Next-Generation Sequencing Analysis of the Tineola bisselliella Larval Gut Transcriptome Reveals Candidate Enzymes for Keratin Digestion.
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ABSTRACT:
SUBMITTER: Schwabe M
PROVIDER: S-EPMC8394580 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:An innovative approach merging both the bottom-up and middle-down ideologies to provide fast, robust and comprehensive solutions for proteomics studies. The methodology, referred to as MELD for Multiple-Enzymatic Limited Digestion, capitalizes on a single two-hour long proteolytic step involving the synergic action of a diluted mix of several enzymes. While the multi-enzymatic benefits are retained, the lower enzyme concentrations induce a limitation in the proteolytic reaction. This feature engenders numerous missed cleavage events and results in abundant peptides of diverse length with overlapping stretches of residues. This outcome eventually increases the extent and confidence in the sequence coverage while opening roads for refined and comprehensive protein characterization. We here use Adalimumab, a therapeutic ~144 kDa human immunoglobulin G IgG1 as a candidate molecule to compare the respective efficacy of state-of-the-art complete mono-enzymatic strategies encompassed in individual or combinational workflows with the standard MELD protocol for extensive protein characterization. The benchmarking analysis was performed over 12 Adalimumab samples issued from independent proteolytic digestions: 6 samples were processed using the MELD methodology, 3 with the combinatory methodology and 3 with the mono-enzymatic tryptic methodology. They were all subjected to independent database searches, using both constrained and unconstrained cleavage site rules for the latter.
2019-05-08 | PXD009800 | Pride
Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride
Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.
| S-EPMC3633008 | biostudies-literature
Project description:BACKGROUND: We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis. RESULTS: The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. CONCLUSION: NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms.
| S-EPMC2907694 | biostudies-literature
Project description:Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.
| S-EPMC5587813 | biostudies-literature
Project description:Natural killer (NK) cells are innate lymphocytes important for early host defense against infectious pathogens and surveillance against malignant transformation. Resting murine NK cells regulate the translation of effector molecule mRNAs (e.g., granzyme B, GzmB) through unclear molecular mechanisms. MicroRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate the translation of their mRNA targets, and are therefore candidates for mediating this control process. While the expression and importance of miRNAs in T and B lymphocytes have been established, little is known about miRNAs in NK cells. Here, we used two next-generation sequencing (NGS) platforms to define the miRNA transcriptomes of resting and cytokine-activated primary murine NK cells, with confirmation by quantitative real-time PCR (qRT-PCR) and microarrays. We delineate a bioinformatics analysis pipeline that identified 302 known and 21 novel mature miRNAs from sequences obtained from NK cell small RNA libraries. These miRNAs are expressed over a broad range and exhibit isomiR complexity, and a subset is differentially expressed following cytokine activation. Using these miRNA NGS data, miR-223 was identified as a mature miRNA present in resting NK cells with decreased expression following cytokine activation. Furthermore, we demonstrate that miR-223 specifically targets the 3' untranslated region of murine GzmB in vitro, indicating that this miRNA may contribute to control of GzmB translation in resting NK cells. Thus, the sequenced NK cell miRNA transcriptome provides a valuable framework for further elucidation of miRNA expression and function in NK cell biology.
| S-EPMC2963822 | biostudies-literature
Project description:BackgroundMycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling.ResultsWe generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose.ConclusionsThe analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.
| S-EPMC3114729 | biostudies-literature
Project description:Aim: There is growing evidence that physical activity modulates gut microbiota composition through complex interactions between diet and microbial species. On the other hand, next-generation sequencing techniques include shotgun metagenomics and 16S amplicon sequencing. These methodologies allow a comprehensive characterisation of microbial communities of athletes from different disciplines as well as non-professional players and sedentary adults exposed to training. This systematic review summarises recent applications of next-generation sequencing to characterise the athletic gut microbiome. Methods: A systematic review of microbiome research was performed to determine the association of microbiota composition profiles with sports performance. Results: Bibliographic analysis revealed the importance of a novel research trend aiming at deciphering the associations between individual microbial species and sports performance. In addition, literature review highlighted the role of butyrate-producing bacteria such as Anaerostipes hadrus, Clostridium bolteae, Faecalibacterium prausnitzii, Roseburia hominis and unidentified species belonging to Clostridiales, Lachnospiraceae and Subdoligranulum species in gut health and sports performance across several disciplines. Interestingly, metabolic activities of Prevotella copri and Veillonella atypica involved in branched amino acid and lactate metabolism may contribute to reducing muscular fatigue. Other microbial metabolic pathways of interest involved in carbohydrate metabolism showed increased proportions in athletes´ metagenomes. Conclusion: Future research will aim at developing personalised nutrition interventions to modulate key species associated with certain components of exercise.
| S-EPMC10688803 | biostudies-literature
Project description:Transcriptome analysis has important applications in many biological fields. However, assembling a transcriptome without a known reference remains a challenging task requiring algorithmic improvements. We present two methods for substantially improving transcriptome de novo assembly. The first method relies on the observation that the use of a single k-mer length by current de novo assemblers is suboptimal to assemble transcriptomes where the sequence coverage of transcripts is highly heterogeneous. We present the Multiple-k method in which various k-mer lengths are used for de novo transcriptome assembly. We demonstrate its good performance by assembling de novo a published next-generation transcriptome sequence data set of Aedes aegypti, using the existing genome to check the accuracy of our method. The second method relies on the use of a reference proteome to improve the de novo assembly. We developed the Scaffolding using Translation Mapping (STM) method that uses mapping against the closest available reference proteome for scaffolding contigs that map onto the same protein. In a controlled experiment using simulated data, we show that the STM method considerably improves the assembly, with few errors. We applied these two methods to assemble the transcriptome of the non-model catfish Loricaria gr. cataphracta. Using the Multiple-k and STM methods, the assembly increases in contiguity and in gene identification, showing that our methods clearly improve quality and can be widely used. The new methods were used to assemble successfully the transcripts of the core set of genes regulating tooth development in vertebrates, while classic de novo assembly failed.
| S-EPMC2945192 | biostudies-literature
Project description:ObjectiveOwing to the overwhelming dominance of human and commensal microbe sequences, low efficiency is a major concern in clinical viral sequencing using next-generation sequencing. DNA composed of 7-deaza-2'-deoxyguanosine 5'-triphosphate (c7dGTP), an analog of deoxyguanosine triphosphate (dGTP), is resistant to selective restriction enzymes. This characteristic has been utilized to develop a novel strategy for target enrichment in next-generation sequencing.ResultsThe new enrichment strategy is named target enrichment via enzymatic digestion in next-generation sequencing (TEEDseq). It combined 7-deaza-2'-deoxyguanosine 5'-triphosphate (c7dGTP)-involved primer extension, splinter-assisted intracellular cyclization, c7dGTP)-resistant enzymatic digestion, and two-phase rolling cycle amplification. We first estimated c7dGTP for its efficiency in PCR amplification and its resistance to three restriction enzymes, AluI, HaeIII, and HpyCH4V. We then evaluated TEEDseq using a serum sample spiked with a 1311-bp hepatitis B virus (HBV) fragment. TEEDseq achieved an HBV on-target rate of 3.31 ± 0.39%, which was equivalent to 454× the enrichment of direct Illumina sequencing. Therefore, the current study has provided a concept proof for TEEDseq as an alternative option for clinical viral sequencing that requires an enrichment in next-generation sequencing.
| S-EPMC7499927 | biostudies-literature