ArticlePLoS computational biology2020
Precise determination of input-output mapping for multimodal gene circuits using data from transient transfection.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells.Molecular systems biology · 2022Article
- Control of mammalian cell-based devices with genetic programming.Current opinion in systems biology · 2021Article
- 'Statistical Irreproducibility' Does Not Improve with Larger Sample Size: How to Quantify and Address Disease Data Multimodality in Human and Animal Research.Journal of personalized medicine · 2021Article
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2 authors.
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Abstract
The mapping of molecular inputs to their molecular outputs (input/output, I/O mapping) is an important characteristic of gene circuits, both natural and synthetic. Experimental determination of such mappings for synthetic circuits is best performed using stably integrated genetic constructs. In mammalian cells, stable integration of complex circuits is a time-consuming process that hampers rapid characterization of multiple circuit variants. On the other hand, transient transfection is quick. However, it is an extremely noisy process and it is unclear whether the obtained data have any relevance to the input/output mapping of a circuit obtained in the case of a stable integration. Here we describe a data processing workflow, Peakfinder algorithm for flow cytometry data (PFAFF), that allows extracting precise input/output mapping from single-cell protein expression data gathered by flow cytometry after a transient transfection. The workflow builds on the numerically-proven observation that the multivariate modes of input and output expression of multi-channel flow cytometry datasets, pre-binned by the expression level of an independent transfection reporter gene, harbor cells with circuit gene copy numbers distributions that depend deterministically on the properties of a bin. We validate our method by simulating flow cytometry data for seven multi-node circuit architectures, including a complex bi-modal circuit, under stable integration and transient transfection scenarios. The workflow applied to the simulated transient transfection data results in similar conclusions to those reached with simulated stable integration data. This indicates that the input/output mapping derived from transient transfection data using our method is an excellent approximation of the ground truth. Thus, the method allows to determine input/output mapping of complex gene network using noisy transient transfection data.
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