Structural identification of unate-like genetic network models from time-lapse protein concentration measurements

Porreca, Riccardo; Cinquemani, Eugenio; Lygeros, John; Ferrari-Trecate, Giancarlo

doi:10.1109/cdc.2010.5717922

Cited by 4 publications

(4 citation statements)

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“…In other words, the promoter activities are the output of a computational procedure taking the approximate experimental curves as input. By contrast, direct methods like those used in WellInverter work the other way around; they treat the promoter activity as the input giving rise to an observed output, the fluorescence time-series data [18–20, 22]. This has the conceptual advantage of allowing smoothing to be defined as a regularized data fitting problem on the quantity to be estimated, the promoter activity, and leads to robust results.…”

Section: Discussionmentioning

confidence: 99%

WellInverter: a web application for the analysis of fluorescent reporter gene data

et al. 2019

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Background Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion. Results We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene. Conclusions The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line. Electronic supplementary material The online version of this article (10.1186/s12859-019-2920-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

WellInverter: a web application for the analysis of fluorescent reporter gene data

et al. 2019

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“…In addition, varying of gene copy number with time (e.g., due to kinetics of plasmid division) should be accounted for by both experiments and theoretical models. A particular challenge would be to reconstruct regulatory networks from sole protein dynamics data, that are becoming more and more available [35]. Development of advanced theoretical methods for such reconstruction, analogous to those for reverse engineering of gene networks from gene expression data, may thus become a necessity in the future.…”

Section: Discussionmentioning

confidence: 99%

Effects of Population Dynamics on Establishment of a Restriction-Modification System in a Bacterial Host

et al. 2019

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In vivo dynamics of protein levels in bacterial cells depend on both intracellular regulation and relevant population dynamics. Such population dynamics effects, e.g., interplay between cell and plasmid division rates, are, however, often neglected in modeling gene expression regulation. Including them in a model introduces additional parameters shared by the dynamical equations, which can significantly increase dimensionality of the parameter inference. We here analyse the importance of these effects, on a case of bacterial restriction-modification (R-M) system. We redevelop our earlier minimal model of this system gene expression regulation, based on a thermodynamic and dynamic system modeling framework, to include the population dynamics effects. To resolve the problem of effective coupling of the dynamical equations, we propose a “mean-field-like” procedure, which allows determining only part of the parameters at a time, by separately fitting them to expression dynamics data of individual molecular species. We show that including the interplay between kinetics of cell division and plasmid replication is necessary to explain the experimental measurements. Moreover, neglecting population dynamics effects can lead to falsely identifying non-existent regulatory mechanisms. Our results call for advanced methods to reverse-engineer intracellular regulation from dynamical data, which would also take into account the population dynamics effects.

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“…Moreover, the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring dynamical models of the expression of reporter genes for their interpretation. Several methods have been proposed to process the fluorescence and absorbance signals and estimate time-varying promoter activities and protein concentrations from the data ( Aïchaoui et al , 2012 ; Bansal et al , 2012 ; de Jong et al , 2010 ; Finkenstädt et al , 2008 ; Leveau and Lindow, 2001 ; Lichten et al , 2014 ; Porreca et al , 2010 ; Ronen et al , 2002 ; Wang et al , 2008 ). The methods differ in the scope of the estimation problems considered, some being restricted to the inference of promoter activities and others also considering mRNA and protein concentrations.…”

Section: Introductionmentioning

confidence: 99%

“…We formulate the estimation problems in the classical framework of regularized linear inversion ( Bertero, 1989 ; de Nicolao et al , 1997 ; Wahba, 1990 ), which gives access to a range of powerful tools for robust estimation. Contrary to the related work of Bansal et al (2012) and Porreca et al (2010) , we consider not only the inference of promoter activities, but also of growth rates and protein concentrations. Moreover, no restrictions are imposed that limit the practical applicability of the approach.…”

Section: Introductionmentioning

confidence: 99%

Robust reconstruction of gene expression profiles from reporter gene data using linear inversion

et al. 2015

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Motivation: Time-series observations from reporter gene experiments are commonly used for inferring and analyzing dynamical models of regulatory networks. The robust estimation of promoter activities and protein concentrations from primary data is a difficult problem due to measurement noise and the indirect relation between the measurements and quantities of biological interest.Results: We propose a general approach based on regularized linear inversion to solve a range of estimation problems in the analysis of reporter gene data, notably the inference of growth rate, promoter activity, and protein concentration profiles. We evaluate the validity of the approach using in silico simulation studies, and observe that the methods are more robust and less biased than indirect approaches usually encountered in the experimental literature based on smoothing and subsequent processing of the primary data. We apply the methods to the analysis of fluorescent reporter gene data acquired in kinetic experiments with Escherichia coli. The methods are capable of reliably reconstructing time-course profiles of growth rate, promoter activity and protein concentration from weak and noisy signals at low population volumes. Moreover, they capture critical features of those profiles, notably rapid changes in gene expression during growth transitions.Availability and implementation: The methods described in this article are made available as a Python package (LGPL license) and also accessible through a web interface. For more information, see https://team.inria.fr/ibis/wellinverter.Contact: Hidde.de-Jong@inria.frSupplementary information: Supplementary data are available at Bioinformatics online.

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Structural identification of unate-like genetic network models from time-lapse protein concentration measurements

Cited by 4 publications

References 39 publications

WellInverter: a web application for the analysis of fluorescent reporter gene data

WellInverter: a web application for the analysis of fluorescent reporter gene data

Effects of Population Dynamics on Establishment of a Restriction-Modification System in a Bacterial Host

Robust reconstruction of gene expression profiles from reporter gene data using linear inversion

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