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

CRISPR revolution: Unleashing precision pathogen detection to safeguard public health and food safety

Foodborne pathogens represent a significant challenge to global food safety, causing widespread illnesses and economic losses. The growing complexity of food supply chains and the emergence of antimicrobial resistance necessitate rapid, sensitive, and portable diagnostic tools. CRISPR technology has emerged as a transformative solution, offering unparalleled precision and adaptability in pathogen detection. This review explores CRISPR's role in addressing critical gaps in traditional and modern diagnostic methods, emphasizing its advantages in sensitivity, specificity, and scalability. CRISPR-based diagnostics, such as Cas12 and Cas13 systems, enable rapid detection of bacterial and viral pathogens, as well as toxins and chemical hazards, directly in food matrices. Their integration with isothermal amplification techniques and portable biosensors enhances field applicability, making them ideal for decentralized and real-time testing. Additionally, CRISPR's potential extends beyond food safety, contributing to public health efforts by monitoring antimicrobial resistance and supporting One Health frameworks. Despite these advancements, challenges remain, including issues with performance in complex food matrices, scalability, and regulatory barriers. This review highlights future directions, including AI integration for assay optimization, the development of universal CRISPR platforms, and the adoption of sustainable diagnostic solutions. By tackling these challenges, CRISPR has the potential to redefine global food safety standards and create a more resilient food system. Collaborative research and innovation will be critical to fully unlocking its transformative potential in food safety and public health.

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR

The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to precisely cleave problematic regions within DNA sequences. This groundbreaking technology holds immense potential for the development of targeted therapies for a wide range of diseases, including cancers, genetic disorders, and hereditary diseases. CRISPR-Cas9 based genome editing is a multi-step process such as designing a precise gRNA, selecting the appropriate Cas protein, and thoroughly evaluating both on-target and off-target activity of the Cas9-gRNA complex. To ensure the accuracy and effectiveness of CRISPR-Cas9 system, after the targeted DNA cleavage, the process requires careful analysis of the resultant outcomes such as indels and deletions. Following the success of artificial intelligence (AI) in various fields, researchers are now leveraging AI algorithms to catalyze and optimize the multi-step process of CRISPR-Cas9 system. To achieve this goal AI-driven applications are being integrated into each step, but existing AI predictors have limited performance and many steps still rely on expensive and time-consuming wet-lab experiments. The primary reason behind low performance of AI predictors is the gap between CRISPR and AI fields. Effective integration of AI into multi-step CRISPR-Cas9 system demands comprehensive knowledge of both domains. This paper bridges the knowledge gap between AI and CRISPR-Cas9 research. It offers a unique platform for AI researchers to grasp deep understanding of the biological foundations behind each step in the CRISPR-Cas9 multi-step process. Furthermore, it provides details of 80 available CRISPR-Cas9 system-related datasets that can be utilized to develop AI-driven applications. Within the landscape of AI predictors in CRISPR-Cas9 multi-step process, it provides insights of representation learning methods, machine and deep learning methods trends, and performance values of existing 50 predictive pipelines. In the context of representation learning methods and classifiers/regressors, a thorough analysis of existing predictive pipelines is utilized for recommendations to develop more robust and precise predictive pipelines.

Recent developments and future directions in point-of-care next-generation CRISPR-based rapid diagnosis

The demand for sensitive, rapid, and affordable diagnostic techniques has surged, particularly following the COVID-19 pandemic, driving the development of CRISPR-based diagnostic tools that utilize Cas effector proteins (such as Cas9, Cas12, and Cas13) as viable alternatives to traditional nucleic acid-based detection methods. These CRISPR systems, often integrated with biosensing and amplification technologies, provide precise, rapid, and portable diagnostics, making on-site testing without the need for extensive infrastructure feasible, especially in underserved or rural areas. In contrast, traditional diagnostic methods, while still essential, are often limited by the need for costly equipment and skilled operators, restricting their accessibility. As a result, developing accessible, user-friendly solutions for at-home, field, and laboratory diagnostics has become a key focus in CRISPR diagnostic innovations. This review examines the current state of CRISPR-based diagnostics and their potential applications across a wide range of diseases, including cancers (e.g., colorectal and breast cancer), genetic disorders (e.g., sickle cell disease), and infectious diseases (e.g., tuberculosis, malaria, Zika virus, and human papillomavirus). Additionally, the integration of machine learning (ML) and artificial intelligence (AI) to enhance the accuracy, scalability, and efficiency of CRISPR diagnostics is discussed, alongside the challenges of incorporating CRISPR technologies into point-of-care settings. The review also explores the potential for these cutting-edge tools to revolutionize disease diagnosis and personalized treatment in the future, while identifying the challenges and future directions necessary to address existing gaps in CRISPR-based diagnostic research.

Harnessing CRISPR/Cas Systems for DNA and RNA Detection: Principles, Techniques, and Challenges

The emergence of CRISPR/Cas systems has revolutionized the field of molecular diagnostics with their high specificity and sensitivity. This review provides a comprehensive overview of the principles and recent advancements in harnessing CRISPR/Cas systems for detecting DNA and RNA. Beginning with an exploration of the molecular mechanisms of key Cas proteins underpinning CRISPR/Cas systems, the review navigates the detection of both pathogenic and non-pathogenic nucleic acids, emphasizing the pivotal role of CRISPR in identifying diverse genetic materials. The discussion extends to the integration of CRISPR/Cas systems with various signal-readout techniques, including fluorescence, electrochemical, and colorimetric, as well as imaging and biosensing methods, highlighting their advantages and limitations in practical applications. Furthermore, a critical analysis of challenges in the field, such as target amplification, multiplexing, and quantitative detection, underscores areas requiring further refinement. Finally, the review concludes with insights into the future directions of CRISPR-based nucleic acid detection, emphasizing the potential of these systems to continue driving innovation in diagnostics, with broad implications for research, clinical practice, and biotechnology.

Bibliometric analysis on CRISPR/Cas: a potential Sherlock Holmes for disease detection

CRISPR has revolutionized illness detection by using precision gene editing to identify specific sequences in recent years. Using the Scopus database, this study performs a comprehensive bibliometric analysis, looking at academic papers on CRISPR that were published between 1992 and 2023. After screening a dataset of 1407 articles using Zotero, trends in annual publishing, citation patterns, author affiliations, and keyword co-occurrence are revealed using analysis tools such as VOSviewer, RStudio, and MS Excel. According to the report, there was only one CRISPR publication in 1992. By 2017, there were a meager 64 papers. Nonetheless, there is a notable upsurge between 2018 and 2023. Leading nations involved in CRISPR-based illness detection research include Germany, the United States, China, India, and the United Kingdom. Chongqing University Three Gorges Hospital, Chongqing University Medical University, and Chongqing University Bioengineering College are a few of the top institutions. With the greatest publication numbers (1688 and 1616) and strong total link strengths (TLS) of 42 and 77, respectively, authors Liu, C., and Li, Y., stand out. The field with the greatest citation counts as of 2023 is Broughton's 2020 study on CRISPR-based SARS-CoV-2 detection in Nature Biotechnology, with 1598 citations. Biosensors and Bioelectronics comprise 14.99% of papers. Researchers, decision-makers, and interested parties can use this thorough summary to help them make well-informed decisions about future CRISPR-based disease detection studies.

CRISPR/Cas12-based electrochemical biosensors for clinical diagnostic and food monitoring

Each organism has a unique sequence of nitrogenous bases in in the form of DNA or RNA which distinguish them from other organisms. This characteristic makes nucleic acid-based detection extremely selective and compare to other molecular techniques. In recent years, several nucleic acid-based detection technology methods have been developed, one of which is the electrochemical biosensor. Electrochemical biosensors are known to have high sensitivity and accuracy. In addition, the ease of miniaturization of this electrochemical technique has garnered interest from many researchers. On the other hand, the CRISPR/Cas12 method has been widely used in detecting nucleic acids due to its highly selective nature. The CRISPR/Cas12 method is also reported to increase the sensitivity of electrochemical biosensors through the utilization of modified electrodes. The electrodes can be modified according to detection needs so that the biosensor's performance can be improved. This review discusses the application of CRISPR/Cas12-based electrochemical biosensors, as well as various electrode modifications that have been successfully used to improve the performance of these biosensors in the clinical and food monitoring fields.

Advancing genome editing with artificial intelligence: opportunities, challenges, and future directions

Clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing (GED) technologies have unlocked exciting possibilities for understanding genes and improving medical treatments. On the other hand, Artificial intelligence (AI) helps genome editing achieve more precision, efficiency, and affordability in tackling various diseases, like Sickle cell anemia or Thalassemia. AI models have been in use for designing guide RNAs (gRNAs) for CRISPR-Cas systems. Tools like DeepCRISPR, CRISTA, and DeepHF have the capability to predict optimal guide RNAs (gRNAs) for a specified target sequence. These predictions take into account multiple factors, including genomic context, Cas protein type, desired mutation type, on-target/off-target scores, potential off-target sites, and the potential impacts of genome editing on gene function and cell phenotype. These models aid in optimizing different genome editing technologies, such as base, prime, and epigenome editing, which are advanced techniques to introduce precise and programmable changes to DNA sequences without relying on the homology-directed repair pathway or donor DNA templates. Furthermore, AI, in collaboration with genome editing and precision medicine, enables personalized treatments based on genetic profiles. AI analyzes patients' genomic data to identify mutations, variations, and biomarkers associated with different diseases like Cancer, Diabetes, Alzheimer's, etc. However, several challenges persist, including high costs, off-target editing, suitable delivery methods for CRISPR cargoes, improving editing efficiency, and ensuring safety in clinical applications. This review explores AI's contribution to improving CRISPR-based genome editing technologies and addresses existing challenges. It also discusses potential areas for future research in AI-driven CRISPR-based genome editing technologies. The integration of AI and genome editing opens up new possibilities for genetics, biomedicine, and healthcare, with significant implications for human health.

Organic Electronics in Biosensing: A Promising Frontier for Medical and Environmental Applications

The promising field of organic electronics has ushered in a new era of biosensing technology, thus offering a promising frontier for applications in both medical diagnostics and environmental monitoring. This review paper provides a comprehensive overview of organic electronics' remarkable progress and potential in biosensing applications. It explores the multifaceted aspects of organic materials and devices, thereby highlighting their unique advantages, such as flexibility, biocompatibility, and low-cost fabrication. The paper delves into the diverse range of biosensors enabled by organic electronics, including electrochemical, optical, piezoelectric, and thermal sensors, thus showcasing their versatility in detecting biomolecules, pathogens, and environmental pollutants. Furthermore, integrating organic biosensors into wearable devices and the Internet of Things (IoT) ecosystem is discussed, wherein they offer real-time, remote, and personalized monitoring solutions. The review also addresses the current challenges and future prospects of organic biosensing, thus emphasizing the potential for breakthroughs in personalized medicine, environmental sustainability, and the advancement of human health and well-being.

Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms

Candida is the largest genus of medically significant fungi. Although most of its members are commensals, residing harmlessly in human bodies, some are opportunistic and dangerously invasive. These have the ability to cause severe nosocomial candidiasis and candidemia that affect the viscera and bloodstream. A prompt diagnosis will lead to a successful treatment modality. The smart solution of biosensing technologies for rapid and precise detection of Candida species has made remarkable progress. The development of point-of-care (POC) biosensor devices involves sensor precision down to pico-/femtogram level, cost-effectiveness, portability, rapidity, and user-friendliness. However, futuristic diagnostics will depend on exploiting technologies such as multiplexing for high-throughput screening, CRISPR, artificial intelligence (AI), neural networks, the Internet of Things (IoT), and cloud computing of medical databases. This review gives an insight into different biosensor technologies designed for the detection of medically significant Candida species, especially Candida albicans and C. auris, and their applications in the medical setting.

Utility of CRISPR/Cas mediated electrochemical biosensors

Electrochemical biosensors represent a class of sensors that employ biological materials as sensitive elements, electrodes as conversion elements, and potential or current as detection signals. The integration of CRISPR/Cas systems into electrochemical biosensors holds immense potential, offering enhanced versatility, heightened sensitivity and specificity, reduced recovery time, and the ability to capture and identify analytes at low concentrations. In this review, we provided a succinct summary of the fundamental principles underlying electrochemical biosensors and CRISPR/Cas systems, and new progress of electrochemical biosensors based on CRISPR/Cas systems in virus, bacteria, and cancer detections. Besides, we discussed its pros and cons, present gaps, potential problem-solvers, and future prospects. To sum up, CRISPR/Cas mediated electrochemical biosensors will surely benefit us a lot in the detection of cells and microorganisms, and of course in other promising fields.

Potential of CRISPR/Cas system as emerging tools in the detection of viral hepatitis infection

Viral hepatitis, the most common cause of inflammatory liver disease, affects hundreds of millions of people worldwide. It is most commonly associated with one of the five nominal hepatitis viruses (hepatitis A-E viruses). HBV and HCV can cause acute infections and lifelong, persistent chronic infections, while HAV and HEV cause self-limiting acute infections. HAV and HEV are predominantly transmitted through the fecal-oral route, while diseases transmitted by the other forms are blood-borne diseases. Despite the success in the treatment of viral hepatitis and the development of HAV and HBV vaccines, there is still no accurate diagnosis at the genetic level for these diseases. Timely diagnosis of viral hepatitis is a prerequisite for efficient therapeutic intervention. Due to the specificity and sensitivity of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated sequences (Cas) technology, it has the potential to meet critical needs in the field of diagnosis of viral diseases and can be used in versatile point-of-care (POC) diagnostic applications to detect viruses with both DNA and RNA genomes. In this review, we discuss recent advances in CRISPR-Cas diagnostics tools and assess their potential and prospects in rapid and effective strategies for the diagnosis and control of viral hepatitis infection.

Smart Graphene-Based Electrochemical Nanobiosensor for Clinical Diagnosis: Review

The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10^-6), Nanomolar nM (10^-9), Picomolar pM (10^-12), femtomolar fM (10^-15), and attomolar aM (10^-18).

Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen-antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.

Next-Generation Diagnostic with CRISPR/Cas: Beyond Nucleic Acid Detection

The early management, diagnosis, and treatment of emerging and re-emerging infections and the rising burden of non-communicable diseases (NCDs) are necessary. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas system has recently acquired popularity as a diagnostic tool due to its ability to target specific genes. It uses Cas enzymes and a guide RNA (gRNA) to cleave target DNA or RNA. The discovery of collateral cleavage in CRISPR-Cas effectors such as Cas12a and Cas13a was intensively repurposed for the development of instrument-free, sensitive, precise and rapid point-of-care diagnostics. CRISPR/Cas demonstrated proficiency in detecting non-nucleic acid targets including protein, analyte, and hormones other than nucleic acid. CRISPR/Cas effectors can provide multiple detections simultaneously. The present review highlights the technical challenges of integrating CRISPR/Cas technology into the onsite assessment of clinical and other specimens, along with current improvements in CRISPR bio-sensing for nucleic acid and non-nucleic acid targets. It also highlights the current applications of CRISPR/Cas technologies.

Powerful CRISPR-Based Biosensing Techniques and Their Integration With Microfluidic Platforms

In the fight against the worldwide pandemic coronavirus disease 2019 (COVID-19), simple, rapid, and sensitive tools for nucleic acid detection are in urgent need. PCR has been a classic method for nucleic acid detection with high sensitivity and specificity. However, this method still has essential limitations due to the dependence on thermal cycling, which requires costly equipment, professional technicians, and long turnover times. Currently, clustered regularly interspaced short palindromic repeats (CRISPR)-based biosensors have been developed as powerful tools for nucleic acid detection. Moreover, the CRISPR method can be performed at physiological temperature, meaning that it is easy to assemble into point-of-care devices. Microfluidic chips hold promises to integrate sample processing and analysis on a chip, reducing the consumption of sample and reagent and increasing the detection throughput. This review provides an overview of recent advances in the development of CRISPR-based biosensing techniques and their perfect combination with microfluidic platforms. New opportunities and challenges for the improvement of specificity and efficiency signal amplification are outlined. Furthermore, their various applications in healthcare, animal husbandry, agriculture, and forestry are discussed.

Exploring nano-enabled CRISPR-Cas-powered strategies for efficient diagnostics and treatment of infectious diseases

Biomedical researchers have subsequently been inspired the development of new approaches for precisely changing an organism's genomic DNA in order to investigate customized diagnostics and therapeutics utilizing genetic engineering techniques. Clustered Regulatory Interspaced Short Palindromic Repeats (CRISPR) is one such technique that has emerged as a safe, targeted, and effective pharmaceutical treatment against a wide range of disease-causing organisms, including bacteria, fungi, parasites, and viruses, as well as genetic abnormalities. The recent discovery of very flexible engineered nucleic acid binding proteins has changed the scientific area of genome editing in a revolutionary way. Since current genetic engineering technique relies on viral vectors, issues about immunogenicity, insertional oncogenesis, retention, and targeted delivery remain unanswered. The use of nanotechnology has the potential to improve the safety and efficacy of CRISPR/Cas9 component distribution by employing tailored polymeric nanoparticles. The combination of two (CRISPR/Cas9 and nanotechnology) offers the potential to open new therapeutic paths. Considering the benefits, demand, and constraints, the goal of this research is to acquire more about the biology of CRISPR technology, as well as aspects of selective and effective diagnostics and therapies for infectious illnesses and other metabolic disorders. This review advocated combining nanomedicine (nanomedicine) with a CRISPR/Cas enabled sensing system to perform early-stage diagnostics and selective therapy of specific infectious disorders. Such a Nano-CRISPR-powered nanomedicine and sensing system would allow for successful infectious illness control, even on a personal level. This comprehensive study also discusses the current obstacles and potential of the predicted technology.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40097-022-00472-7.

CRISPR-Cas based virus detection: Recent advances and perspectives

Viral infections are one of the most intimidating threats to human beings. One convincing example is the coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2. Rapid, sensitive, specific and field-deployable identification of causal viruses is critical for disease surveillance, control and treatment. The shortcomings of current methods create an impending need for developing novel biosensing platforms. CRISPR-Cas systems, especially CRISPR-Cas12a and CRISPR-Cas13a, characterized by their sensitivity, specificity, high base resolution and programmability upon nucleic acid recognition, have been repurposed for molecular diagnostics, surging a new path forward in biosensing. They, as the core of some robust diagnostic tools, are revolutionizing the way that virus can be detected. This review focuses on recent advances in virus detection with CRISPR-Cas systems especially CRISPR-Cas12a/Cas13a. We started with a short introduction to CRISPR-Cas systems and the properties of Cas12a and Cas13a effectors, and continued with reviewing the current advances of virus detection utilizing CRISPR-Cas systems. The significance and advantages of such methods were then discussed. Finally, the challenges and perspectives were proposed. We tried to provide readers with a concise profile of emerging and fast-expanding CRISPR-Cas based biosensing technology, and highlighted its potential applications in a range of scenarios with regard to virus detection.

Towards CRISPR powered electrochemical sensing for smart diagnostics

Even though global health has been steadily improved, the global disease burden associated with communicable and non-communicable diseases extensively increased healthcare expenditure. The present COVID-19 pandemic scenario has again ascertained the importance of clinical diagnostics as a basis to make life-saving decisions. In this context, there is a need for developing next-generation integrated smart real-time responsive biosensors with high selectivity and sensitivity. The emergence of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas biosensing systems has shown remarkable potential for developing next-generation biosensors. CRISPR/Cas integrated electrochemical biosensors (E-CRISPR) stands out with excellent properties. In this opinionated review, we illustrate the rapidly evolving applications for E-CRISPR-integrated detection systems towards biosensing and the future scope associated with E-CRISPR based diagnostics.

CRISPR detectives against SARS-CoV-2: a major setback against COVID-19 blowout

The emergence of SARS-CoV-2 has brought the world to a standstill, and till date, effective treatments and diagnostics against this idiosyncratic pathogen are lacking. As compared to the standard WHO/CDC qPCR detection method, which consumes several hours for detection, CRISPR-based SHERLOCK, DETECTR, and FELUDA have emerged as rapid diagnostic tools for the detection of the RNA genome of SARS-CoV-2 within an hour with 100% accuracy, specificity, and sensitivity. These attributes of CRISPR-based detection technologies have taken themselves one step ahead of available detection systems and are emerging as an inevitable tool for quick detection of the virus. Further, the discovery of Cas13s nucleases and their orthologs has opened a new corridor for exploitation of Cas13s as an antiviral therapy against SARS-CoV-2 and other viral diseases. One such approach is Prophylactic Antiviral CRISPR in huMAN cells (PACMAN), which needs a long haul to bring into therapy. The approval of SHERLOCK as the first CRISPR-based SARS-CoV-2 test kit by the FDA, for emergency diagnosis of COVID-19 patients, has given positive hope to scientists that sooner human trials of CRISPR-based therapy will be ratified. In this review, we have extensively reviewed the present CRISPR-based approaches, challenges, and future prospects in the light of diagnostics and therapeutics against SARS-CoV-2. KEY POINTS: • The discovery of Cas12 and Cas13 siblings allowed scientists to detect the viral genes. • Cas13d's identification aided scientists in precisely cleaving the SARS-CoV-2 ssRNA. • CRISPR-Cas system acts as "molecular detector and antiviral proctor."

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

The current pandemic of the 2019 novel coronavirus (COVID-19) caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) has raised significant public health concern. Rapid, affordable, and accurate diagnostics of SARS-CoV-2 is essential for early treatment and control of the disease spread. In the past few years, CRISPR technology has shown great potential for highly sensitive and specific molecular diagnostics. Amid the ongoing COVID-19 pandemic, there is an increasing interest in implementing CRISPR-based diagnostic principles to develop fast and precise methods for detecting SARS-CoV-2. In this work, we reviewed and summarized these CRISPR-based diagnostic systems as well as their characteristics and challenges. We also provided future perspectives of CRISPR-based sensing towards point-of-care molecular diagnosis applications.

CRISPR-based tools: Alternative methods for the diagnosis of COVID-19

The recently emerged severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spread all over the world rapidly and caused a global pandemic. To prevent the virus from spreading to more individuals, it is of great importance to identify and isolate infected individuals through testing. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the gold standard method for the diagnosis of coronavirus disease (COVID-19) worldwide. However, performing RT-qPCR is limited to centralized laboratories because of the need for sophisticated laboratory equipment and skilled personnel. Further, it can sometimes give false negative or uncertain results. Recently, new methods have been developed for nucleic acid detection and pathogen diagnosis using CRISPR-Cas systems. These methods present rapid and cost-effective diagnostic platforms that provide high sensitivity and specificity without the need for complex instrumentation. Using the CRISPR-based SARS-CoV-2 detection methods, it is possible to increase the number of daily tests in existing laboratories, reduce false negative or uncertain result rates obtained with RT-qPCR, and perform testing in resource-limited settings or at points of need where performing RT-qPCR is not feasible. Here, we briefly describe the RT-qPCR method, and discuss its limitations in meeting the current diagnostic needs. We explain how the unique properties of various CRISPR-associated enzymes are utilized for nucleic acid detection and pathogen diagnosis. Then, we highlight the important features of CRISPR-based diagnostic methods developed for SARS-CoV-2 detection. Finally, we examine the advantages and limitations of these methods, and discuss how they can contribute to improving the efficiency of the current testing systems for combating SARS-CoV-2.

AI Techniques for COVID-19

Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.