Aptamers are a class of single-stranded (ss) nucleic acid molecules generated through Systematic Evolution of Ligands by Exponential Enrichment (SELEX) that involves iterations of time-consuming and tedious selection, amplification, and enrichment steps. To compensate for the drawbacks of conventional SELEX, we have devised an in-silico methodology that facilitates a cost-effective and facile manner of aptamer selection. Here, we report the isolation of DNA aptamers against androgen receptors (ARs) using androgen response elements (ARE) that possess natural affinity toward AR. A virtual library of ARE sequences was prepared and subjected to a stringent selection criterion to generate a sequence pool having stable hairpin conformations and high GC content. The 3D-structures of the selected ss AREs were modeled and screened through rigid docking and molecular dynamic (MD) simulation to examine their potency as potential AR binders. The predicted sequences were further validated using direct enzyme-linked aptasorbent assay (ELASA), which includes the measurement of their binding affinity, specificity, and target discrimination properties under complex biological enviroments. A short, 15 nucleotides (nts), ssDNA aptamer, termed ARapt1 with the estimated Kd value of 5.5 ± 3 nm, was chosen as the most prominent aptamer against AR based on the coherence of both the in-silico and in-vitro evaluation results. The high target-binding affinity and selectivity of ARapt1 signify its potential use as a versatile tool in diagnostic applications relevant to prostate cancer and related diseases.
Clustered regularly interspaced short palindromic repeats (CRISPR) have established itself as a frontier technology in genetic engineering. Researchers have successfully used the CRISPR/Cas system as precise gene editing tools and have further expanded their scope beyond both imaging and diagnostic applications. The most prominent utility of CRISPR is its capacity for gene therapy, serving as the contemporary, disease-modifying drug at the genetic level of human medical disorders. Correcting these diseases using CRISPR-based gene editing has developed to the extent of preclinical trials and possible patient treatments. A major impediment in actualizing this is the complications associated with in vivo delivery of the CRISPR/Cas complex. Currently, only the viral vectors (e.g., lentivirus) and non-viral encapsulation (e.g., lipid particles, polymer-based, and gold nanoparticles) techniques have been extensively reviewed, neglecting the efficiency of direct delivery. However, the direct delivery of CRISPR/Cas for in vivo gene editing therapies is an intricate process with numerous drawbacks. Hence, this paper discusses in detail both the need and the strategies that can potentially improve the direct delivery aspects of CRISPR/Cas biomolecules for gene therapy of human diseases. Here, we focus on enhancing the molecular and functional features of the CRISPR/Cas system for targeted in vivo delivery such as on-site localization, internalization, reduced immunogenicity, and better in vivo stability. We additionally emphasize the CRISPR/Cas complex as a multifaceted, biomolecular vehicle for co-delivery with therapeutic agents in targeted disease treatments. The delivery formats of efficient CRISPR/Cas systems for human gene editing are also briefly elaborated.
Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.
Leptospirosis is a potentially life-threatening zoonosis caused by pathogenic Leptospira and for rapid diagnostics, direct detection is desirable. LipL32 protein is the most suitable biomarker for direct detection. DNA aptamers are sought to be generated against LipL32 by Systemic Evolution of Ligands via Exponential Enrichment (SELEX). LepDapt-5a is the most potent aptamer candidate among all the candidates, as determined by direct Enzyme-linked Aptasorbent Assay (ELASA). LepDapt-5a was predicted to form a G-quadruplex structure as predicted by QGRS Mapper and validated experimentally by direct ELASA. The diagnostic potential of the aptamer was further tested on a direct and sandwich ELASA platform. A LOD of 106 mL-1 and 105 mL-1 were estimated by direct and sandwich ELASA platforms, respectively, which are within the range associated with leptospiremia levels. The dot blot assay developed was able to attain a LOD of 104 CFU mL-1 against pathogenic Leptospira, which is also within the leptospiremia level. This is the first-ever DNA aptamer and hybrid-heterodimeric aptamer constructed against LipL32. The diagnostic potentiality of the LepDapt-5a DNA aptamer was proven on three major diagnostic platforms, which are direct ELASA, sandwich ELASA, and aptamer-based dot assay.