroundMicrobiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD.ResultsIn-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested.ConclusionsEven when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.
| S-EPMC5450146 | biostudies-literature
Project description:Recognition of microbial challenges leads to enhanced immunity at both the local and systemic levels. In Arabidopsis, EFR and PEPR1/PEPR2 act as the receptor for the bacterial elongation factor EF-Tu (elf18 epitope) and for the endogenous PROPEP-derived Pep epitopes, respectively. The PEPR pathway has been described to mediate defence signalling following microbial recognition. Here we show that PROPEP2/PROPEP3 induction upon pathogen challenges is robust against jasmonate, salicylate, or ethylene dysfunction. Comparative transcriptome profiling between Pep2- and elf18-treated plants points to co-activation of otherwise antagonistic jasmonate- and salicylate-mediated immune branches as a key output of PEPR signalling. Accordingly, as well as basal defences against hemibiotrophic pathogens, systemic immunity is reduced in pepr1 pepr2 plants. Remarkably, PROPEP2/PROPEP3 induction is essentially restricted to the pathogen challenge sites during pathogen-induced systemic immunity. Localized Pep application activates genetically separable jasmonate and salicylate branches in systemic leaves without significant PROPEP2/PROPEP3 induction. Our results suggest that local PEPR activation provides a critical step in connecting local to systemic immunity by reinforcing separate defence signalling pathways.
| S-EPMC3990683 | biostudies-literature
Project description:A peptidase gene expressing L-proline-beta-naphthylamide-hydrolyzing activity was cloned from a gene library of Lactobacillus rhamnosus 1/6 isolated from cheese. Peptidase-expressing activity was localized in a 1.5-kb SacI fragment. A sequence analysis of the SacI fragment revealed the presence of one complete open reading frame (ORF1) that was 903 nucleotides long. The ORF1-encoded 34.2-kDa protein exhibited 68% identity with the PepR protein from Lactobacillus helveticus. Additional sequencing revealed the presence of another open reading frame (ORF2) following pepR; this open reading frame was 459 bp long. Northern (RNA) and primer extension analyses indicated that pepR is expressed both as a monocistronic transcriptional unit and as a dicistronic transcriptional unit with ORF2. Gene replacement was used to construct a PepR-negative strain of L. rhamnosus. PepR was shown to be the primary enzyme capable of hydrolyzing Pro-Leu in L. rhamnosus. However, the PepR-negative mutant did not differ from the wild type in its ability to grow and produce acid in milk. The cloned pepR expressed activity against dipeptides with N-terminal proline residues. Also, Met-Ala, Leu-Leu, and Leu-Gly-Gly and the chromogenic substrates L-leucine-beta-naphthylamide and L-phenylalanine-beta-naphthylamide were hydrolyzed by the PepR of L. rhamnosus.
| S-EPMC106238 | biostudies-literature
Project description:The success of high-throughput sequencing has lead to an increasing number of projects which sequence large populations of a species. Storage and analysis of sequence data is a key challenge in these projects, because of the sheer size of the datasets. Compression is one simple technology to deal with this challenge. Referential factorization and compression schemes, which store only the differences between input sequence and a reference sequence, gained lots of interest in this field. Highly-similar sequences, e.g., Human genomes, can be compressed with a compression ratio of 1,000:1 and more, up to two orders of magnitude better than with standard compression techniques. Recently, it was shown that the compression against multiple references from the same species can boost the compression ratio up to 4,000:1. However, a detailed analysis of using multiple references is lacking, e.g., for main memory consumption and optimality. In this paper, we describe one key technique for the referential compression against multiple references: The factorization of sequences. Based on the notion of an optimal factorization, we propose optimization heuristics and identify parameter settings which greatly influence 1) the size of the factorization, 2) the time for factorization, and 3) the required amount of main memory. We evaluate a total of 30 setups with a varying number of references on data from three different species. Our results show a wide range of factorization sizes (optimal to an overhead of up to 300%), factorization speed (0.01 MB/s to more than 600 MB/s), and main memory usage (few dozen MB to dozens of GB). Based on our evaluation, we identify the best configurations for common use cases. Our evaluation shows that multi-reference factorization is much better than single-reference factorization.
| S-EPMC4589410 | biostudies-literature
Project description:Benchmarking of metagenomics pipelines
| PRJEB39393 | ENA
Project description:The construction of industrial projects involves fabricating and installing massive quantities of pipelines. The design data of pipelines is complex, usually unique for each project and not easily available to researchers and the public for confidentiality reasons. As a result, an industrial pipelines data generator able to realistically simulate pipelines structures will lessen the dependence on real-life data. This article describes an industrial pipelines data generator that was developed using topological and physical properties of pipelines from real industrial projects. This generator can simulate the properties (the type of component, length, diameter, running direction, and the connectivity relationships between components) of real industrial pipelines. Its application in construction engineering and management research, more specifically in the experimental analysis of an optimization algorithm, was described by the authors in previous work [1]. The data generator can be used to develop benchmark problem instances for optimization problems and for simulation studies of construction operations in industrial projects.
| S-EPMC7490719 | biostudies-literature