Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors.

ABSTRACT: Biosensors are key components in engineered biological systems, providing a means of measuring and acting upon the large biochemical space in living cells. However, generating small molecule sensing elements and integrating them into in vivo biosensors have been challenging. Here, using aptamer-coupled ribozyme libraries and a ribozyme regeneration method, de novo rapid in vitro evolution of RNA biosensors (DRIVER) enables multiplexed discovery of biosensors. With DRIVER and high-throughput characterization (CleaveSeq) fully automated on liquid-handling systems, we identify and validate biosensors against six small molecules, including five for which no aptamers were previously found. DRIVER-evolved biosensors are applied directly to regulate gene expression in yeast, displaying activation ratios up to 33-fold. DRIVER biosensors are also applied in detecting metabolite production from a multi-enzyme biosynthetic pathway. This work demonstrates DRIVER as a scalable pipeline for engineering de novo biosensors with wide-ranging applications in biomanufacturing, diagnostics, therapeutics, and synthetic biology.

SUBMITTER: Townshend B

PROVIDER: S-EPMC7933316 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2016-03-28 | E-GEOD-77634 | biostudies-arrayexpress

Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery

Project description:Cerebrospinal fluid (CSF) is a body fluid of high clinical relevance and an important source of potential biomarkers for brain-associated damages such as traumatic brain injury, stroke, and for brain diseases like Alzheimer’s and Parkinson's . Herein, we have implemented, evaluated and validated a scalable automated proteomic pipeline (ASAP2) for the sample preparation and proteomic analysis of CSF, enabling increased throughput and robustness for biomarker discovery. Human CSF samples were depleted from abundant proteins, and submitted to automated reduction, alkylation, protein digestion, tandem mass tag (TMT) 6-plex labeling, pooling, and sample clean-up in a 96-well plate format before reversed-phase liquid chromatography tandem mass spectrometry (RP-LC MS/MS). First, we showed the impact on the CSF proteome coverage of applying the depletion of abundant proteins, which is usually performed on blood plasma or serum samples. Using ASAP2 to analyze 96 identical CSF samples, we determined the analytical figures of merit of our shotgun proteomic approach regarding proteome coverage consistency (i.e., 387 proteins), quantitative accuracy, and individual protein variability. We demonstrated that, as for human plasma samples, ASAP2 is efficient in analyzing large numbers of human CSF samples and is a valuable tool for biomarker discovery.

2015-12-09 | PXD003024 | Pride

Nested Patch PCR enables highly multiplexed mutation discovery in candidate genes.

Project description: Not available

| S-EPMC2577855 | biostudies-literature

The Bacteria Genome Pipeline (BAGEP): an automated, scalable workflow for bacteria genomes with Snakemake.

Project description: Not available

| S-EPMC7597632 | biostudies-literature

Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites

Project description:This SuperSeries is composed of the SubSeries listed below.

2016-03-28 | GSE77634 | GEO

A scalable multiplexed platform to accelerate protein interactome discovery

Project description:Chromatographic fractionation-mass spectrometry (CF-MS) allows for mapping native protein-protein interactions and macromolecular complexes on a proteome-scale but is tedious and resource intensive for comparative analysis. Here, we present a more parsimonious and reproducible multiplexing CF-MS platform for measuring multi-protein assemblies across different experimental samples simultaneously with an order-of-magnitude faster than previous approaches. We used this innovative strategy to elucidate protein networks in control and breast cancer cells models in parallel within two weeks of total MS instrument time.

2022-08-03 | PXD027704 | Pride

Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites [iCLIP]

Project description:RNA binding proteins (RBPs) play essential roles in cellular physiology by interacting with target RNAs. As defects in protein-RNA recognition lead to human disease, UV-crosslinking and immunoprecipitation (CLIP) of ribonuclear complexes followed by deep sequencing (-seq) is critical in constructing protein-RNA maps to expand our understanding of RBP function. However, current CLIP protocols are technically demanding and involve low complexity libraries that yield squandered sequencing of PCR duplicates and high experimental failure rates. To enable truly large-scale implementation of CLIP-seq, we have developed an enhanced CLIP methodology (eCLIP) that features a decrease of ~10 cycles of requisite amplification with a concomitant >60% decrease in discarded PCR duplicate reads, while maintaining the ability to identify RNA binding with single-nucleotide resolution. By simplifying the generation of paired IgG and size-matched input controls, eCLIP also dramatically improves specificity in discovery of authentic binding sites. To demonstrate that eCLIP enables large-scale and robust profiling of RBPs, 102 eCLIP experiments in biological duplicate for a diverse collection of 74 RBPs in HepG2 and K562 cells were completed (available at https://www.encodeproject.org). We establish that eCLIP is comparable in amplification and sample requirements to ChIP-seq, and enables integrative analysis of diverse RBPs to reveal factor-specific profiles, common artifacts for CLIP experiments and RNA-centric perspectives of RBP activity.

2016-03-28 | GSE77633 | GEO

Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites [array]

2016-03-28 | GSE77339 | GEO

CRISPRdisco: An Automated Pipeline for the Discovery and Analysis of CRISPR-Cas Systems.

Project description: Not available

| S-EPMC6636876 | biostudies-literature

damidseq_pipeline: an automated pipeline for processing DamID sequencing datasets

Project description:DamID is a powerful technique for identifying regions of the genome bound by a DNA-binding (or DNA-associated) protein. Currently no method exists for automatically processing next-generation sequencing DamID (DamID-seq) data, and the use of DamID-seq datasets with normalisation based on read-counts alone can lead to high background and the loss of bound signal. DamID-seq thus presents novel challenges in terms of normalisation and background minimisation. We describe here damidseq_pipeline, a software pipeline that performs automatic normalisation and background reduction on multiple DamID-seq FASTQ or BAM datasets. Single replicate profiling of pol II occupancy in 3rd instar larval neuroblasts of Drosophila

2015-06-26 | E-GEOD-69184 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data