Ontology highlight
ABSTRACT:
PROVIDER: PRJNA470545 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7135120_1.fastq.gz | Fastqsanger.gz | |||
| SRR7135120_2.fastq.gz | Fastqsanger.gz |
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Project description:20 random DNA barcodes were designed in silico and transfected into PC3 cells. Barcodes were sequenced using Illumina-Miseq technology to find the sequence and their respective copy numbers. Current file contains the raw data of these DNA barcodes in fastq format Validating an algorithm called SRiD that generates random DNA barcodes that do not match a genome of interest, in this case human genome. 20 DNA barcodes were used for this validation.
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Project description:Detecting strain-specific barcodes with mass spectrometry can facilitate the screening of genetically engineered bacterial libraries. Here, we introduce intact protein barcoding, a method to measure protein-based library barcodes and metabolites using flow-injection mass spectrometry (FI-MS). Protein barcodes are based on ubiquitin with N-terminal tags of six amino acids. We demonstrate that FI-MS detects intact ubiquitin proteins and identifies the mass of N-terminal barcodes. In the same analysis, we measured relative concentrations of primary metabolites. We constructed 6 ubiquitin-barcoded CRISPRi strains targeting metabolic enzymes, and analyzed their metabolic profiles and ubiquitin barcodes. FI-MS detected barcodes and distinct metabolome changes in CRISPRi-targeted pathways. We demonstrate the scalability of intact protein barcoding by measuring 132 ubiquitin barcodes in microtiter plates. These results show that intact protein barcoding enables fast and simultaneous detection of library barcodes and intracellular metabolites, opening up new possibilities for mass spectrometry-based barcoding.
2024-10-30 | MSV000096254 | MassIVE
Project description:20 random DNA barcodes were designed in silico and transfected into PC3 cells. Barcodes were sequenced using Illumina-Miseq technology to find the sequence and their respective copy numbers. Current file contains the raw data of these DNA barcodes in fastq format
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Project description:This SuperSeries is composed of the following subset Series: GSE18916: Expression data from 42 prostate cancer samples - 16 recurrent and 26 recurrence-free GSE18917: Expression data from 22 prostate cancer samples - 6 recurrent and 16 recurrence-free from the validation dataset Refer to individual Series
2011-06-15 | E-GEOD-18918 | biostudies-arrayexpress
Project description:LNPs have been demonstrated to hold great promise for the clinical advancement of RNA therapeutics. Continued exploration of LNPs for application in new disease areas requires identification and optimisation of leads in a high throughput way. Currently available high throughput in vivo screening platforms are well suited to screen for cellular uptake but less so for functional cargo delivery. We report on a platform which measures functional delivery of LNPs using unique peptide ‘barcodes’. We describe the design and selection of the peptide barcodes and the evaluation of these for the screening of LNPs. We show that proteomic analysis of peptide barcodes correlates with quantification and efficacy of barcoded reporter proteins both in vitro and in vivo and, that the ranking of selected LNPs using peptide barcodes in a pool correlates with ranking using alternative methods in groups of animals treated with individual LNPs. We show that this system is sensitive, selective, and capable of reducing the size of an in vivo study by screening up to 10 unique formulations in a single pool, thus accelerating the discovery of new technologies for mRNA delivery.
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Project description:We report the synthesis and expression measurement of ~9000 inducible promoter variants. By tagging individual variants with barcodes, we can measure the expression levels of all variants under both induced and uninduced conditions in a single pooled experiment. Sequencing data here is used for 1) paired-end sequencing to map barcodes to their promoters or 2) Quantifying the counts of barcodes at the DNA and RNA levels
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Project description:Spatial transcriptomics technologies that can quantify gene expression in space are transforming contemporary biology research. Some of such methods use spatially barcoded bead arrays that are optically sequenced by a microscopy setup to detect bead barcodes in space which can be consecutively matched to cell barcodes from the respective single cell sequencing experiment. To have good quality barcodes and a high number of barcode matches in space, robust and efficient computational pipelines are needed to process raw microscopy images and call the bases of bead barcodes accurately. Here, we present Optocoder, a computational pipeline that takes raw optical sequencing microscopy images as input and outputs bead barcodes in space. Optocoder efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal such as crosstalk and phasing before base calling. Furthermore, we implement a machine learning pipeline that is trained using the signal from the beads that match to illumina barcodes in order to predict non-matching bead barcodes which can boost up the number of barcode matches. We benchmark Optocoder using data from an in-house spatial transcriptomics platform as well as data from the Slide-seq method and we show that it can efficiently process both datasets with minimal modification.
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Project description:Background: Dishevelled (DVL) is an essential component of the Wnt signaling cascades. Function of DVL is controlled by phosphorylation but the molecular details are missing. DVL3 contains 131 serines and threonines whose phosphorylation generates complex barcodes underlying diverse DVL3 functions. In order to dissect the role of DVL phosphorylation we analyzed the phosphorylation of human DVL3 induced by previously reported (CK1ε, NEK2, PLK1, CK2α, RIPK4, PKCδ) and newly identified (TTBK2, Aurora A) DVL kinases. Methods: Shotgun proteomics including TiO2 enrichment of phosphorylated peptides followed by liquid chromatography tandem mass spectrometry on immunoprecipitates from HEK293T cells was used to identify and quantify phosphorylation of DVL3 protein induced by 8 kinases. Functional characterization was performed by in-cell analysis of phospho-mimicking/non phosphorylatable DVL3 mutants and supported by FRET assays and NMR spectroscopy. Results: We used quantitative mass spectrometry and calculated site occupancies and quantified phosphorylation of >80 residues. Functional validation demonstrated the importance of CK1ε-induced phosphorylation of S268 and S311 for Wnt-3a-induced β-catenin activation. S630-643 cluster phosphorylation by CK1, NEK2 or TTBK2 is essential for even subcellular distribution of DVL3 when induced by CK1 and TTBK2 but not by NEK2. Further investigation showed that NEK2 utilizes a different mechanism to promote even localization of DVL3. NEK2 triggered phosphorylation of PDZ domain at S263 and S280 prevents binding of DVL terminus to PDZ and promotes an open conformation of DVL3 that is more prone to even subcellular localization. Conclusions: We identify unique phosphorylation barcodes associated with DVL function. Our data provide an example of functional synergy between phosphorylation in structured domains and unstructured IDRs that together dictate the biological outcome.
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