Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known. In this paper, the S1 conformation was investigated for MERS-CoV, SARS-CoV, and SARS-CoV-2 at serological pH by measuring their Amide I infrared absorption bands. The SARS-CoV-2 S1 secondary structure revealed a strong difference compared to those of MERS-CoV and SARS-CoV, with a significant presence of extended ß-sheets. Furthermore, the conformation of the SARS-CoV-2 S1 showed a significant change by moving from serological pH to mild acidic and alkaline pH conditions. Both results suggest the capability of infrared spectroscopy to follow the secondary structure adaptation of the SARS-CoV-2 S1 to different environments.

Electromagnetic deactivation spectroscopy of human coronavirus 229E.

An investigation of the deactivation of pathogens using electromagnetic waves in the microwave region of the spectrum is achieved using custom-built waveguide structures. The waveguides feature sub-wavelength gratings to allow the integration of an air cooling system without disturbing the internal propagating fields. The waveguides are tapered to accommodate an experimental sample internally with sufficient surrounding airflow. The proposed methodology allows for precise control over power densities due to the well-defined fundamental mode excited in each waveguide, in addition to temperature control of the sample due to microwave exposure over time. Human coronavirus (HCoV-229E) is investigated over the 0-40 GHz range, where a peak 3-log viral reduction is observed in the 15.0-19.5 GHz sub-band. We conclude HCoV-229E has an intrinsic resonance in this range, where nonthermal structure damage is optimal through the structure-resonant energy transfer effect.

Magnetic Particle Spectroscopy for Point-of-Care: A Review on Recent Advances.

Since its first report in 2006, magnetic particle spectroscopy (MPS)-based biosensors have flourished over the past decade. Currently, MPS are used for a wide range of applications, such as disease diagnosis, foodborne pathogen detection, etc. In this work, different MPS platforms, such as dual-frequency and mono-frequency driving field designs, were reviewed. MPS combined with multi-functional magnetic nanoparticles (MNPs) have been extensively reported as a versatile platform for the detection of a long list of biomarkers. The surface-functionalized MNPs serve as nanoprobes that specifically bind and label target analytes from liquid samples. Herein, an analysis of the theories and mechanisms that underlie different MPS platforms, which enable the implementation of bioassays based on either volume or surface, was carried out. Furthermore, this review draws attention to some significant MPS platform applications in the biomedical and biological fields. In recent years, different kinds of MPS point-of-care (POC) devices have been reported independently by several groups in the world. Due to the high detection sensitivity, simple assay procedures and low cost per run, the MPS POC devices are expected to become more widespread in the future. In addition, the growth of telemedicine and remote monitoring has created a greater demand for POC devices, as patients are able to receive health assessments and obtain results from the comfort of their own homes. At the end of this review, we comment on the opportunities and challenges for POC devices as well as MPS devices regarding the intensely growing demand for rapid, affordable, high-sensitivity and user-friendly devices.

Ultra-sensitive and specific detection of pathogenic nucleic acids using composite-excited hyperfine plasma spectroscopy combs sensitized by Au nanoarrays functionalized with 2D Ta2C-MXene.

Accurate and rapid screening techniques on a population scale are crucial for preventing and managing epidemics like COVID-19. The standard gold test for nucleic acids in pathogenic infections is primarily the reverse transcription polymerase chain reaction (RT-PCR). However, this method is not suitable for widespread screening due to its reliance on large-scale equipment and time-consuming extraction and amplification processes. Here, we developed a collaborative system that combines high-load hybridization probes targeting N and OFR1a with Au NPs@Ta2C-M modified gold-coated tilted fiber Bragg grating (TFBG) sensors to enable direct nucleic acid detection. Multiple activation sites of SARS-CoV-2 were saturable modified on the surface of a homogeneous arrayed AuNPs@Ta2C-M/Au structure based on a segmental modification approach. The combination of hybrid probe synergy and composite polarisation response in the excitation structure results in highly specific hybridization analysis and excellent signal transduction of trace target sequences. The system demonstrates excellent trace specificity, with a limit of detection of 0.2 pg/mL, and achieves a rapid response time of 1.5 min for clinical samples without amplification. The results showed high agreement with the RT-PCR test (Kappa index = 1). And the gradient-based detection of 10-in-1 mixed samples exhibits high-intensity interference immunity and excellent trace identification. Therefore, the proposed synergistic detection platform has a good tendency to curb the global spread of epidemics such as COVID-19.

Detection of viral antibodies in camel sera using magnetic particle spectroscopy.

Pandemics like SARS-Cov-2 very frequently have their origin in different animals and in particular herds of camels could be a source of zoonotic diseases. This study took advantage on a highly sensitive and adaptable method for the fast and reliable detection of viral antibodies in camels using low-cost equipment. Magnetic nanoparticles (MNP) have high variability in their functionalization with different peptides and proteins. We confirm that 3-aminopropyl triethoxysilane (APTES)-coated MNP could be functionalized with viral proteins. The protein loading could be confirmed by simple loading controls using FACS-analysis (p < 0.05). Complementary combination of antigen and antibody yields in a significant signal increase could be proven by both FACS and COMPASS. However, COMPASS needs only a few seconds for the measurement. In COMPASS, the phase φn on selected critical point of the fifth higher harmonic (n = 5th). Here, positive sera display highly significant signal increase over the control or negative sera. Furthermore, a clear distinction could be made in antibody detection as an immune response to closely related viruses (SARS-CoV2 and MERS). Using modified MNPs along with COMPASS offers a fast and reliable method that is less cost intensive than current technologies and offers the possibility to be quickly adapted in case of new occurring viral infections. KEY POINTS: • COMPASS (critical offset magnetic particle spectroscopy) allows the fast detection of antibodies. • Magnetic nanoparticles can be adapted by exchange of the linked bait molecule. • Antibodies could be detected in camel sera without washing steps within seconds.

Breath analysis by ultra-sensitive broadband laser spectroscopy detects SARS-CoV-2 infection.

Rapid testing is essential to fighting pandemics such as coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exhaled human breath contains multiple volatile molecules providing powerful potential for non-invasive diagnosis of diverse medical conditions. We investigated breath detection of SARS-CoV-2 infection using cavity-enhanced direct frequency comb spectroscopy (CE-DFCS), a state-of-the-art laser spectroscopic technique capable of a real-time massive collection of broadband molecular absorption features at ro-vibrational quantum state resolution and at parts-per-trillion volume detection sensitivity. Using a total of 170 individual breath samples (83 positive and 87 negative with SARS-CoV-2 based on reverse transcription polymerase chain reaction tests), we report excellent discrimination capability for SARS-CoV-2 infection with an area under the receiver-operating-characteristics curve of 0.849(4). Our results support the development of CE-DFCS as an alternative, rapid, non-invasive test for COVID-19 and highlight its remarkable potential for optical diagnoses of diverse biological conditions and disease states.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

Electrochemistry and Spectroscopy-Based Biosensors.

During and after the COVID-19 pandemic, the development of low-cost detection and analysis methods of bioanalytes as well as infection biomarkers became an increasingly important challenge in order to improve public and personal health [...].

Stokes-Mueller polarization-based analysis of model SARS-CoV-2 virions.

Understanding the virology of the coronavirus at the structural level has gained utmost importance to overcome the constant and long-term health complications induced by them. In this work, the light scattering properties of SARS-CoV-2 of size 140 nm were simulated by using discrete dipole approximation (DDA) for two incident wavelengths 200 nm and 350 nm, respectively. Three different 3-dimensional (3D) models of SARS-CoV-2 corresponding to 15, 20, and 40 numbers of spike proteins on the viral capsid surface were constructed as target geometries for the DDA calculations. These models were assessed by employing Stokes-Mueller polarimetry to obtain individual polarization properties such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP). Irrespective of its spike numbers, all the coronavirus models were found to display higher DOP and DOCP values and negligibly small DOLP values for circularly polarized incident light, indicating the presence of chiral structures. On the other hand, the lack of understanding about the dependence of the Mueller matrix on its microstructural properties was overcome by transforming 16 Mueller elements into sub-matrices with specific structural and physical properties using Lu-Chipman-based Mueller matrix polar decomposition method. The obtained properties such as retardance, diattenuation, and depolarization were used for investigating the composition and microstructural information. The approach presented in this work has the potential to understand the virology of the coronavirus at the structural level and, therefore, will be beneficial in developing effective detection strategies by exploiting their characteristic electromagnetic scattering signatures.

Characterizing viral samples using machine learning for Raman and absorption spectroscopy.

Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here, we utilized both convolutional neural networks (CNNs) and random forests (RFs) to predict the concentration of the samples containing measles, mumps, rubella, and varicella-zoster viruses (ProQuad®) based on Raman and absorption spectroscopy. We prepared Raman and absorption spectra data sets with known concentration values, then used the Raman and absorption signals individually and together to train RFs and CNNs. We demonstrated that both RFs and CNNs can make predictions with R2 values as high as 95%. We proposed two different networks to jointly use the Raman and absorption spectra, where our results demonstrated that concatenating the Raman and absorption data increases the prediction accuracy compared to using either Raman or absorption spectrum alone. Additionally, we further verified the advantage of using joint Raman-absorption with principal component analysis. Furthermore, our method can be extended to characterize properties other than concentration, such as the type of viral particles.

Critical Offset Magnetic PArticle SpectroScopy for rapid and highly sensitive medical point-of-care diagnostics.

Magnetic nanoparticles (MNPs) have been adapted for many applications, e.g., bioassays for the detection of biomarkers such as antibodies, by controlled engineering of specific surface properties. Specific measurement of such binding states is of high interest but currently limited to highly sensitive techniques such as ELISA or flow cytometry, which are relatively inflexible, difficult to handle, expensive and time-consuming. Here we report a method named COMPASS (Critical-Offset-Magnetic-Particle-SpectroScopy), which is based on a critical offset magnetic field, enabling sensitive detection to minimal changes in mobility of MNP ensembles, e.g., resulting from SARS-CoV-2 antibodies binding to the S antigen on the surface of functionalized MNPs. With a sensitivity of 0.33 fmole/50 µl (≙7 pM) for SARS-CoV-2-S1 antibodies, measured with a low-cost portable COMPASS device, the proposed technique is competitive with respect to sensitivity while providing flexibility, robustness, and a measurement time of seconds per sample. In addition, initial results with blood serum demonstrate high specificity.

Electrolyte Analysis in Blood Serum by Laser-Induced Breakdown Spectroscopy Using a Portable Laser.

The fast and reliable analysis of electrolytes such as K, Na, Ca in human blood serum has become an indispensable tool for diagnosing and preventing diseases. Laser-induced breakdown spectroscopy (LIBS) has been demonstrated as a powerful analytical technique on elements. To apply LIBS to the quantitative analysis of electrolyte elements in real time, a self-developed portable laser was used to measure blood serum samples supported by glass slides and filter paper in this work. The partial least squares regression (PLSR) method was employed for predicting the concentrations of K, Na, Ca from serum LIBS spectra. Great prediction accuracies with excellent linearity were obtained for the serum samples, both on glass slides and filter paper. For blood serum on glass slides, the prediction accuracies for K, Na, Ca were 1.45%, 0.61% and 3.80%. Moreover, for blood serum on filter paper, the corresponding prediction accuracies were 7.47%, 1.56% and 0.52%. The results show that LIBS using a portable laser with the assistance of PLSR can be used for accurate quantitative analysis of elements in blood serum in real time. This work reveals that the handheld LIBS instruments will be an excellent tool for real-time clinical practice.

Cardiovascular magnetic resonance imaging and spectroscopy in clinical long-COVID-19 syndrome: a prospective case-control study.

BACKGROUND: The underlying pathophysiology of post-coronavirus disease 2019 (long-COVID-19) syndrome remains unknown, but increased cardiometabolic demand and state of mitochondrial dysfunction have emerged as candidate mechanisms. Cardiovascular magnetic resonance (CMR) provides insight into pathophysiological mechanisms underlying cardiovascular disease and 31-phosphorus CMR spectroscopy (31P-CMRS) allows non-invasive assessment of the myocardial energetic state. The main aim of the study was to assess whether long COVID-19 syndrome is associated with abnormalities of myocardial structure, function, perfusion and energy metabolism. METHODS: Prospective case-control study. A total of 20 patients with a clinical diagnosis of long COVID-19 syndrome (seropositive) and no prior underlying cardiovascular disease (CVD) and 10 matching healthy controls underwent 31P-CMRS and CMR at 3T at a single time point. All patients had been symptomatic with acute COVID-19, but none required hospital admission. RESULTS: Between the long COVID-19 syndrome patients and matched contemporary healthy controls there were no differences in myocardial energetics (phosphocreatine to ATP ratio), in cardiac structure (biventricular volumes), function (biventricular ejection fractions, global longitudinal strain), tissue characterization (T1 mapping and late gadolinium enhancement) or perfusion (myocardial rest and stress blood flow, myocardial perfusion reserve). One patient with long COVID-19 syndrome showed subepicardial hyperenhancement on late gadolinium enhancement imaging compatible with prior myocarditis, but no accompanying abnormality in cardiac size, function, perfusion, extracellular volume fraction, native T1, T2 or cardiac energetics. CONCLUSIONS: In this prospective case-control study, the overwhelming majority of patients with a clinical long COVID-19 syndrome with no prior CVD did not exhibit any abnormalities in myocardial energetics, structure, function, blood flow or tissue characteristics.

Targeted Delivery of Zinc Pyrithione to Skin Epithelia.

Zinc pyrithione (ZnPT) is an anti-fungal drug delivered as a microparticle to skin epithelia. It is one of the most widely used ingredients worldwide in medicated shampoo for treating dandruff and seborrheic dermatitis (SD), a disorder with symptoms that include skin flaking, erythema and pruritus. SD is a multi-factorial disease driven by microbiol dysbiosis, primarily involving Malassezia yeast. Anti-fungal activity of ZnPT depends on the cutaneous availability of bioactive monomeric molecular species, occurring upon particle dissolution. The success of ZnPT as a topical therapeutic is underscored by the way it balances treatment efficacy with formulation safety. This review demonstrates how ZnPT achieves this balance, by integrating the current understanding of SD pathogenesis with an up-to-date analysis of ZnPT pharmacology, therapeutics and toxicology. ZnPT has anti-fungal activity with an average in vitro minimum inhibitory concentration of 10-15 ppm against the most abundant scalp skin Malassezia species (Malassezia globosa and Malassezia restrica). Efficacy is dependent on the targeted delivery of ZnPT to the skin sites where these yeasts reside, including the scalp surface and hair follicle infundibulum. Imaging and quantitative analysis tools have been fundamental for critically evaluating the therapeutic performance and safety of topical ZnPT formulations. Toxicologic investigations have focused on understanding the risk of local and systemic adverse effects following exposure from percutaneous penetration. Future research is expected to yield further advances in ZnPT formulations for SD and also include re-purposing towards a range of other dermatologic applications, which is likely to have significant clinical impact.

Effect of Wearing Surgical Face Masks on Gas Detection from Respiration Using Photoacoustic Spectroscopy.

Wearing surgical face masks is among the measures taken to mitigate coronavirus disease (COVID-19) transmission and deaths. Lately, concern was expressed about the possibility that gases from respiration could build up in the mask over time, causing medical issues related to the respiratory system. In this research study, the carbon dioxide concentration and ethylene in the breathing zone were measured before and immediately after wearing surgical face masks using the photoacoustic spectroscopy method. From the determinations of this study, the C2H4 was established to be increased by 1.5% after one hour of wearing the surgical face mask, while CO2 was established to be at a higher concentration of 1.2% after one hour of wearing the surgical face mask, when the values were correlated with the baseline (control).

Insights into the specificity for the interaction of the promiscuous SARS-CoV-2 nucleocapsid protein N-terminal domain with deoxyribonucleic acids.

The SARS-CoV-2 nucleocapsid protein (N) is a multifunctional promiscuous nucleic acid-binding protein, which plays a major role in nucleocapsid assembly and discontinuous RNA transcription, facilitating the template switch of transcriptional regulatory sequences (TRS). Here, we dissect the structural features of the N protein N-terminal domain (N-NTD) and N-NTD plus the SR-rich motif (N-NTD-SR) upon binding to single and double-stranded TRS DNA, as well as their activities for dsTRS melting and TRS-induced liquid-liquid phase separation (LLPS). Our study gives insights on the specificity for N-NTD(-SR) interaction with TRS. We observed an approximation of the triple-thymidine (TTT) motif of the TRS to ß-sheet II, giving rise to an orientation difference of ~25° between dsTRS and non-specific sequence (dsNS). It led to a local unfavorable energetic contribution that might trigger the melting activity. The thermodynamic parameters of binding of ssTRSs and dsTRS suggested that the duplex dissociation of the dsTRS in the binding cleft is entropically favorable. We showed a preference for TRS in the formation of liquid condensates when compared to NS. Moreover, our results on DNA binding may serve as a starting point for the design of inhibitors, including aptamers, against N, a possible therapeutic target essential for the virus infectivity.

Microsecond simulations and CD spectroscopy reveals the intrinsically disordered nature of SARS-CoV-2 spike-C-terminal cytoplasmic tail (residues 1242-1273) in isolation.

All available SARS-CoV-2 spike protein crystal and cryo-EM structures have shown missing electron densities for cytosolic C-terminal regions (CTR). Generally, the missing electron densities point towards the intrinsically disordered nature of the protein region (IDPR). This curiosity has led us to investigate the cytosolic CTR of the spike glycoprotein of SARS-CoV-2 in isolation. The spike CTR is supposed to be from 1235 to 1273 residues or 1242-1273 residues based on our used prediction. Therefore, we have demonstrated the structural conformation of cytosolic region and its dynamics through computer simulations up to microsecond timescale using OPLS and CHARMM forcefields. The simulations have revealed the unstructured conformation of cytosolic region. Further, we have validated our computational observations with circular dichroism (CD) spectroscopy-based experiments and found its signature spectra at 198 nm. We believe that our findings will surely help in understanding the structure-function relationship of the spike protein's cytosolic region.

Antimicrobial and Anticancer Application of Silver(I) Dipeptide Complexes.

Three silver(I) dipeptide complexes [Ag(GlyGly)]n(NO3)n (AgGlyGly), [Ag2(GlyAla)(NO3)2]n (AgGlyAla) and [Ag2(HGlyAsp)(NO3)]n (AgGlyAsp) were prepared, investigated and characterized by vibrational spectroscopy (mid-IR), elemental and thermogravimetric analysis and mass spectrometry. For AgGlyGly, X-ray crystallography was also performed. Their stability in biological testing media was verified by time-dependent NMR measurements. Their in vitro antimicrobial activity was evaluated against selected pathogenic microorganisms. Moreover, the influence of silver(I) dipeptide complexes on microbial film formation was described. Further, the cytotoxicity of the complexes against selected cancer cells (BLM, MDA-MB-231, HeLa, HCT116, MCF-7 and Jurkat) and fibroblasts (BJ-5ta) using a colorimetric MTS assay was tested, and the selectivity index (SI) was identified. The mechanism of action of Ag(I) dipeptide complexes was elucidated and discussed by the study in terms of their binding affinity toward the CT DNA, the ability to cleave the DNA and the ability to influence numbers of cells within each cell cycle phase. The new silver(I) dipeptide complexes are able to bind into DNA by noncovalent interaction, and the topoisomerase I inhibition study showed that the studied complexes inhibit its activity at a concentration of 15 µM.

Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications.

Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH2 scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.