A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

A genome-wide approach for identification and characterisation of metabolite-inducible systems. | LitMetric

A genome-wide approach for identification and characterisation of metabolite-inducible systems.

Nat Commun

BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of Life Sciences, The University of Nottingham, Nottingham, NG7 2RD, UK.

Published: March 2020

AI Article Synopsis

  • Inducible gene expression systems are crucial for synthetic biology, particularly in developing biosensors that can aid diagnostics and enhance microbial cell factories.
  • A new genome-wide approach identifies and validates 15 functional biosensors, creating a workflow that streamlines engineering efforts and shows versatility across different host organisms.
  • The study also uncovers new interactions between these sensors and relevant compounds using a large library, paving the way for the detection of more biological molecules in future research.

Article Abstract

Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, we address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. We construct and validate 15 functional biosensors, provide a characterisation workflow to facilitate forward engineering efforts, exemplify their broad-host-range applicability, and demonstrate their utility in enzyme screening. Previously uncharacterised interactions between sensors and compounds of biological relevance are identified by employing the largest reported library of metabolite-responsive biosensors in an automated high-throughput screen. With the rapidly growing genomic data these innovative capabilities offer a platform to vastly increase the number of biologically detectable molecules.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057948PMC
http://dx.doi.org/10.1038/s41467-020-14941-6DOI Listing

Publication Analysis

Top Keywords

genome-wide approach
8
inducible gene
8
gene expression
8
expression systems
8
compounds biological
8
approach identification
4
identification characterisation
4
characterisation metabolite-inducible
4
metabolite-inducible systems
4
systems inducible
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!