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Reconstructing promoter activity from Lux bioluminescent reporters

Iqbal, Mudassar; Doherty, Neil; Page, Anna M.L.; Qazi, Saara N.A.; Ajmera, Ishan; Lund, Peter A.; Kypraios, Theodore; Scott, David J.; Hill, Philip J.; Stekel, Dov J.

Reconstructing promoter activity from Lux bioluminescent reporters Thumbnail


Authors

Mudassar Iqbal

Anna M.L. Page

Saara N.A. Qazi

Ishan Ajmera

Peter A. Lund

DAVID SCOTT DAVID.SCOTT@NOTTINGHAM.AC.UK
Associate Professor & Reader in Physical Biochemistry

PHIL HILL phil.hill@nottingham.ac.uk
Associate Professor

DOV STEKEL DOV.STEKEL@NOTTINGHAM.AC.UK
Professor of Computational Biology



Abstract

The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used for whole cell biosensors, or in real time with live animals without the need for euthanasia. However, correct interpretation of bioluminescent data is limited: the bioluminescence is different from gene expression because of nonlinear molecular and enzyme dynamics of the Lux system. We have developed a computational approach that, for the first time, allows users of Lux assays to infer gene transcription levels from the light output. This approach is based upon a new mathematical model for Lux activity, that includes the actions of LuxAB, LuxEC and Fre, with improved mechanisms for all reactions, as well as synthesis and turn-over of Lux proteins. The model is calibrated with new experimental data for the LuxAB and Fre reactions from Photorhabdus luminescens --- the source of modern Lux reporters --- while literature data has been used for LuxEC. Importantly, the data show clear evidence for previously unreported product inhibition for the LuxAB reaction. Model simulations show that predicted bioluminescent profiles can be very different from changes in gene expression, with transient peaks of light output, very similar to light output seen in some experimental data sets. By incorporating the calibrated model into a Bayesian inference scheme, we can reverse engineer promoter activity from the bioluminescence. We show examples where a decrease in bioluminescence would be better interpreted as a switching off of the promoter, or where an increase in bioluminescence would be better interpreted as a longer period of gene expression. This approach could benefit all users of Lux technology.

Journal Article Type Article
Acceptance Date Aug 19, 2017
Publication Date Sep 18, 2017
Deposit Date Sep 7, 2017
Publicly Available Date Sep 18, 2017
Journal PLoS Computational Biology
Print ISSN 1553-734X
Electronic ISSN 1553-734X
Publisher Public Library of Science
Peer Reviewed Peer Reviewed
Volume 13
Issue 9
Article Number e1005731
DOI https://doi.org/10.1371/journal.pcbi.1005731
Public URL https://nottingham-repository.worktribe.com/output/883445
Publisher URL http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005731

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