Ontology highlight
ABSTRACT:
PROVIDER: PRJEB75188 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21423015.fasta.gz | Fasta.gz | |||
| SRR21423025.fasta.gz | Fasta.gz | |||
| SRR21423010.fasta.gz | Fasta.gz | |||
| SRR21423020.fasta.gz | Fasta.gz | |||
| SRR21423014.fasta.gz | Fasta.gz |
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Project description:We optimized the extraction protocol of gluten in beer, investigated the deamidated gluten peptides and gluten fragments in beer, and explored the gluten map of eight commercial beers using optimized gluten extraction protocol followed by LC-MS/MS analysis.
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Project description:We present an efficient protein extraction and in-solution enzymatic digestion protocol optimized for mass spectrometry-based proteomics studies of human skin samples.
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Project description:<p><strong>INTRODUCTION:</strong> The extraction solvent mixtures were optimized for untargeted metabolomics analysis of microbial communities from two laboratory scale activated sludge reactors performing enhanced biological phosphorus removal (EBPR).</p><p><strong>OBJECTIVE:</strong> To develop a robust and simple analytical protocol to analyse microbial metabolomics from EBPR bioreactors.</p><p><strong>METHODS:</strong> Extra- and intra-cellular metabolites were extracted using five methods and analysed by ultraperformance liquid chromatography mass spectrometry (UPLC-MS).</p><p><strong>RESULTS:</strong> The optimal extraction method was biomass specific and methanol:water (1:1 v/v) and methanol:chloroform:water (2:2:1 v/v) were chosen, respectively, for each of the two different bioreactors.</p><p><strong>CONCLUSION:</strong> Our approach provides direct surveys of the metabolic state of PAO-enriched EBPR communities, showing that extraction methods should be carefully tailored to the microbial community under study</p>
2019-08-16 | MTBLS884 | MetaboLights
Project description:2,5-furan dicarboxylic acid (FDCA) is the top-12 value-added chemicals derived from biomass that may serve as a 'green' substitute for terephthalate acid (TPA) in polyesters. FDCA can be synthesized chemically from 5-(hydroxymethyl) furfural (HMF), which is produced from fructose or glucose. To investigate impact of the production chain of FDCA on terrestrial ecosystem and unravel molecular pathways invoked and the biological process affected in the animal, a microarray analysis was applied to measure the transcriptome-wide response in soil invertebrates Folsomia candida. Microarrays examined transcriptional changes at EC50 concentrations of FDCA, HMF and TPA spiked in sterilized LUFA 2.2 soils. The results indicated FDCA and TPA caused no significant change in gene expression, which may due to the low chemical water solubility leading to slow uptake by the animal from the pore water after. A substantial number of genes were significantly regulated in F. candida after exposure to HMF. Gene Ontology analysis showed many biological process were significantly affected, such as nucleic acid metabolism, transcriptional metabolic process, cell developmental process and oxidation-reduction process. Transcriptional profile also indicated HMF can be biotransformed by F. candida into SMF which is genotoxic and mutagenic. The current research shows that environmental risk of the FDCA production chain from biomass is not due to the final product but to the intermediate HMF.
2016-06-01 | GSE74640 | GEO
Project description:2,5-furan dicarboxylic acid (FDCA) is the top-12 value-added chemicals derived from biomass that may serve as a 'green' substitute for terephthalate acid (TPA) in polyesters. FDCA can be synthesized chemically from 5-(hydroxymethyl) furfural (HMF), which is produced from fructose or glucose. To investigate impact of the production chain of FDCA on terrestrial ecosystem and unravel molecular pathways invoked and the biological process affected in the animal, a microarray analysis was applied to measure the transcriptome-wide response in soil invertebrates Folsomia candida. Microarrays examined transcriptional changes at EC50 concentrations of FDCA, HMF and TPA spiked in sterilized LUFA 2.2 soils. The results indicated FDCA and TPA caused no significant change in gene expression, which may due to the low chemical water solubility leading to slow uptake by the animal from the pore water after. A substantial number of genes were significantly regulated in F. candida after exposure to HMF. Gene Ontology analysis showed many biological process were significantly affected, such as nucleic acid metabolism, transcriptional metabolic process, cell developmental process and oxidation-reduction process. Transcriptional profile also indicated HMF can be biotransformed by F. candida into SMF which is genotoxic and mutagenic. The current research shows that environmental risk of the FDCA production chain from biomass is not due to the final product but to the intermediate HMF. We used a one-color microarray design where each sample was hybridized to a single array
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Project description:Bone metabolism is a dynamic process involving osteoblasts, osteoclasts, and osteocytes, which maintain skeletal integrity through continuous remodelling. Disruptions in this homeostasis – caused by mineral or hormonal imbalances, systemic metabolic or inflammatory conditions, or genetic predispositions – can lead to diseases like osteoporosis and osteoarthritis, increased fracture risk and impaired bone healing. Understanding the molecular mechanisms within the bone tissue underlying these conditions is crucial for developing targeted therapies. Proteomic analyses using liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) can advance bone research by identifying crucial proteins and their dynamic interplay involved in bone health and disease. However, extracting meaningful proteomic data from bone tissue presents unique challenges due to its dense, mineral-rich matrix and the predominance of type I collagen. High-abundance bone proteins impede the detection of low-abundant non-collagenous and cellular proteins that are critical for understanding bone physiology and pathology, thereby limit the depth of proteomic analyses. To address this challenge, previous approaches have attempted to reduce collagen interference by enzymatic digestion with bacterial collagenase or by applying multi-step extraction protocols using various buffers. This study aimed to develop a novel two-step proteome extraction protocol, that 1) minimizes collagen interference while enhancing the detection of low-abundance proteins, including non-collagenous and cellular proteins; 2) is reproducible and time-efficient; and 3) is multi-omics-compatible by integrating upstream metabolite extraction. We conducted a systematic comparison of our newly proposed two-step bone proteome extraction procedure with two existing protein extraction methods: one based on enzymatic digestion with collagenase after a single-step extraction, and another using sequential extraction with four different buffers. We evaluated their performance in terms of reproducible protein quantification, variance, collagen content, as well as handling and instrument time. The enzymatic digestion of collagens in the single-step extraction method successfully reduced collagen content and improved reproducibility but still resulted in fewer quantifiable proteins compared to sequential extraction protocols (2,689 proteins). Although more complex extraction protocols identified a greater number of different collagens, they also provided greater coverage of low-abundance proteins. The four-step protocol achieved the highest quantification rate (4,934 proteins) but required twice the extraction time and produced more fractions, with no significant improvement in coefficients of variation (CVs) and high collagen content in the last fraction. Our proposed 2-step protocol combined short extraction time with effective protein quantification of 4,518 proteins, achieving a dynamic range over four orders of magnitude and reasonable reproducibility. Implementing a chloroform-methanol-based metabolite extraction before proteome extraction by the two-step protocol reduced the number of reproducibly quantified proteins by only 3% to 4,393 proteins, making it suitable for application in multi-omics approaches. By sequentially using different buffers, this protocol reduces collagen content in the extracts, enabling better coverage of the diverse range of proteins present in bone tissue. This approach not only enhances proteome coverage but also is compatible with simultaneous metabolite extraction, facilitating comprehensive multi-omics analyses.
2025-08-13 | PXD056459 | Pride
Project description:Here we have designed a full processing pipeline of P. falciparum RNA that innclues RNA preservation, extraction, cDNA synthesis and amplification, globin depletion and final transcriptome readout. To validate the protocol we have analyzed transcriptomes of P. falciaprum samples derived from filed studies as well as 3D7 lab strains. This dataset have been used to establish the best conditions for whole transcriptome amplification protocol. Additionally it inclues the validation of bead extraction protocol. It also contains field samples used for validation of the entire protocol.
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Project description:A novel integrated extraction protocol for multi-omic studies in heavily degraded samples
| PRJEB61253 | ENA