{"title":"Experimental evidence for constraints in amplitude-timescale co-variation of a biomolecular pulse generating circuit design","authors":"Abhilash Patel, Shaunak Sen","doi":"10.1049/iet-syb.2019.0123","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Understanding constraints on the functional properties of biomolecular circuit dynamics, such as the possible variations of amplitude and timescale of a pulse, is an important part of biomolecular circuit design. While the amplitude-timescale co-variations of the pulse in an incoherent feedforward loop have been investigated computationally using mathematical models, experimental support for any such constraints is relatively unclear. Here, the authors address this using experimental measurement of an existing pulse generating incoherent feedforward loop circuit realisation in the context of a standard mathematical model. They characterise the trends of co-variation in the pulse amplitude and rise time computationally by randomly exploring the parameter space. They experimentally measured the co-variation by varying inducers and found that larger amplitude pulses have a slower rise time. They discuss the gap between the experimental measurements and predictions of the standard model, highlighting model additions and other biological factors that might bridge the gap.</p></div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"14 5","pages":"217-222"},"PeriodicalIF":1.9000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/79/66/SYB2-14-217.PMC9272780.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/iet-syb.2019.0123","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding constraints on the functional properties of biomolecular circuit dynamics, such as the possible variations of amplitude and timescale of a pulse, is an important part of biomolecular circuit design. While the amplitude-timescale co-variations of the pulse in an incoherent feedforward loop have been investigated computationally using mathematical models, experimental support for any such constraints is relatively unclear. Here, the authors address this using experimental measurement of an existing pulse generating incoherent feedforward loop circuit realisation in the context of a standard mathematical model. They characterise the trends of co-variation in the pulse amplitude and rise time computationally by randomly exploring the parameter space. They experimentally measured the co-variation by varying inducers and found that larger amplitude pulses have a slower rise time. They discuss the gap between the experimental measurements and predictions of the standard model, highlighting model additions and other biological factors that might bridge the gap.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.