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. 2023 Feb 6;24(4):3209.
doi: 10.3390/ijms24043209.

Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis

Yuting Wu  1 , Zhiwei Liu  1 , Sihan Mao  2 , Bing Liu  1 , Zhaoyang Tong  1
Affiliations

Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis

Yuting Wu et al. Int J Mol Sci. .

Abstract

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.

Keywords: PCA-LDA; SARS-CoV-2; identification; phage display; spectroscopy; virus-like models.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Validation of the Model-S. (a) Double digestion (SfiI/NotI) of pHB-S. Lane M: Marker; Lane 1: double digestion result. (b) PCR amplification of pHB-S. Lane M: Marker; Lane 1: PCR result. (c) Sandwich ELISA result from Model-S. Compared with the blank M13 phages and BSA, the results from Model-S were positive when combined with anti-SARS-CoV-2 spike antibodies. (d) Affinity analysis: interference shifts over time, reflecting the interference change caused by different concentrations. (e) Steady-state analysis: Response over the concentration of Model-S. (d,e) for the calculation of the affinity constant of Model-S.
Figure 2
Figure 2
The score plot for the nine samples from 3DFS after PCA analysis. (a) Coordination PC1−PC2; (b) Coordination PC1−PC3.
Figure 3
Figure 3
3DFS Group center plot for the nine samples after LDA analysis under the coordination Function 1 and Function 2. Bio−threats Model-S and Model-N can be separated and distinguished from the other samples.
Figure 4
Figure 4
The scatter plot describes the scores for the nine samples from RS after PCA analysis. (a) Coordination PC1−PC2; (b) Coordination PC1−PC3.
Figure 5
Figure 5
RS Group center plot for the nine samples after LDA analysis.
Figure 6
Figure 6
Schematic flow diagram for the preparation of the virus-like Model-S.
See this image and copyright information in PMC

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