Automated DNA metabarcoding
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB45792 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples originating from a variety of sources, including frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format, performing unbiased protein purification and digestion delivering peptides that can be directly analyzed by LCMS. AutoSP3 eliminates hands-on time and minimizes the risk of error, and we show it reduces the protein quantification variability, and improves longitudinal performance and reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1000 proteins from 100-1000 cells (<100 ng protein). Furthermore, we added a LE220-plus focused- ultrasonicator (Covaris Ltd, UK) to our pipeline to include 96-well format lysis of fresh-frozen tissue and cells. Collectively, autoSP3 provides a generic, scalable, and cost-effective pipeline for routine and standardized proteomic sample processing that should enable reproducible proteomics in broad range of clinical and non-clinical applications.
2020-03-27 | PXD015840 | Pride
Project description:High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples originating from a variety of sources, including frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format, performing unbiased protein purification and digestion delivering peptides that can be directly analyzed by LCMS. AutoSP3 eliminates hands-on time and minimizes the risk of error, and we show it reduces the protein quantification variability, and improves longitudinal performance and reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1000 proteins from 100-1000 cells (<100 ng protein). Furthermore we applied it to process a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples, and recapitulate their separation into known histological growth patterns based on proteome profiles. Collectively, autoSP3 provides a generic, scalable, and cost-effective pipeline for routine and standardized proteomic sample processing that should enable reproducible proteomics in broad range of clinical and non-clinical applications.
2020-01-10 | PXD014556 | Pride
Project description:Although tandem mass tag (TMT)-based isobaric labeling has become a powerful technique for multiplexed protein quantitation, it has not been easy to automate the workflow for widespread adoption. This is because preparation of TMT labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction and alkylation to tryptic digestion, desalting, labeling with TMT reagents and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic especially with large-scale studies such as clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for automated proteomics workflows for TMT-labeling experiments with manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using the automated platform and a conventional manual protocol. Single shot LC-MS/MS analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiencies of tryptic digestion, alkylation and TMT labeling were similar both in manual and automated process. In addition, comparison of quantitation accuracy and precision showed similar performance in automated workflow compared to manual sample preparation. Overall, we demonstrated that the automated platform performs at a level similar to manual process in TMT-based proteomics. We expect that the automated workflow will increasingly replace manual work and be applied to large-scale TMT-baed studies providing robust results and high sample throughput.
2023-10-24 | PXD040788 | Pride
Project description:Here, we present a standardized, “off-the-shelf” proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlining a fully automated sample preparation platform, data independent acquisition (DIA) coupled with high field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showed single compensation voltage (CV) at -35V not only yields deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines showed Spectronaut outperforms others, providing highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot MS using single CV(-35V)-FAIMS-DIA results in >9,000 quantifiable proteins with < 10% missing values, as well as superior reproducibility and accuracy compared to other existing DIA methods.
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Project description:Transcription factor binding locations by ChIP followed by high throughput sequencing. To build and validate an automated Chromatin Immunoprecipitation and high throughput Illumina sequencing pipeline
2013-06-01 | E-MTAB-1579 | biostudies-arrayexpress
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The CMx platform has been showed to be able to the detection of Circulating Tumor Cells (CTCs) in high sensitivity and specificity. In published studies, circulating Tumor Cells (CTCs) are captured and quantified in advanced-stages of colorectal cancer. In order to detect early and pre-cancer circulating tumor cells, we have developed an Automated Liquid Biopsy Platform that improves the detection of CTCs in early cancer stages. Therefore, this study goals are: 1) to establish a standard detection process utilizing the Automated Liquid Biopsy Platform. 2) Parallel comparison of laboratory manual operation and Automated Liquid Biopsy Platform. 3) Verify the feasibility of use of an Automated Liquid Biopsy Platform in the clinical setting.
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Project description:BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility. In this study, we optimized the BAC araay-CGH protocol for automated hybridization for FFPE breast cancer samples. We have tested hybridization temperature and duration, different hybridization buffer conditions, and post-hybridization washing.
2010-06-12 | E-GEOD-7122 | biostudies-arrayexpress
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Project description:Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring
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Project description:BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility.
2007-02-23 | GSE7122 | GEO