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Engineering constructed of high selectivity dexamethasone aptamer based on truncation and mutation technology.

ABSTRACT: Various biosensors based on aptamers are currently the most popular rapid detection approaches, but the performance of these sensors is closely related to the affinity of aptamers. In this work, a strategy for constructed high-affinity aptamer was proposed. By truncating the bases flanking the 59 nt dexamethasones (DEX) original aptamer sequence to improve the sensitivity of the aptamer to DEX, and then base mutation was introduced to further improve the sensitivity and selectivity of aptamers. Finally, the 33 nt aptamer Apt-M13 with G-quadruplex structures was obtained. The dissociation constant (K_d) was determined to be 200 nM by Graphene oxide (GO)-based fluorometry. As-prepared Apt-M13 was used for a label-free colorimetric aptamer sensor based on gold nanoparticles, the LOD was 3.2-fold lower than the original aptamer described in previous works. The anti-interference ability of DEX analogs is also further improved. It indicates that truncation technology effectively improves the specificity of the aptamer to DEX in this work, and the introduction of mutation further improves the affinity and selectivity of the aptamer to DEX. Therefore, the proposed aptamer optimization method is also expected to become a general strategy for various aptamer sequences.

SUBMITTER: Qin Y

PROVIDER: S-EPMC9513367 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Engineering constructed of high selectivity dexamethasone aptamer based on truncation and mutation technology.

Qin Yadi Y Qin Yanan Y Bubiajiaer Hayilati H Chen Fengxia F Yao Jun J Zhang Minwei M

Frontiers in bioengineering and biotechnology 20220913

Various biosensors based on aptamers are currently the most popular rapid detection approaches, but the performance of these sensors is closely related to the affinity of aptamers. In this work, a strategy for constructed high-affinity aptamer was proposed. By truncating the bases flanking the 59 nt dexamethasones (DEX) original aptamer sequence to improve the sensitivity of the aptamer to DEX, and then base mutation was introduced to further improve the sensitivity and selectivity of aptamers. ...[more]

PMID: 36177181

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Project description:BackgroundThe interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.Methodology/principal findingsWe present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.Conclusions/significanceWe describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Project description:Purpose: There is a need to identify new biomarkers of radiation exposure both for use in the development of biodosimetry blood diagnostics for radiation exposure and for clinical use as markers of radiation injury. In the current study, a novel high-throughput proteomics screening approach was used to identify proteomic markers of radiation exposure in the plasma of total body irradiated mice. A subset panel of significantly altered proteins was selected to build predictive models of radiation exposure and received radiation dose useful for population screening in a future radiological or nuclear event. Methods: Female C57BL6 Mice of 8-14 weeks of age received a single total body irradiation (TBI) dose of 2, 3.5, 8 Gy or sham radiation and plasma was collected by cardiac puncture at days 1, 3, and 7 post-exposure. Plasma was then screened using the aptamer-based SOMAscan proteomic assay technology, for changes in expression of 1,310 protein analytes. A subset panel of protein biomarkers which demonstrated significant changes (p < 0.05) in expression following radiation exposure were used to build predictive models of radiation exposure and radiation dose. Results: Detectable values were obtained for all 1,310 proteins included in the SOMAscan assay. For the Control vs. Radiation model, the top predictive proteins were immunoglobulin heavy constant mu (IGHM), mitogen-activated protein kinase 14 (MAPK14), ectodysplasin A2 receptor (EDA2R) and solute carrier family 25 member 18 (SLC25A18). For the Control vs. Dose model, the top predictive proteins were cyclin dependent kinase 2/cyclin A2 (CDK2. CCNA2), E-selectin (SELE), BCL2 associated agonist of cell death (BAD) and SLC25A18. Following model validation with a training set of samples, both models tested with a new sample cohort had overall predictive accuracies of 85% and 73% for the Control vs. Radiation and Control vs. Dose models respectively. Conclusion: The SOMAscan proteomics platform is a useful screening tool to evaluate changes in biomarker expression. In our study we were able to identify a novel panel of radiation responsive proteins useful for predicting whether an animal had received a radiation exposure and to what dose they had received. Such diagnostic tools are needed for future medical management of radiation exposures.

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Engineering constructed of high selectivity dexamethasone aptamer based on truncation and mutation technology.

Publications

Engineering constructed of high selectivity dexamethasone aptamer based on truncation and mutation technology.

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