Futuristic CRISPR-based biosensing in the cloud and internet of things era: an overview

Abstract

Biosensors-based devices are transforming medical diagnosis of diseases and monitoring of patient signals. The development of smart and automated molecular diagnostic tools equipped with biomedical big data analysis, cloud computing and medical artificial intelligence can be an ideal approach for the detection and monitoring of diseases, precise therapy, and storage of data over the cloud for supportive decisions. This review focused on the use of machine learning approaches for the development of futuristic CRISPRbiosensors based on microchips and the use of Internet of Things for wireless transmission of signals over the cloud for support decision making. The present review also discussed the discovery of CRISPR, its usage as a gene editing tool, and the CRISPRbased biosensors with high sensitivity of Attomolar (10 −18 M), Femtomolar (10 −15 M) and Picomolar (10 −12 M) in comparison to conventional biosensors with sensitivity of nanomolar 10 −9 M and micromolar 10 −3 M. Additionally, the review also outlines limitations and open research issues in the current state of CRISPR-based biosensing applications.

Notice of Retraction: AI Techniques for COVID-19

“…A virtual stockpiling medium or gadget is typically likewise connected with virtual machines. A virtual machine appears to the client as an undeniable PC with a working framework and all the fancy odds and ends, and obviously with its very own capacity drive [142] , [143] .…”

CRISPR-Cas based virus detection: Recent advances and perspectives

“…Simplified operation steps or POC test development may be the solution for complete true field detection. In order to facilitate the application of CRISPR-Cas in POC or field-deployable settings, integration of CRISPR-Cas with other platforms such as LFA, microfluidics, biochip, nanotechnology, mobile phone technology, cloud computing and artificial intelligence will be an effective solution ( Berg et al, 2015 ; Ibrahim et al, 2020 ; Quesada-González and Merkoçi, 2017 ; Weiss et al, 2020 ). Microfluidics has provided a powerful tool for the development of point-of-care detection.…”

CRISPR-based detection of SARS-CoV-2: A review from sample to result

“…Enhancing the CRISPR sensing performance. Nanomaterials and artificial intelligence have been introduced to enhance the performance of CRISPR sensing with respect to signal enhancement ( Rabiee et al, 2020 ) and classification ( Ibrahim et al, 2020 ). For instance, Bao et al developed a simple visual detection system coupled with quantum dots as an ultra-brightness indicator and a CRISPR-Cas12a assay for isothermal viral DNA target sensing.…”

“…Furthermore, point of care sensing technology can be combined with artificial intelligence (AI) for improved data storage, classification, and sharing ( Kaushik et al, 2020 ). For instance, Ibrahim et al combined the internet of thing technology and machine learning with CRISPR sensing for wireless transmission of signals over the cloud to support decision making ( Ibrahim et al, 2020 ). This opens up many possibilities for further enhancing the CRISPR sensing performance in the future.…”

“…The mechanism of Cas12, 13, or 14 systems, which are programmed by guide RNA, allows for single-base specificity compared to the amplification-based molecular diagnostics techniques such as PCR ( Gootenberg et al, 2017 ). The general CRISPR-based nucleic acid detection methods were reviewed in several previous studies ( Anson et al, 2020 ; Ibrahim et al, 2020 ; van Dongen et al, 2020 ; Wang et al, 2020c ). Due to the growing interest in developing CRISPR-based systems for sensitive and specific diagnostics of SARS-CoV-2 amid the ongoing COVID-19 pandemic, in this work, we specifically focused on the recent progress of applying Cas12 and Cas13 for SARS-CoV-2 detection and reviewed their assay, readout methods, and the system integration.…”