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Spectroscopic methods for COVID-19 detection and early diagnosis

Virology Journal volume 19, Article number: 152 (2022) Cite this article

Abstract

The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

Introduction

COVID-19 is a global pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Protection have been the core of pandemic management due to the high transmissibility, the elevated fatality rate (more than 1%) and the lack of viable antiviral treatments [1]. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million recorded cases of coronavirus infections globally, with 5 million fatalities [2]. COVID-19 is a pulmonary illness that predominantly affects the endothelium of the blood vessels [3]. In addition, COVID-19 can affect numerous important organs, including the heart, blood vessels, kidneys, abdomen, especially when the patients are not of a vulnerable age. Tremendous efforts have been exerted to slow the COVID-19 spread and to protect all individuals, especially those with chronic diseases [4,5,6,7,8,9].

COVID-19 identification is regarded as a key step in the eradication and treatment of COVID-19-infected individuals. Furthermore, the quick and thorough testing aids in the tracking and isolation of close contacts of anyone who has tested positive for COVID-19, preventing the virus from spreading. As a result, the test and trace service allow for the management of the reproduction rate, as well as assisting governments in developing plans and implementing required control measures, such as local or nationwide lockdowns, to limit the pandemic and save lives. Several COVID-19 test techniques are currently available in the market [10], which could be divided into two types: viral tests (to identify an infection) and antibody tests (also known as serologic tests). Antigen testing and nucleic acid amplification tests are two forms of viral tests that can be utilized. For the diagnosis of COVID-19 infection, the WHO and the US Centers for Disease Control and Prevention propose real-time reverse transcription polymerase chain reaction (PCR), which involves the detection of viral RNA using nucleic acid amplification tests [11].

Because of its excellent sensitivity and specificity, PCR is the gold standard for detecting COVID-19 infections [12,13,14,15,16,17,18,19]. A PCR test, on the other hand, is a time-consuming procedure that needs a sophisticated laboratory instrument, skilled staff, and sample transportation logistics. Furthermore, the chance of getting false-negative findings from PCR testing might be as high as 29% [20], which became a growing source of worry. Furthermore, delays in receiving PCR findings provide a window in which infectious virus might be shed, making management of onward transmission difficult. Alternative antigen lateral flow assays are faster; however, they have lower sensitivity and specificity, when compared to PCR. Rapid antigen tests, on the other hand, can give important information as point-of-care testing, therefore interest in their performance is increasing, with a particular focus on sensitivity and overall specificity [21]. The antibody-based diagnostic methods are promising, but antibodies may not emerge for weeks or months after the first exposure. As a result, there is still an unmet need for a low-cost, fast diagnostic approach with high sensitivity and specificity that may be used for large-scale testing and monitoring of the COVID-19 infection [22].

Spectroscopic techniques were widely used in virus detection, including Raman [20,21,22], infrared [23,24,25,26,27], mass spectrophotometry [28,29,30,31] and fluorescence spectroscopy [32,33,34]. In this review, the reported state-of-the-art spectroscopic methods for the COVID-19 detection and early diagnosis were discussed. The different techniques were compared in terms of accuracy, sensitivity and specificity. The requirements, the technical aspects, the limitations and the performance of each technique were discussed.

Discussion

Spectroscopic methods could be applied to detect the biological changes in COVID-19 infection. The main objective was to develop simple, fast, time saving spectroscopic technique for early detection and diagnosis of coronaviruses. SARS patients' serum samples showed an upregulation of long-chain acylcarnitine (carnitines C18:0 and C18-OH), fructose, myo-inositol phosphate, 1,2,4-trihydroxybenzene, 2,3,4-trihydroxybutyric acid, cysteine and pyroglutamic acid, compared with healthy volunteers. On the other side, methyl esters such as 9,12-octadecadienoic acid and hexadecanoic acid, free carnitine, and arginine were lower in recovered SARS patients, compared with healthy volunteers. In addition, there was an elevation in serum lipids, including phosphatidylglycerol, lysophosphatidylcholines, lysophosphatidylethanolamines and some free fatty acids. Also, infection with COVID-19 resulted in increased blood levels of cysteine, alanine, aspartic acid, succinic acid, and lactic acid, while the levels of ether phosphatidylethanolamines, phosphatidylserines, sphingomyelins, triglycerides and long chain fatty acids decreased in recovered SARS patients [35]. Moreover, angiotensin-converting enzyme II (ACE2); a receptor involved in the virus's entrance mechanism into cells, was highly expressed in oral epithelial cells, according to studies [16, 36]. These changes will be tracked by spectroscopic techniques, as elaborated in in the next sections, to aid in COVID-19 early detection. The most important applications of spectroscopic technique for COVID-19 detection are summarized in Table 1.

Table 1 Applications of spectroscopic technique for COVID-19 detection
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COVID-19 virus detection using Raman spectroscopy

Raman spectroscopy is a type of vibrational spectroscopy that could be used to optically examine the molecular alterations in sick tissues. In th-eory, Raman spectroscopy is based on inelastic scattering in which scattered photons have less or more energy than incident photons. The difference in energy corresponds to the vibrational levels in the studied molecules, which gives information about the structural features and alterations in these molecules. Raman spectra are produced by directing a monochromatic laser beam at a sample and plotting the scattered intensity as a function of the energy difference between incoming and scattered photons. The difference in the end and starting vibrational energy levels of the molecules correlates with the loss (or gain) in photon energies. Shifts in wavenumbers (inverse of wavelength) from the incident frequency describe the resulting spectra. The frequency difference between incoming and Raman-scattered light is unique to each molecule and is known as the Raman shift, expressed as cm−1 [37].

Raman spectroscopy is a nondestructive analytical method that offers information about the molecular composition of the materials analyzed with only a little quantity of sample and allows diagnosis in a matter of minutes with the right statistical and computational tools [38]. Raman spectroscopy may be used to identify biomolecular characteristics in biological materials, such as lipids, proteins, nucleic acids, and amino acids [39]. Raman spectroscopy, which is based on the principle of inelastic light scattering [40], has been used to identify HIV, dengue fever, and a variety of biomarkers, and could possibly overcome practical issues with mass testing as a point-of-care device [41,42,43]. For the analysis of biological samples, vibrational spectroscopic techniques such as Raman spectroscopy offer several advantages over biochemical methods, including high speed, the easiness of sample preparation and small sample size required. As mentioned previously, increased blood levels of cysteine, alanine, aspartic acid, succinic acid, and lactic acid were seen after infection with COVID-19 [35], besides angiotensin-converting enzyme II (ACE2), which was significantly expressed in oral epithelial cells of patients [36]. Raman spectroscopy could possibly detect ACE2, by tracking the changes in intensity, width or shifts of Raman peaks [39]. Carlomagno et al. [16] used surface enhanced Raman spectroscopy (SERS) as a novel method for detecting current (COV +) and previous SARS-CoV-2 infections (COV-) in saliva. As indicated in Fig. 1, the subtraction spectra were dominated by peaks at 1048 and 1126 cm−1, with significant differences between the healthy group and the COV + and COV-, respectively. The strong signals in these two locations were usually linked with an environment high in aromatic amino acids, especially tryptophan and phenylalanine. The same two peaks (1048 cm−1 and 1126 cm−1) have also been discovered as distinctive signals from coronaviruses, indicating that they are involved in the viral protein structure or interactions with physiologically produced molecules.

Fig. 1
figure 1

Subtraction Raman spectra of (a) the average CTRL signal versus the average signal of COV + , (b) the average CTRL signal versus the average COV- spectrum and c the average COV + signal versus the average COV − signal. The ± 0.005 ΔI intervals are indicated in the graphs, confirmed by the error propagation from the spectra standard deviation. d Overlapped average spectra of CTRL, COV + and COV − with the main different regions highlighted. (With permission from [16])

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SERS could be utilized for more than only virus detection, because in it could aid in examining protein structure and track in situ changes caused by various environments. Sanchez et al. [44] used SERS generated by gold nanostars nanoparticles and molybdenum disulfide (MoS2) thin films for virus detection (Fig. 2). Furthermore, the major proteins S and N spectra were well-defined. Using a gold nano star, in this case resulted in increasing the signal of SERS. Goulart et al. [38] indicated that Raman spectroscopy could identify COVID-19 in human serum through the biochemical changes associated with the presence of SARS-Cov-2, including an increase in lipids, nitrogen compounds (urea and amines/amides), and nucleic acids, as well as a reduction in proteins and amino acids (tryptophan). These reports indicated that SERS could be a non-invasive, label-free method for detecting COVID-19 infection.

Fig. 2
figure 2

a SEM image of the Au–Cu nano, stars used as SERS substrate. The image shows very sharp peaks which act as plasmonic antennas. b Optical absorption spectra of the nano, stars revealed a strong peak in the near IR. (With permission from [44])

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COVID-19 virus detection using infrared spectroscopy

Infrared spectroscopy is a commonly used analytical method for identifying chemical functional groups in a variety of materials. When infrared light interacts with molecules' intrinsic vibrational modes, it creates a spectrum that represents the sample's chemical fingerprint. Infrared (IR) radiation is the electromagnetic spectrum area between visible (VIS) and microwave wavelengths. Two types of IR radiations are involved in diagnostics; near IR (NIR) and mid IR (MIR). In NIR spectroscopy, molecules are excited at wavelengths ranging from 750 to 2500 nm, corresponding to wavenumbers ranging from 4000 to 13,000 cm−1. Solid, liquid, or gaseous samples can absorb certain wavelengths of incoming infrared light, resulting in a fingerprint or a spectrum. Stretching, deformation, and scissor vibrations are performed by molecules with C–H, C–O, C = O, N–H, and O–H functional groups in this spectral area. In contrast to the MIR area (4000–400 cm−1), where only fundamental vibrations ("signatures") could be noticed, overtones and combinations are observed in the NIR range, which contains a greater amount of information than MIR. As a result, the spectrum is frequently cluttered with overlapping peaks. Despite the fact that NIR intensities are 10–1000 times lower than MIR intensities, extremely sensitive spectrometers could be developed in a variety of ways, including the use of efficient detectors. The light collected by the detector carries compositional information that a computer may use to report several results almost instantly. IR spectroscopy could allow simultaneous, non-destructive qualitative and quantitative examination of the key components in a wide range of organic compounds [45].

In the field of biological diagnostics, the development of portable attenuated total reflection Fourier transform infrared (ATR-FTIR) spectrometers has been prospering over years [46]. ATR-FTIR has recently been used to diagnose Plasmodium species in blood [47] and viruses such as hepatitis B and C in serum [48]. ATR-FTIR relies on identifying both the pathogen's molecular phenotype and the host's immunological response. The chemical differences between infected and uninfected samples could subsequently be used to predict diagnostic outcomes using advanced machine learning algorithms. Barauna et al. [49] used ATR-FTIR to examine saliva obtained from COVID-19 diagnosed individuals. The swab was put on an ATR spectrometer and the spectra of both the saliva and the swab were recorded. Figure 3 demonstrates the examination of swabs spiked with saliva, with or without irradiated COVID-19 virus particles. The bands responsible for increasing concentrations of viral material (nucleic acid bands) are shown on principal component 1 (PC1), whereas the bands responsible for differentiation between saliva and virus are shown on PC2. It is worth mentioning that both the bands of amide I and II bands were observed only in saliva, not in virus.

Fig. 3
figure 3

a Average raw spectra and b pre-processed spectra for saliva (n = 2), pure COVID-19 virus in different concentrations (n = 28, 1 × 105–98 copies/mL), and saliva + virus in different concentrations (n = 63, 1 × 105–24 copies/mL). c PCA scores and d PCA loadings on PC1 vs. PC2 for the pre-processed data. Inset c1 and c2 show both low concentration (≤ 781 copies/mL) and high concentration (≥ 1.25 × 10.4 copies/mL) of mixed saliva/virus. (With permission from [49])

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Saliva contains numerous additional COVID-19 indicators, including ACE2, adenosine deaminase, immunoglobulin G, immunoglobulin M, RNA, and secretory immunoglobulin A, in addition to SARS-CoV-2 virions [50]. Wood et al. [51] investigated these biomarker in saliva for COVID-19 detection. Mir et al. [52] indicated that ATR–FTIR analysis was cost-effective since it took less time and required no reagent. Significant vibrational modes of biological materials generally fell within the 1800–900 cm–1 band, which was referred to as the "bio fingerprint" zone.

Kitane et al. [53] depended on the determination of SARS-CoV-2 by characterization of extracted RNA samples. Figure 4 indicated that a careful examination of the greatest footprint spectral region of the RNA spectra for positive and negative SARS-CoV-2 RNA samples revealed the existence of three primary visible domains: one at 600–1350 cm−1, another at 1500–1700 cm−1, and the third at 2300–3900 cm−1. The phosphate backbone vibrations (vP-O) were assigned to the first domain, with the 1000–1182 cm−1 area resulting from symmetric stretching vibrations of PO2 and allocated to the phosphodiester and ribose C–O stretching vibration. The PO2 asymmetric stretching vibration of the RNA, which was normally centered at 1251 cm−1, could be responsible for the spectral area 1200–1300 cm−1. RNA nucleobases may be attributed to the third 1500–1700 cm−1 area. In addition, this area coincided with a set of biomarker bands that were commonly associated with Amide I and II vibrations. The stretching vibrations of the OH, NH, and CH groups were aligned in the 2400–3900 cm−1 range. Taken together, these results clearly matched the RNA signature, demonstrating the FT-IR/machine learning dual coupling's resilience in viral identification and patient categorization.

Fig. 4
figure 4

Detection of SARS-CoV-2 with multivariable analysis. a Raw Spectra b Sample of 2nd derivative of Savitzky–Golay smoothened spectra of positive and negative samples. c, d, e First three latent variables of PLS-DA. (f) Coefficients of variables selected by the sparse classification algorithm of second derivatives of raw spectra (g, h) Zooms on regions indicated by sparse classification. i Projection of the 280 spectra used according to the first two latent variables obtained. j Projection of the 280 spectra used according to the first three latent variables obtained. (With permission from [53])

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Cuazitl et al. [54] used ATR-FTIR for the determination of immune responses through three different antibodies. IgA, IgG and IgM were assigned to the regions 1285–1237, 1560–1464 and 1420–1289 cm−1, respectively as indicated in Fig. 5.

Fig. 5
figure 5

Mean of FTIR spectra of healthy (N = 1209) and COVID-19 (N = 255) groups. A Biological fingerprint region, diverse absorption bands related to biological samples are evidenced such as Amide I (1644 cm−1), Amide II (1545 cm−1), and Amide III (1240 cm−1), as well as phosphorylated molecules (1240 cm−1and 1076 cm−1), carbohydrates (1030 cm−1), and DNA backbone (968 cm−1). Likewise, peaks in ranges: 1100–850 cm−1and 1080–950 cm−1 attributed to nucleic acids and α-amylase, respectively were observed. Differences in absorbance and displacements between the bands of the groups representing changes in biochemical compositions were evidenced. B Immunoglobulins regions, different intervals were detected such as IgG (560–1464 cm−1), IgM (1420–1289 cm−1 and 1160–1028 cm−1), and IgA (1285–1237 cm.−1), noticing that the COVID-19 group exhibited a higher absorbance. (With permission from [54])

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Guleken et al. [55] used FTIR spectroscopy to prove that COVID-19 affected peripheral blood cells, biochemical parameters, and coagulation markers in both second and third trimester pregnant women. Furthermore, COVID-19 lowered albumin levels in both third trimester and severe second trimester women. Banerjee et al. [56] invested ATR-FTIR for COVID-19 severity classification. The study indicated that ATR-FTIR was a promising method for COVID-19 monitoring in real time. Clinical laboratory professionals may readily carry out the sample preparation and spectrum collection procedures established here due to their simplicity. The high cost of the instruments could be the main obstacle against the widespread of Raman spectroscopy in COVID-19 diagnosis.

COVID-19 virus detection using fluorescence spectroscopy

Luminescence is the emission of light from any substance that occurs when it is stimulated by light. Luminescence is classified into two types: fluorescence and phosphorescence, based on the nature of the excited state. The electron in the excited orbital is coupled (by opposing spin) to the second electron in the ground-state orbital in excited singlet states. As a result, return to the ground state is spin permitted and occurs swiftly via photon emission. Fluorescence emission rates are approximately 108 s−1, resulting in a typical fluorescence lifetime of around 10 ns (10 × 10−9 s). A fluorophore's lifespan is the average duration between excitation and return to the ground state. Because fluorescence has a short timeframe, measuring time-resolved emission needs complex optics and electronics. Despite the extra complexity, time-resolved fluorescence is extensively employed because the data contain more information than stationary or steady-state observations. Furthermore, technological advancements have simplified time-resolved measurements, even when utilizing microscopes [57]. The development of fluorescence-based optical technology has been widely used in biomedical for illness detection and diagnosis [15].When given a light source with a wavelength of 200–800 nm, the samples will glow and provide a response in the form of a conventional fluorescence spectrum with excitation and emission peaks [58]. Disease diagnosis was traditionally done by identifying the primary cause of disease, such as germs, anomalies in certain bodily cells, or viruses. When a virus has multiplied itself in vivo, detection of illnesses caused by viruses is possible. Virus genetic information is dependent on the genetic information of virus-infected organisms. For each of these viruses, genetic information can be a unique marker that appears as a fluorescence emission[33]. To identify the virus, a 450 nm laser diode was employed as a light source. Using a labelling agent, the virus's specific fluorescence emission may be boosted. Rong et al. created a smartphone-based fluorescent lateral flow immunoassay (LFIA) technology for extremely sensitive Zika virus nonstructural protein 1 point-of-care detection [59]. In this investigation, ZIKV NS1 was detected quantitatively at the point of care in 20 min. ZIKV NS1 had detection limits of 0.045 and 0.15 ng/mL in buffer and serum, respectively. Fluorescence technology was used for more than just the initial detection and screening. It can, however, be utilized to describe coronavirus enzymatic activity. In 2005, Chen et al. employed fluorescence resonance energy transfer to study the enzymatic activity of the coronavirus (3CLpro) 3C-like protease (3CLpro) and its four sites directed mutations in the severe acute respiratory syndrome (SARS) coronavirus (CoV) [60]. Kong et al. (2015) employed a bimolecular fluorescence complementation (BiFC) test to discover SARS-CoV accessory protein interactions. The universal application of the BiFC system for the evaluation of protein–protein interactions of SARS-CoV with direct visualization was demonstrated in this work. Fluorescence technology can be used in conjunction with other approaches to identify coronaviruses. To detect SARS-CoV, Huang et al. developed a fiber-optic biosensor with a localized surface plasmon coupled fluorescence (LSPCF) [61]. Fluorescence technology can also be employed in the diagnosis of COVID-19 infections. In 2020, Diao et al. developed an immunochromatographic fluorescent method for identifying SARS-CoV-2 nucleocapsid protein [62].

COVID-19 virus detection using mass spectroscopy

Mass spectroscopy is an analytical method used to identify biomolecules or proteins in biological materials, as well as to study protein–protein interactions. The fundamental idea is that a substance or molecule is fragmented into charged species, which are then accelerated, deflected, and eventually focused on a detector based on their mass and charge ratio. Ion deflection is determined by charge, mass, and velocity, while ion separation is monitored by the mass to charge (m/z) ratio, and the signal intensity is proportional to the ion abundance [63]. Mass spectrometry (MS) is a useful analytical method for examining genomes, proteomics, metabolomics, and microbiomics of human disorders [64, 65] due to its inherent sensitivity, specificity, and speed. These advantages makes MS-based technologies a valuable analytical tool to detect COVID-19 [66]. On COVID-19-related human fluids, significant MS-based metabolomic and proteomic research have been completed [67,68,69,70,71,72,73,74] using different ionization techniques such as matrix-assisted laser desorption/ionization (MALDI), ambient ionization, desorption electrospray ionization (DESI) [75], paper spray [76]) and direct ionization [77].

In clinical and pathologic research on COVID-19, evaluating human exhaled breath aerosol (EBA) profiles is beneficial due to COVID-19's respiratory characteristics [78, 79]. Volatile organic compounds, droplets that can dissolve a variety of non-volatile metabolites, salts, proteins, and microorganisms such as bacterial and viral particles were all present in EBA, which could be a substantial source of coronavirus infection [80]. MS Spectrometry-based approaches of human breath samples have numerous benefits over existing COVID-19 diagnostic procedures being noninvasive, easy to operate, with a strong analytical performance. Grassin-Delyle et al. used PTR-MS to detect volatile organic compounds (VOCS) in breath including 2,4-octadiene 1-chloroheptane, methylpent-2-enal and nonanal. This study found that direct MS analysis of breath VOCs from COVID-19 patients had a 93% accuracy, which could lead to the development of the novel online approaches for large-scale COVID-19 screening [77]. For COVID-19 diagnosis, GC–MS analysis of breath VOC and blood metabolites has been recommended [81, 82]. LC–MS has been a widely used technique for determination of exhaled breath condensate (EBC). This EBC contained a range of nonvolatile organic chemicals and biological matrices that could be used to provide useful biochemical information regarding respiratory disorders in the future. LC–MS has therefore been proposed for the COVID-19 diagnosis [82]. Because SARS-CoV-2 can be transmitted by breath droplets, direct detection of SARS-CoV-2 from breath samples is critical [83]. Because of its excellent precision, mass range, and good analytical performance, MALDI-MS is an efficient analytical instrument for detecting microorganisms such as bacteria, fungi, and viruses [84,85,86,87]. So, MALDI-MS is expected to a powerful diagnostic tool using breath sample. Nachtigall et al. used MALDI-MS for COVID-19 detection by using a nasal swab. The results showed that MALDI-MS is an accurate, sensitive, cheap and simple in comparison with RT-PCR [51]. Yan et al. used Matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for fast detection of COVID-19 depending on peptidome profiling of serum. The results showed that COVID-19 may be detected quickly and accurately using MALDI-TOF-based serum profiling. It offers a lot of promise for screening, regular surveillance, and diagnostics in big populations, which is crucial for pandemic control [88].

Perspectives

Microfluidics has found applications in a variety of sectors, including medication delivery, clinical diagnostics, and chemical analysis [89]. A microfluidic platform is made up of micro-scale fluid handling compartments including channels, valves, reservoirs, membranes, and so on that allow for integrated biochemical examination in a consistent and straightforward manner [90, 91]. Jadhav et al. used SERS in conjunction with microfluidic devices with built-in microchannels as indicated in Fig. 6. The Raman signal could be enhanced by the Ag/Au nanoparticles in the detecting well. Machine learning techniques could be used to analyze the Raman signal, which would be trained on the signals of known viral molecules. The spectrum of the test sample would be compared to a previously recorded SARS-CoV-2 standard reference spectrum. Viruses are trapped using vertically aligned Au/Ag coated carbon nanotubes (Au/Ag-VACNTs), which not only help to separate viruses from samples, but they also help to concentrate them (on repeated applications). This localized rise in titre aids in the correct identification and increases the assay's sensitivity. This assay does not need the tagging of virus particles or the preparation of materials before they are introduced into the instrument. As a result of the short time, the microfluidic-based SERS has the potential to become a robust, reliable, highly sensitive, and extremely quick detection technique of choice throughout the world. Furthermore, the excellent performance of this tool will make it easier to build and manufacture portable systems to combat future viral outbreaks with a significant reduction in reaction time [14].

Fig. 6
figure 6

a Proposed microfluidic platform for virus detection. b Proposed VACNTs functionalized microfluidic platform. (With permission from [14])

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SARS-CoV-2 diagnosis can be derived from mRNA or microRNA (miRNA) detection approaches, using a programmable nanoparticle network made up of DNA-bridged gold nanoparticles and quantum dots to boost signal gain [92, 93]. Quantum dots made of carbon and graphene have unique electrical and fluorescent characteristics that may be attached to RNA or DNA substrates to detect viral RNA. Carbon dots are more favorable than traditional quantum dots and organic dyes because of their excellent water solubility, photobleaching stability, greater biocompatibility, and low toxicity [94, 95]. Yao et al. [96] depended on single-stranded DNA probes, functionalized with evaporated gold nano-island sheets as surface enhanced infrared absorption (SEIRA) substrates for targeted binding to certain SARS-CoV-2 genomic regions. To find the important distinctive changes between infected and control samples, the infrared absorption spectra were examined using the principal component analysis approach. The SEIRA-based biosensor could detect SARS-CoV-2 quickly, taking less than 5 min to detect 1 million viral nucleic acids without any amplification. The detection capability of 2.98 copies per liter may be performed in 30 min when paired with the recombinase polymerase amplification therapy. This method provides a straightforward and cost-effective method for diagnosing COVID-19, which would be beneficial in monitoring and managing future pandemics in a timely way.

Conclusion

In the fight against COVID-19, scientists have gone a long way. However, a new viral variety might jeopardize development. Viruses are transferred more easily through human contact and touching surfaces. As a result, quick and accurate viral identification methods are essential in order to limit pandemic breakouts. This review gave an overview of COVID-19 and a comprehensive knowledge of coronavirus detection utilizing spectroscopic tools. These spectroscopic methods are rapid and practical, for determination of COVID-19 in comparison with real time PCR which is the gold standard diagnosis.

Availability of data and materials

Not applicable.

References

  1. Whitelaw S, Mamas MA, Topol E, Van Spall HGC. Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit Heal. 2020;2:e435–40.

    Article  Google Scholar 

  2. Hamed M, El-Hasab M, Mansour FR. Direct acting anti-hepatitis C combinations as potential COVID-19 protease inhibitors. VirusDisease. 2021;32:279–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Ilkhani H, Hedayat N, Farhad S. Novel approaches for rapid detection of COVID-19 during the pandemic: A review. Anal Biochem. 2021;634:114362.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Manekiya M, Donelli M. Monitoring the covid-19 diffusion by combining wearable biosensors and smartphones. Prog Electromagn Res M. 2021;100:13–21.

    Article  CAS  Google Scholar 

  5. Suresh Kumar S, Dashtipour K, Abbasi QH, Imran MA, Ahmad W. A review on wearable and contactless sensing for COVID-19 with policy challenges. Front Commun Netw. 2021;2:1–10.

    Google Scholar 

  6. Mirjalali S, Peng S, Fang Z, Wang C, Wu S. Wearable sensors for remote health monitoring: potential applications for early diagnosis of Covid-19. Adv Mater Technol. 2021;7:2100545.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Abdallah IA, Hammad SF, Bedair A, Elshafeey AH, Mansour FR. Determination of favipiravir in human plasma using homogeneous liquid–liquid microextraction followed by HPLC/UV. Bioanalysis. 2022;14:205–16.

    Article  CAS  PubMed  Google Scholar 

  8. Abdallah IA, Hammad SF, Bedair A, Mansour FR. Menthol-assisted homogenous liquid-liquid microextraction for HPLC/UV determination of favipiravir as an antiviral for COVID-19 in human plasma. J Chromatogr B. 2022;1189:123087.

    Article  CAS  Google Scholar 

  9. Abdallah IA, Hammad SF, Bedair A, Abdelaziz MA, Danielson ND, Elshafeey AH, et al. A gadolinium-based magnetic ionic liquid for supramolecular dispersive liquid–liquid microextraction followed by HPLC/UV for the determination of favipiravir in human plasma. Biomed Chromatogr. 2022;36:1–10.

    Article  Google Scholar 

  10. La Marca A, Capuzzo M, Paglia T, Roli L, Trenti T, Nelson SM. Testing for SARS-CoV-2 (COVID-19): a systematic review and clinical guide to molecular and serological in-vitro diagnostic assays. Reprod Biomed Online. 2020;41:483–99.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Udugama B, Kadhiresan P, Kozlowski HN, Malekjahani A, Osborne M, Li VYC, et al. Diagnosing COVID-19: the disease and tools for detection. ACS Nano. 2020;14:3822–35.

    Article  CAS  PubMed  Google Scholar 

  12. Crozier A, Rajan S, Buchan I, McKee M. Put to the test: use of rapid testing technologies for covid-19. BMJ. 2021;372:n208.

    Article  PubMed  Google Scholar 

  13. Adigal SS, Rayaroth NV, John RV, Pai KM, Bhandari S, Mohapatra AK, et al. Expert review of molecular diagnostics a review on human body fluids for the diagnosis of viral infections: scope for rapid detection of. Expert Rev Mol Diagn. 2021;21:31–42.

    Article  CAS  PubMed  Google Scholar 

  14. Jadhav SA, Biji P, Panthalingal MK, Murali Krishna C, Rajkumar S, Joshi DS, et al. Development of integrated microfluidic platform coupled with surface-enhanced Raman spectroscopy for diagnosis of COVID-19. Med Hypotheses. 2021;146:110356.

    Article  CAS  PubMed  Google Scholar 

  15. Lukose J, Chidangil S, George SD. Biosensors and bioelectronics optical technologies for the detection of viruses like COVID-19: progress and prospects. Biosens Bioelectron. 2021;178:113004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Carlomagno C, Bertazioli D, Gualerzi A, Picciolini S, Banfi PI, Lax A, et al. COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections. Sci Rep. 2021;11:4943.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Nogueira MS, Leal LB, Macarini W, Pimentel RL, Muller M, Vassallo PF, et al. Rapid diagnosis of COVID-19 using FT-IR ATR spectroscopy and machine learning. Sci Rep. 2021;11:1–13.

    CAS  Google Scholar 

  18. Saviñon-Flores F, Méndez E, López-Castaños M, Carabarin-Lima A, López-Castaños KA, González-Fuentes MA, et al. A review on SERS-based detection of human virus infections: influenza and coronavirus. Biosensors. 2021;11:66.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gowri A, Ashwin Kumar N, Suresh Anand BS. Recent advances in nanomaterials based biosensors for point of care (PoC) diagnosis of Covid-19 – a minireview. TrAC Trends Anal Chem. 2021;137:116205.

    Article  CAS  Google Scholar 

  20. Arevalo-Rodriguez I, Buitrago-Garcia D, Simancas-Racines D, Zambrano-Achig P, Del Campo R, Ciapponi A, et al. False-negative results of initial RT-PCR assays for COVID-19: a systematic review. PLoS ONE. 2020;15:e0242958.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Mertens P, De Vos N, Martiny D, Jassoy C, Mirazimi A, Cuypers L, et al. Development and potential usefulness of the COVID-19 Ag respi-strip diagnostic assay in a pandemic context. Front Med. 2020;7:225.

    Article  Google Scholar 

  22. Afroj S, Britnell L, Hasan T, Andreeva DV, Novoselov KS, Karim N. graphene-based technologies for tackling COVID-19 and future pandemics. Adv Funct Mater. 2021;31:2107407.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Johnson JB, Naiker M. Seeing red: a review of the use of near-infrared spectroscopy (NIRS) in entomology spectroscopy (NIRS) in entomology. Appl Spectrosc Rev. 2020;55:810–39.

    Article  Google Scholar 

  24. Lyu W, Teng H, Wu C, Zhang X, Guo X, Yang X, et al. Anisotropic acoustic phonon polariton-enhanced infrared spectroscopy for single molecule detection. Nanoscale. 2021;13:12720–6.

    Article  PubMed  Google Scholar 

  25. Fernandes JN, dos Santos LMB, Chouin-Carneiro T, Pavan MG, Garcia GA, David MR, et al. Rapid, noninvasive detection of Zika virus in Aedes aegypti mosquitoes by near-infrared spectroscopy. Sci Adv. 2018;4:4–10.

    Article  Google Scholar 

  26. Zhang Y, Yurdakul C, Devaux AJ, Wang L, Xu XG, Connor JH, et al. Vibrational spectroscopic detection of a single virus by mid-infrared photothermal microscopy. Anal Chem. 2021;93:4100–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Khan RS, Rehman IU. Spectroscopy as a tool for detection and monitoring of Coronavirus (COVID-19). Expert Rev Mol Diagn. 2020;20:647–9.

    Article  CAS  PubMed  Google Scholar 

  28. Stump MJ, Fleming RC, Gong W, Jaber AJ, Jones JJ, Surber CW, et al. Matrix-assisted laser desorption mass spectrometry. Appl Spectrosc Rev. 2002;37:275–303.

    Article  CAS  Google Scholar 

  29. Zachertowska A, Brewer D, Evans DH. MALDI-TOF mass spectroscopy detects the capsid structural instabilities created by deleting the myxoma virus cupro-zinc SOD1 homolog M131R. J Virol Methods. 2004;122:63–72.

    Article  CAS  PubMed  Google Scholar 

  30. Chen H, Gill A, Dove BK, Emmett SR, Kemp CF, Ritchie MA, et al. Mass spectroscopic characterization of the coronavirus infectious bronchitis virus nucleoprotein and elucidation of the role of phosphorylation in RNA binding by using surface plasmon resonance. J Virol. 2005;79:1164–79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Alizadeh M, Yousefi L, Pakdel F, Ghotaslou R, Rezaee MA, Khodadadi E, et al. MALDI-TOF mass spectroscopy applications in clinical microbiology. Adv Pharmacol Pharm Sci. 2021;2021:1–8.

    Article  Google Scholar 

  32. Shahzad A, Edetsberger M, Koehler G. Fluorescence spectroscopy : an emerging excellent diagnostic tool in medical sciences. Appl Spectrosc Rev. 2010;45(1):1–11.

    Article  CAS  Google Scholar 

  33. Madurani KA, Suprapto S, Syahputra MY, Puspita I, Masudi A, Rizqi HD, et al. Review—recent development of detection methods for controlling COVID-19 outbreak. J Electrochem Soc. 2021;168:037511.

    Article  CAS  Google Scholar 

  34. El-Malla SF, Elattar RH, Kamal AH, Mansour FR. A highly sensitive switch-on spectrofluorometric method for determination of ascorbic acid using a selective eco-friendly approach. Spectrochim Acta Part A Mol Biomol Spectrosc. 2022;270:120802.

    Article  CAS  Google Scholar 

  35. Wu Q, Zhou L, Sun X, Yan Z, Hu C, Wu J, et al. Altered lipid metabolism in recovered SARS patients twelve years after infection. Sci Rep. 2017;7:9110.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Schlagenhauf-Lawlor P, Gautret P, Hagmann S, Cohen A, Leder K, Patel D. Travel medicine and infectious disease editor-in-chief. 2019;9:18–9.

  37. Movasaghi Z, Rehman S, Rehman IU. Raman spectroscopy of biological tissues. Appl Spectrosc Rev. 2007;42:493–541.

    Article  CAS  Google Scholar 

  38. Goulart ACC, Zângaro RA, Carvalho HC, Silveira L. Diagnosing COVID-19 in human sera with detected immunoglobulins IgM and IgG by means of Raman spectroscopy. J Raman Spectrosc. 2021. https://doi.org/10.1002/jrs.6235.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Ember K, Daoust F, Mahfoud M, Dallaire F. Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning. J Biomed Opt. 2021;27(2):025002.

    Google Scholar 

  40. Raman CV, Krishnan KS. A new type of secondary radiation. Nature. 1928;121:501–2.

    Article  CAS  Google Scholar 

  41. Ryzhikova E, Kazakov O, Halamkova L, Celmins D, Malone P, Molho E, et al. Raman spectroscopy of blood serum for Alzheimer’s disease diagnostics: specificity relative to other types of dementia. J Biophotonics. 2015;8:584–96.

    Article  PubMed  Google Scholar 

  42. Sahu A, Dalal K, Naglot S, Aggarwal P, Murali KC. Serum based diagnosis of asthma using raman spectroscopy: an early phase pilot study. PLoS ONE. 2013;8:e78921.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Rehman A, Anwar S, Firdous S, Ahmed M, Rasheed R, Nawaz M. Dengue blood analysis by Raman spectroscopy. Laser Phys. 2012;22:1085–9.

    Article  CAS  Google Scholar 

  44. Sanchez JE, Jaramillo SA, Settles E, Velazquez Salazar JJ, Lehr A, Gonzalez J, et al. Detection of SARS-CoV-2 and its S and N proteins using surface enhanced Raman spectroscopy. RSC Adv. 2021;11:25788–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Huck CW. Advances of infrared spectroscopy in natural product research. Phytochem Lett. 2015;11:384–93.

    Article  CAS  Google Scholar 

  46. Baker MJ, Trevisan J, Bassan P, Bhargava R, Butler HJ, Dorling KM, et al. Using Fourier transform IR spectroscopy to analyze biological materials. Nat Protoc. 2014;9:1771–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Heraud P, Chatchawal P, Wongwattanakul M, Tippayawat P, Doerig C, Jearanaikoon P, et al. Infrared spectroscopy coupled to cloud-based data management as a tool to diagnose malaria: a pilot study in a malaria-endemic country. Malar J. 2019;18:1–11.

    Article  Google Scholar 

  48. Roy S, Perez-Guaita D, Bowden S, Heraud P, Wood BR. Spectroscopy goes viral: diagnosis of hepatitis B and C virus infection from human sera using ATR-FTIR spectroscopy. Clin Spectrosc. 2019;1:100001.

    Article  Google Scholar 

  49. Barauna VG, Singh MN, Barbosa LL, Marcarini WD, Vassallo PF, Mill JG, et al. Ultrarapid on-site detection of SARS-CoV-2 infection using simple ATR-FTIR spectroscopy and an analysis algorithm: high sensitivity and specificity. Anal Chem. 2021;93:2950–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wood BR, Kochan K, Bedolla DE, Salazar-Quiroz N, Grimley SL, Perez-Guaita D, et al. Infrared based saliva screening test for COVID-19. Angew Chemie. 2021;133:17239–44.

    Article  Google Scholar 

  51. Nachtigall FM, Pereira A, Trofymchuk OS, Santos LS. Detection of SARS-CoV-2 in nasal swabs using MALDI-MS. Nat Biotechnol. 2020;38:1168–73.

    Article  CAS  PubMed  Google Scholar 

  52. Mir JM, Khan MW, Shalla AH, Maurya RC. A Nonclinical spectroscopic approach for diagnosing covid-19: a concise perspective. J Appl Spectrosc. 2021;88:765–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kitane DL, Loukman S, Marchoudi N, Fernandez-Galiana A, El Ansari FZ, Jouali F, et al. A simple and fast spectroscopy-based technique for Covid-19 diagnosis. Sci Rep. 2021;11:1–11.

    Article  Google Scholar 

  54. Martinez-Cuazitl A, Vazquez-Zapien GJ, Sanchez-Brito M, Limon-Pacheco JH, Guerrero-Ruiz M, Garibay-Gonzalez F, et al. ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients. Sci Rep. 2021;11:19980.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Guleken Z, Jakubczyk P, Wiesław P, Krzysztof P, Bulut H, Öten E, et al. Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications. Talanta. 2021;237:122916.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Banerjee A, Gokhale A, Bankar R, Palanivel V, Salkar A, Robinson H, et al. Rapid classification of COVID-19 severity by ATR-FTIR spectroscopy of plasma samples. Anal Chem. 2021;93:10391–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Instrumentation for Fluorescence Spectroscopy. In: Lakowicz, J.R. (eds) Principles of Fluorescence Spectroscopy. Springer, Boston, MA, 2019; 27–61. https://doi.org/10.1007/978-0-387-46312-4_2

  58. Fardiyah Q, Ersam T, Suyanta SA, Suprapto KF. New potential and characterization of Andrographis paniculata L. Ness plant extracts as photoprotective agent. Arab J Chem. 2020;13:8888–97.

    Article  CAS  Google Scholar 

  59. Rong Z, Wang Q, Sun N, Jia X, Wang K, Xiao R, et al. Smartphone-based fluorescent lateral flow immunoassay platform for highly sensitive point-of-care detection of Zika virus nonstructural protein 1. Anal Chim Acta. 2019;1055:140–7.

    Article  CAS  PubMed  Google Scholar 

  60. Chen S, Chen L, Luo H, Sun T, Chen J, Ye F, et al. Enzymatic activity characterization of SARS coronavirus 3C-like protease by fluorescence resonance energy transfer technique1. Acta Pharmacol Sin. 2005;26:99–106.

    Article  PubMed  Google Scholar 

  61. Huang JC, Chang Y-F, Chen K-H, Su L-C, Lee C-W, Chen C-C, et al. Detection of severe acute respiratory syndrome (SARS) coronavirus nucleocapsid protein in human serum using a localized surface plasmon coupled fluorescence fiber-optic biosensor. Biosens Bioelectron. 2009;25:320–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Diao B, Wen K, Chen J, Liu Y, Yuan Z, Han C, et al. Diagnosis of acute respiratory syndrome coronavirus 2 infection by detection of nucleocapsid protein. medRxiv. 2020.

  63. Rajawat J, Jhingan G. Mass spectroscopy. Data process. Handb. Complex Biol. Data Sources. 2019.

  64. Yates JR. Mass spectrometry. Trends Genet. 2000;16:5–8.

    Article  CAS  PubMed  Google Scholar 

  65. Griffiths WJ, Wang Y. Mass spectrometry: from proteomics to metabolomics and lipidomics. Chem Soc Rev. 2009;38:1882.

    Article  CAS  PubMed  Google Scholar 

  66. Mahmud I, Garrett TJ. Mass Spectrometry techniques in emerging pathogens studies: COVID-19 perspectives. J Am Soc Mass Spectrom. 2020;31:2013–24.

    Article  CAS  PubMed  Google Scholar 

  67. Ihling C, Tänzler D, Hagemann S, Kehlen A, Hüttelmaier S, Arlt C, et al. Mass spectrometric identification of SARS-CoV-2 proteins from gargle solution samples of COVID-19 patients. J Proteome Res. 2020;19:4389–92.

    Article  CAS  PubMed  Google Scholar 

  68. Sen R. High-throughput approaches of diagnosis and therapies for COVID-19: antibody panels, proteomics and metabolomics. Futur Drug Discov. 2021;3:FDD55.

    Article  Google Scholar 

  69. Wu D, Shu T, Yang X, Song J-X, Zhang M, Yao C, et al. Plasma metabolomic and lipidomic alterations associated with COVID-19. Natl Sci Rev. 2020;7:1157–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Migaud M, Gandotra S, Chand HS, Gillespie MN, Thannickal VJ, Langley RJ. Metabolomics to predict antiviral drug efficacy in COVID-19. Am J Respir Cell Mol Biol. 2020;63:396–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Bojkova D, Klann K, Koch B, Widera M, Krause D, Ciesek S, et al. Proteomics of SARS-CoV-2-infected host cells reveals therapy targets. Nature. 2020;583:469–72.

    Article  CAS  PubMed  Google Scholar 

  72. Shen B, Yi X, Sun Y, Bi X, Du J, Zhang C, et al. Proteomic and metabolomic characterization of COVID-19 patient sera. Cell. 2020;182:59-72.e15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Zhao Y, Shang Y, Ren Y, Bie Y, Qiu Y, Yuan Y, et al. Omics study reveals abnormal alterations of breastmilk proteins and metabolites in puerperant women with COVID-19. Signal Transduct Target Ther. 2020;5:247.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Tian W, Zhang N, Jin R, Feng Y, Wang S, Gao S, et al. Immune suppression in the early stage of COVID-19 disease. Nat Commun. 2020;11:5859.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Stavrakaki SM, Mckenzie J, Mcgill D, Koguna H, Kinross J, Takats Z. Rapid detection of SARS-CoV2 by Ambient Mass Spectrometry Techniques Authors. MedRxiv. 2020

  76. De Silva IW, Nayek S, Singh V, Reddy J, Granger JK, Verbeck GF. Paper spray mass spectrometry utilizing Teslin® substrate for rapid detection of lipid metabolite changes during COVID-19 infection. Analyst. 2020;145:5725–32.

    Article  PubMed  Google Scholar 

  77. Grassin-Delyle S, Roquencourt C, Moine P, Saffroy G, Carn S, Heming N, et al. Metabolomics of exhaled breath in critically ill COVID-19 patients: a pilot study. EBioMedicine. 2021;63:103154.

    Article  CAS  PubMed  Google Scholar 

  78. Fernández-Peralbo MA, Calderón Santiago M, Priego-Capote F, Luque de Castro MD. Study of exhaled breath condensate sample preparation for metabolomics analysis by LC–MS/MS in high resolution mode. Talanta. 2015;144:1360–9.

    Article  PubMed  Google Scholar 

  79. Yuan Z-C, Hu B. Mass spectrometry-based human breath analysis: towards COVID-19 diagnosis and research. J Anal Test. 2021;5:287–97.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Ma J, Qi X, Chen H, Li X, Zhang Z, Wang H, et al. Exhaled breath is a significant source of SARS-CoV-2 emission. medRxiv. 2020;1–8.

  81. Mougang YK, Di Zazzo L, Minieri M, Capuano R, Catini A, Legramante JM, et al. Sensor array and gas chromatographic detection of the blood serum volatolomic signature of COVID-19. iScience. 2021;24:102851.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Zheng H, Jin S, Li T, Ying W, Ying B, Chen D, et al. Metabolomics reveals sex-specific metabolic shifts and predicts the duration from positive to negative in non-severe COVID-19 patients during recovery process. Comput Struct Biotechnol J. 2021;19:1863–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Ryan DJ, Toomey S, Madden SF, Casey M, Breathnach OS, Morris PG, et al. Use of exhaled breath condensate (EBC) in the diagnosis of SARS-COV-2 (COVID-19). Thorax. 2021;76:86–8.

    Article  PubMed  Google Scholar 

  84. Maier T, Klepel S, Renner U, Kostrzewa M. Fast and reliable MALDI-TOF MS–based microorganism identification. Nat Methods. 2006;3:i–ii.

    Article  CAS  Google Scholar 

  85. Calderaro A, Arcangeletti M-C, Rodighiero I, Buttrini M, Gorrini C, Motta F, et al. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification. Sci Rep. 2015;4:6803.

    Article  Google Scholar 

  86. Singhal N, Kumar M, Kanaujia PK, Virdi JS. MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Front Microbiol. 2015;6:1–16.

    Article  Google Scholar 

  87. Kriegsmann J, Casadonte R, Kriegsmann K, Longuespée R, Kriegsmann M. Mass spectrometry in pathology – Vision for a future workflow. Pathol - Res Pract. 2018;214:1057–63.

    Article  CAS  PubMed  Google Scholar 

  88. Yan L, Yi J, Huang C, Zhang J, Fu S, Li Z, et al. Rapid detection of COVID-19 using MALDI-TOF-based serum peptidome profiling. Anal Chem. 2021;93:4782–7.

    Article  CAS  PubMed  Google Scholar 

  89. Alsaeed B, Mansour FR. Distance-based paper microfluidics; principle, technical aspects and applications. Microchem J. 2020;155:104664.

    Article  CAS  Google Scholar 

  90. Azizipour N, Avazpour R, Rosenzweig DH, Sawan M, Ajji A. Evolution of biochip technology: a review from lab-on-a-chip to organ-on-a-chip. Micromachines. 2020;11:599.

    Article  PubMed Central  Google Scholar 

  91. Whitesides GM. What comes next? Lab Chip. 2011;11:191–3.

    Article  CAS  PubMed  Google Scholar 

  92. Yue R, Li Z, Wang G, Li J, Ma N. Logic sensing of MicroRNA in living cells using DNA-programmed nanoparticle network with high signal gain. ACS Sensors. 2019;4:250–6.

    Article  CAS  PubMed  Google Scholar 

  93. Yuan X, Yang C, He Q, Chen J, Yu D, Li J, et al. Current and perspective diagnostic techniques for COVID-19. ACS Infect Dis. 2020;6:1998–2016.

    Article  PubMed  PubMed Central  Google Scholar 

  94. El-Malla SF, Elshenawy EA, Hammad SF, Mansour FR. N-Doped carbon dots as a fluorescent nanosensor for determination of colchicine based on inner filter effect. J Fluoresc. 2021;31:675–84.

    Article  CAS  PubMed  Google Scholar 

  95. El-Malla SF, Elshenawy EA, Hammad SF, Mansour FR. Rapid microwave synthesis of N, S-doped carbon quantum dots as a novel turn off-on sensor for label-free determination of copper and etidronate disodium. Anal Chim Acta. 2022;1197:339491.

    Article  CAS  PubMed  Google Scholar 

  96. Yao Z, Zhang Q, Zhu W, Galluzzi M, Zhou W, Li J, et al. Rapid detection of SARS-CoV-2 viral nucleic acids based on surface enhanced infrared absorption spectroscopy. Nanoscale. 2021;13:10133–42.

    Article  CAS  PubMed  Google Scholar 

  97. Zhang L, Xiao M, Wang Y, Peng S, Chen Y, Zhang D, et al. Fast screening and primary diagnosis of COVID-19 by ATR–FT-IR. Anal Chem. 2021;93:2191–9.

    Article  CAS  PubMed  Google Scholar 

  98. Huang J, Wen J, Zhou M, Ni S, Le W, Chen G, et al. On-Site detection of SARS-CoV-2 antigen by deep learning-based surface-enhanced Raman spectroscopy and its biochemical foundations. Anal Chem. 2021;93:9174–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Goulart ACC, Silveira L, Carvalho HC, Dorta CB, Pacheco MTT, Zangaro RA. Diagnosing COVID-19 in human serum using Raman spectroscopy: a preliminary study. medRxiv. 2021;2021.08.09.21261798.

  100. Ibrahim W, Cordell RL, Wilde MJ, Richardson M, Carr L, Sundari Devi Dasi A, et al. Diagnosis of COVID-19 by exhaled breath analysis using gas chromatography–mass spectrometry. ERJ Open Res. 2021;7:00139–2021.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Lazari LC, Ghilardi FDR, Rosa-Fernandes L, Assis DM, Nicolau JC, Santiago VF, et al. Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19. Life Sci Alliance. 2021;4:e202000946.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Tran NK, Howard T, Walsh R, Pepper J, Loegering J, Phinney B, et al. Novel application of automated machine learning with MALDI-TOF-MS for rapid high-throughput screening of COVID-19: a proof of concept. Sci Rep. 2021;11:8219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Lv L, Jiang H, Chen Y, Gu S, Xia J, Zhang H, et al. The faecal metabolome in COVID-19 patients is altered and associated with clinical features and gut microbes. Anal Chim Acta. 2021;1152:338267.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Department of Analytical Chemistry, Faculty of Pharmacy, University of Sadat City, Sadat City, 32958, Egypt

    Alaa Bedair

  2. Internal Medicine and Nephrology Department, Faculty of Medicine, Tanta University, Tanta, Egypt

    Kamal Okasha

  3. Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, The Medical Campus of Tanta University, Elgeish Street, Tanta, 31111, Egypt

    Fotouh R. Mansour

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  1. Alaa Bedair
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AB prepared the initial draft of the manuscript. KO participated in manuscript revision. FRM participated in manuscript preparation, revision and submission. All authors reviewed and approved the final manuscript.

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Bedair, A., Okasha, K. & Mansour, F.R. Spectroscopic methods for COVID-19 detection and early diagnosis. Virol J 19, 152 (2022). https://doi.org/10.1186/s12985-022-01867-2

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Keywords

  • COVID-19
  • Coronavirus
  • Raman spectroscopy
  • Infrared spectroscopy
  • Mass spectrometry
  • Fluorescence spectroscopy

Virology Journal

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