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Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies
Xianghui Li1, Jing Wang2, Jingping Geng1
1Department of Microbiology and Immunology, Medical School, China Three Gorges University, Yichang, 443002, China.
Abstract:
In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the currently approved coronavirus disease 2019 vaccines can be given to those over 5 years of age and older in most countries, strikingly, the number of people diagnosed positive for SARS-Cov-2 is still increasing. Therefore, to prevent and control this epidemic, early diagnosis of infected individuals is of great importance. The current detection of SARS-Cov-2 coronavirus variants are mainly based on reverse transcription-polymerase chain reaction. Although the sensitivity of reverse transcription-polymerase chain reaction is high, it has some disadvantages, for example, multiple temperature changes, long detection time, complicated operation, expensive instruments, and the need for professional personnel, which brings considerable inconvenience to the early diagnosis of this virus. This review comprehensively summarizes the development and application of various current detection technologies for novel coronaviruses, including isothermal amplification, CRISPR-Cas detection, serological detection, biosensor, ensemble, and microfluidic technology, along with next-generation sequencing. Those findings offer us a great potential to replace or combine with reverse transcription-polymerase chain reaction detection to achieve the purpose of allowing predictive diagnostics and targeted prevention of SARS-Cov-2 in the future.
Insights
New diagnostic methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are crucial as infections rise. This review explores advanced detection technologies that could improve upon current reverse transcription-polymerase chain reaction methods for early diagnosis and prevention.
Area of Science:
- Virology
- Molecular Biology
- Biotechnology
Background:
- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), identified in 2019, causes significant global morbidity and mortality.
- Despite widespread vaccination, SARS-CoV-2 infections continue to increase, highlighting the need for effective diagnostic and preventative strategies.
- Current detection relies on reverse transcription-polymerase chain reaction (RT-PCR), which has limitations including complexity, cost, and time.
Purpose of the Study:
- To review and summarize current and emerging detection technologies for SARS-CoV-2.
- To evaluate alternative and complementary methods to RT-PCR for early diagnosis and targeted prevention of SARS-CoV-2.
- To provide insights into the potential of novel technologies in managing the ongoing pandemic.
Main Methods:
- Comprehensive review of scientific literature on SARS-CoV-2 detection technologies.
- Analysis of methods including isothermal amplification, CRISPR-Cas, serological assays, biosensors, ensemble techniques, microfluidics, and next-generation sequencing.
- Comparison of these technologies against established RT-PCR methods.
Main Results:
- Various advanced technologies show promise for SARS-CoV-2 detection, offering potential advantages over RT-PCR.
- Isothermal amplification, CRISPR-Cas, biosensors, and microfluidics present opportunities for faster, simpler, and potentially more accessible diagnostics.
- Next-generation sequencing and ensemble methods offer comprehensive genetic analysis and improved accuracy.
Conclusions:
- Emerging diagnostic technologies hold significant potential to enhance early detection and targeted prevention of SARS-CoV-2 infections.
- These novel methods could overcome limitations of current RT-PCR diagnostics, improving pandemic control efforts.
- Further development and integration of these technologies are key for future predictive diagnostics and public health strategies.
