Dataset Information

Advances in CRISPR Delivery Methods: Perspectives and Challenges.

ABSTRACT: With the advent of new genome editing technologies and the emphasis placed on their optimization, the genetic and phenotypic correction of a plethora of diseases sit on the horizon. Ideally, genome editing approaches would provide long-term solutions through permanent disease correction instead of simply treating patients symptomatically. Although various editing machinery options exist, the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated protein) editing technique has emerged as the most popular due to its high editing efficiency, simplicity, and affordability. However, while CRISPR technology is gradually being perfected, optimization is futile without accessible, effective, and safe delivery to the desired cell or tissue. Therefore, it is important that scientists simultaneously focus on inventing and improving delivery modalities for editing machinery as well. In this review, we will discuss the critical details of viral and nonviral delivery systems, including payload, immunogenicity, efficacy in delivery, clinical application, and future directions.

SUBMITTER: Demirci S

PROVIDER: S-EPMC9835311 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Advances in CRISPR Delivery Methods: Perspectives and Challenges.

Demirci Selami S Essawi Khaled K Germino-Watnick Paula P Liu Xiong X Hakami Waleed W Tisdale John F JF

The CRISPR journal 20221001 5

With the advent of new genome editing technologies and the emphasis placed on their optimization, the genetic and phenotypic correction of a plethora of diseases sit on the horizon. Ideally, genome editing approaches would provide long-term solutions through permanent disease correction instead of simply treating patients symptomatically. Although various editing machinery options exist, the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated protein) editin ...[more]

PMID: 36260301

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Project description:The World Health Organization (WHO) estimated that pathogens like Escherichia coli, primarily linked to food and water contamination, are associated with 485,000 deaths from diarrheal diseases annually, translating to a staggering worldwide economic loss of nearly 12 billion USD per annum. International organizations like the WHO and United Nations Children's Fund (UNICEF) have established related guidelines and criteria for pathogenic detection technologies and driving the search for innovative and efficient detection methods. This comprehensive review examines the trajectory of waterborne pathogenic bacteria detection technologies from traditional techniques, i.e., culture-based methods, to current detection methods including various forms of polymerase chain reaction (PCR) techniques [qualitative real-time PCR, digital PCR, ELISA, loop-mediated isothermal amplification, next-generation sequencing (NGS)] and to emerging techniques, i.e., biosensors and artificial intelligence (AI). The scope of the review paper focuses on waterborne pathogenic bacteria that are recognized as human pathogens, posing tangible threats to public health through waterborne. The detection techniques' merits, constraints, research gaps and future perspectives are critically discussed. Advancements in digital droplet PCR, NGS and biosensors have significantly improved sensitivity and specificity, revolutionizing pathogen detection. Additionally, the integration of artificial intelligence (AI) with these technologies has enhanced detection accuracy, enabling real-time analysis of large datasets. Molecular-based methods and biosensors show promise for efficient water quality monitoring, especially in resource-constrained settings, but on-site practical implementation remains a challenge. The pairwise comparison metrics used in this review also offer valuable insights into quick evaluation on the advantages, limitations and research gaps of various techniques, focusing on their applicability in field settings and timely analyses. Future research efforts should focus on developing robust, cost-effective and user-friendly techniques for routine waterborne bacteria monitoring, ultimately safeguarding global water supplies and public health, with AI and data analysis playing a crucial role in advancing these methods for a safer environment.

Project description:The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Dataset Information

Advances in CRISPR Delivery Methods: Perspectives and Challenges.

Publications

Advances in CRISPR Delivery Methods: Perspectives and Challenges.

Similar Datasets

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