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End-to-end computational approach to the design of RNA biosensors for detecting miRNA biomarkers of cervical cancer 被引量:2
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作者 Priyannth Ramasami S.Baabu Shivaramakrishna Srinivasan +4 位作者 Swetha Nagarajan Sangeetha Muthamilselvan Thamarai Selvi Raghavv R.Suresh ashok palaniappan 《Synthetic and Systems Biotechnology》 SCIE 2022年第2期802-814,共13页
Cervical cancer is a global public health subject as it affects women in the reproductive ages,and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50%mortality rate.Relativel... Cervical cancer is a global public health subject as it affects women in the reproductive ages,and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50%mortality rate.Relatively scant awareness and limited access to effective diagnosis have led to this enormous disease burden,calling for point-of-care,minimally invasive diagnosis methods.Here,an end-to-end quantitative unified pipeline for diagnosis has been developed,beginning with identification of optimal biomarkers,concurrent design of toehold switch sensors,and finally simulation of the designed diagnostic circuits to assess performance.Using miRNA expression data in the public domain,we identified miR-21-5p and miR-20a-5p as blood-based miRNA biomarkers specific to early-stage cervical cancer employing a multi-tier algorithmic screening.Synthetic riboregulators called toehold switches specific to the biomarker panel were then designed.To predict the dynamic range of toehold switches for use in genetic circuits as biosensors,we used a generic grammar of these switches,and built a neural network model of dynamic range using thermodynamic features derived from mRNA secondary structure and interaction.Second-generation toehold switches were used to overcome the design challenges associated with miRNA biomarkers.The resultant model yielded an adj.R^(2)~0.71,outperforming earlier models of toehold-switch dynamic range.Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers.Simulations showed a linear response between 10 nM and 100 nM before saturation.Our study demonstrates an end-to-end computational workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic/nucleic-acid signatures.The approach has the potential to replace iterative experimental trial and error,and focus time,money,and efforts.All software including the toehold grammar parser,neural network model and reaction kinetics simulation are available as open-source software(https://github.com/SASTRA-iGEM2019)under GNU GPLv3 licence. 展开更多
关键词 Cervical cancer biosensor miRNA biomarker Synthetic toehold switches Genetic circuit design Reaction network modelling Toehold efficacy modelling Toehold switch grammar Machine learning
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