Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains,from pathogen detection to single cell transcriptomics analysis.The many applications of nucleic a...Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains,from pathogen detection to single cell transcriptomics analysis.The many applications of nucleic acid detection and identification are mostly carried out by PCR techniques,sequencing,and their derivatives used at large scale.However,these methods’limitations on speed,cost,complexity and specificity have motivated the development of innovative detection methods among which nucleic acid biosensing technologies seem promising.Toehold switches are a particular class of RNA sensing devices relying on a conformational switch of secondary structure induced by the pairing of the detected trigger RNA with a de novo designed synthetic sensing mRNA molecule.Here we describe a streamlined methodology enabling the development of such a sensor for the RNA-mediated detection of an endangered plant species in a cell-free reaction system.We applied this methodology to help identify the rosewood Dalbergia maritima,a highly trafficked wood,whose protection is limited by the capacity of the authorities to distinguish protected logs from other unprotected but related species.The streamlined pipeline presented in this work is a versatile framework enabling cheap and rapid development of new sensors for custom RNA detection.展开更多
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
文摘Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains,from pathogen detection to single cell transcriptomics analysis.The many applications of nucleic acid detection and identification are mostly carried out by PCR techniques,sequencing,and their derivatives used at large scale.However,these methods’limitations on speed,cost,complexity and specificity have motivated the development of innovative detection methods among which nucleic acid biosensing technologies seem promising.Toehold switches are a particular class of RNA sensing devices relying on a conformational switch of secondary structure induced by the pairing of the detected trigger RNA with a de novo designed synthetic sensing mRNA molecule.Here we describe a streamlined methodology enabling the development of such a sensor for the RNA-mediated detection of an endangered plant species in a cell-free reaction system.We applied this methodology to help identify the rosewood Dalbergia maritima,a highly trafficked wood,whose protection is limited by the capacity of the authorities to distinguish protected logs from other unprotected but related species.The streamlined pipeline presented in this work is a versatile framework enabling cheap and rapid development of new sensors for custom RNA detection.
文摘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.
