With the outbreak and spread of COVID-19, a deep investigation of SARS-CoV-2 is urgent. Direct usage of this virus for scientific research could provide reliable results and authenticity. However, it is strictly constrained and unrealistic due to its high pathogenicity and infectiousness. Considering its biosafety, different systems and technologies have been employed in immunology and biomedical studies. In this study, phage display technology was used to construct a nonpathogenic model for COVID-19 research. The nucleocapsid protein of SARS-CoV-2 was fused with the M13 phage capsid p3 protein and expressed on the M13 phages. After validation of its successful expression, its potential as the standard for qPCR quantification and affinity with antibodies were confirmed, which may show the possibility of using this nonpathogenic bacteriophage to replace the pathogenic virus in scientific research concerning SARS-CoV-2. In addition, the model was used to develop a system for the classification and identification of different samples using ATR–FTIR, which may provide an idea for the development and evaluation of virus monitoring equipment in the future.

The rapid identification and recognition of COVID-19 have been challenging since its outbreak. Multiple methods were developed to realize fast monitoring early to prevent and control the pandemic. In addition, it is difficult and unrealistic to apply the actual virus to study and research because of the highly infectious and pathogenic SARS-CoV-2. In this study, the virus-like models were designed and produced to replace the original virus as bio-threats. Three-dimensional excitation-emission matrix fluorescence and Raman spectroscopy were employed for differentiation and recognition among the produced bio-threats and other viruses, proteins, and bacteria. Combined with PCA and LDA analysis, the identification of the models for SARS-CoV-2 was achieved, reaching a correction of 88.9% and 96.3% after cross-validation, respectively. This idea might provide a possible pattern for detecting and controlling SARS-CoV-2 from the perspective of combining optics and algorithms, which could be applied in the early-warning system against COVID-19 or other bio-threats in the future.

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