Project description:We compared 3 small RNA library prep kits (CleanTag, NEXTflex, QIAseq) and two RNA extraction methods (miRNeasy and MagnaZol) on plasma. We report that library preparation has a significant effect upon the miRNA profile detected, with QIAseq libraries exhibiting the least sequencing bias of the three library kits. RNA extraction methods also contribute, to a lesser extent, to the miRNA profile detected, with MagnaZol RNA extraction increasing the percentage of reads mapping to miRNAs and the number of individual miRNAs detected.
Project description:Serum miRNAs are considered useful as non-invasive biomarkers for various diseases, but the optimal method for extracting RNA from serum is currently unknown. In this study, several RNA extraction kits were used to determine which kit is the optimal method. RNA was extracted from the serum of 8-week-old C57BL/6NJcl male mice according to the protocol of each RNA extraction kit. The yield of extracted RNA samples was calculated and electrophoretic patterns were evaluated by Agilent bioanalyzer. Expression patterns of the extracted RNA samples were confirmed by Agilent mouse miRNA microarray. The results showed significant differences in RNA yields in the miRNeasy serum/plasma advanced kit, and mirVana™ PARIS™ RNA and Native Protein Purification Kit compared to almost all other samples. Furthermore, two peaks were identified in the miRNeasy serum/plasma advanced kit using small RNA kit of Agilent bioanalyzer, one at 20-40 nucleotides (nt) and the other around 40-100 nt whereas the other reagents had a single peak. In addition, a high correlation was observed between the two RNA extraction kits in microarray. These results suggest that the above two kits are suitable for miRNA extraction from mouse serum.
Project description:Microbiome nucleic acid extraction kit model is a Named Entity Recognition (NER) model that identifies and annotates the name of the kits used in extracting microbiome nucleic acids in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with kits metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
Project description:Shotgun metagenomic sequencing has improved our understanding of the human gut microbiota. Various DNA extraction methods have been compared to find protocols that robustly and most accurately reflect the original microbial community structures. However, these recommendations can be further refined by considering the time and cost demands in dealing with samples from very large human cohorts. Additionally, fungal DNA extraction performance has so far been little investigated. We compared 6 DNA extraction protocols, MagPure Fast Stool DNA KF Kit B, Macherey Nagel™ NucleoSpin™®Soil kit, Zymo Research Quick-DNA™ Fecal/Soil Microbe kit, MOBIO DNeasy PowerSoil kit, the manual non-commercial protocol MetaHIT, and the recently published protocol Q using 1 microbial mock community (MMC) (containing 8 bacterial and 2 fungal strains) and fecal samples. All samples were manually extracted and subjected to shotgun metagenomics sequencing. Extracting DNA revealed high reproducibility within all 6 protocols, but microbial extraction efficiencies varied. The MMC results demonstrated that bead size was a determining factor for fungal and bacterial DNA yields. In human fecal samples, the MagPure bacterial extraction performed as well as the standardized protocol Q but was faster and more cost-effective. Extraction using the PowerSoil protocol resulted in a significantly higher ratio of gram-negative to gram-positive bacteria than other protocols, which might contribute to reported gut microbial differences between healthy adults. We emphasize the importance of bead size selection for bacterial and fungal DNA extraction. More importantly, the performance of the novel protocol MP matched that of the recommended standardized protocol Q but consumed less time, was more cost-effective, and is recommended for further large-scale human gut metagenomic studies.
Project description:Entamoeba histolytica membrane proteins are important players in the parasite’s pathogenicity. However, most of the proteins have not been identified. This study reports the membrane proteins extracted using three extractions methods: two commercial kits (ProteoExtract® from Calbiochem and ProteoPrep® from Sigma), and a conventional laboratory method. The resulting membrane fractions (MF) and cytosolic fractions (CF)were analysed using LC-ESI-MS/MS. The proteins identified in at least two out of three biological replicates revealed a total of 490, 492, and 587 MF proteins extracted using the ProteoExtract® kit, ProteoPrep® kit and conventional method, respectively. Meanwhile, 487, 611 and 343 proteins were identified in the CF extracted using the ProteoExtract® kit, ProteoPrep® kit and conventional method, respectively. Analysis of the identified MF and CF proteins extracted by the respective extraction kits suggests that the ProteoPrep® extraction kit was the most selective in separating MF and CF among the three extraction methods.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.