Cell-free hemoglobin is a marker of systemic inflammation in mouse models of sepsis: a Raman spectroscopic study.

Sepsis is a life-threatening condition caused by heightened host immune responses post infection. Despite intensive research, most of the existing diagnostic methods remain non-specific, labour-intensive, time-consuming or are not sensitive enough for rapid and timely diagnosis of the onset and progression of sepsis. The present work was undertaken to explore the potential of Raman spectroscopy to identify the biomarkers of sepsis in a label-free and minimally invasive manner using different mouse models of inflammation. The sera of BALB/c mice infected with Salmonella Typhimurium reveal extensive hemolysis, as indicated by the Raman bands that are characteristic of the porphyrin ring of hemoglobin (668, 743, 1050, 1253 and 1397 cm-1) which increase in a kinetic manner. These markers are also observed in a lipopolysaccharide-induced endotoxic shock model, but not in a thioglycollate-induced sterile peritonitis model. These data demonstrate that hemolysis is a signature of systemic, but not localised, inflammation. To further validate our observations, sepsis was induced in the nitric oxide synthase 2 (Nos2-/-) deficient strain which is more sensitive to infection. Interestingly, Nos2-/- mice exhibit a higher degree of hemolysis than C57BL/6 mice. Sepsis-induced hemolysis was also confirmed using resonance Raman spectroscopy with 442 nm excitation which demonstrated a pronounced increase in the resonant Raman bands at 670 and 1350 cm-1 in sera of the infected mice. This is the first study to identify inflammation-induced hemolysis in mouse models of sepsis using Raman spectral signatures for hemoglobin. The possible implications of this method in detecting hemolysis in different inflammatory pathologies, such as the ongoing COVID-19 pandemic, are discussed.

A Review on SERS-Based Detection of Human Virus Infections: Influenza and Coronavirus.

The diagnosis of respiratory viruses of zoonotic origin (RVsZO) such as influenza and coronaviruses in humans is crucial, because their spread and pandemic threat are the highest. Surface-enhanced Raman spectroscopy (SERS) is an analytical technique with promising impact for the point-of-care diagnosis of viruses. It has been applied to a variety of influenza A virus subtypes, such as the H1N1 and the novel coronavirus SARS-CoV-2. In this work, a review of the strategies used for the detection of RVsZO by SERS is presented. In addition, relevant information about the SERS technique, anthropozoonosis, and RVsZO is provided for a better understanding of the theme. The direct identification is based on trapping the viruses within the interstices of plasmonic nanoparticles and recording the SERS signal from gene fragments or membrane proteins. Quantitative mono- and multiplexed assays have been achieved following an indirect format through a SERS-based sandwich immunoassay. Based on this review, the development of multiplex assays that incorporate the detection of RVsZO together with their specific biomarkers and/or secondary disease biomarkers resulting from the infection progress would be desirable. These configurations could be used as a double confirmation or to evaluate the health condition of the patient.

An efficient primary screening of COVID-19 by serum Raman spectroscopy.

The outbreak of COVID-19 coronavirus disease around the end of 2019 has become a pandemic. The preferred method for COVID-19 detection is the real-time polymerase chain reaction (RT-PCR)-based technique; however, it also has certain limitations, such as sample-dependent procedures with a relatively high false negative ratio. We propose a safe and efficient method for screening COVID-19 based on Raman spectroscopy. A total of 177 serum samples are collected from 63 confirmed COVID-19 patients, 59 suspected cases, and 55 healthy individuals as a control group. Raman spectroscopy is adopted to analyze these samples, and a machine learning support-vector machine (SVM) method is applied to the spectrum dataset to build a diagnostic algorithm. Furthermore, 20 independent individuals, including 5 asymptomatic COVID-19 patients and 5 symptomatic COVID-19 patients, 5 suspected patients, and 5 healthy patients, were sampled for external validation. In these three groups-confirmed COVID-19, suspected, and healthy individuals-the distribution of statistically significant points of difference showed highly consistency for intergroups after repeated sampling processes. The classification accuracy between the COVID-19 cases and the suspected cases is 0.87 (95% confidence interval [CI]: 0.85-0.88), and the accuracy between the COVID-19 and the healthy controls is 0.90 (95% CI: 0.89-0.91), while the accuracy between the suspected cases and the healthy control group is 0.68 (95% CI: 0.67-0.73). For the independent test dataset, we apply the obtained SVM model to the classification of the independent test dataset to have all the results correctly classified. Our model showed that the serum-level classification results were all correct for independent test dataset. Our results suggest that Raman spectroscopy could be a safe and efficient technique for COVID-19 screening.

Development of integrated microfluidic platform coupled with Surface-enhanced Raman Spectroscopy for diagnosis of COVID-19.

Corona Virus Disease 19 (COVID-19) pandemic has created an alarming situation across the globe. Varieties of diagnostic protocols are being developed for the diagnosis of COVID-19. Many of these diagnostic protocols however, have limitations such as for example unacceptable no of false-positive and false-negative cases, particularly during the early stages of infection. At present, the real-time (quantitative) reverse transcriptase-polymerase chain reaction (RT-PCR) is considered the gold standard for COVID-19 diagnosis. However, RT-PCR based tests are complex, expensive, time consuming and involve pre-processing of samples. A swift, sensitive, inexpensive protocol for mass screening is urgently needed to contain this pandemic. There is urgent need to harness new powerful technologies for accurate detection not only of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) but also combating the emergence of pandemics of new viruses as well. To overcome the current challenges, the authors propose a diagnostic protocol based on Surface-enhanced Raman Spectroscopy (SERS) coupled with microfluidic devices containing integrated microchannels functionalized either with vertically aligned Au/Ag coated carbon nanotubes or with disposable electrospun micro/nano-filter membranes. These devices have the potential to successfully trap viruses from diverse biological fluids/secretions including saliva, nasopharyngeal, tear etc. These can thus enrich the viral titre and enable accurate identification of the viruses from their respective Raman signatures. If the device is successfully developed and proven to detect target viruses, it would facilitate rapid screening of symptomatic as well as asymptomatic individuals of COVID-19. This would be a valuable diagnostic tool not only for mass screening of current COVID-19 pandemic but also in viral pandemic outbreaks of future.

Exploring optical spectroscopic techniques and nanomaterials for virus detection.

Viral infections pose significant health challenges globally by affecting millions of people worldwide and consequently resulting in a negative impact on both socioeconomic development and health. Corona virus disease 2019 (COVID-19) is a clear example of how a virus can have a global impact in the society and has demonstrated the limitations of detection and diagnostic capabilities globally. Another virus which has posed serious threats to world health is the human immunodeficiency virus (HIV) which is a lentivirus of the retroviridae family responsible for causing acquired immunodeficiency syndrome (AIDS). Even though there has been a significant progress in the HIV biosensing over the past years, there is still a great need for the development of point of care (POC) biosensors that are affordable, robust, portable, easy to use and sensitive enough to provide accurate results to enable clinical decision making. The aim of this study was to present a proof of concept for detecting HIV-1 pseudoviruses by using anti-HIV1 gp41 antibodies as capturing antibodies. In our study, glass substrates were treated with a uniform layer of silane in order to immobilize HIV gp41 antibodies on their surfaces. Thereafter, the HIV pseudovirus was added to the treated substrates followed by addition of anti-HIV gp41 antibodies conjugated to selenium nanoparticle (SeNPs) and gold nanoclusters (AuNCs). The conjugation of SeNPs and AuNCs to anti-HIV gp41 antibodies was characterized using UV-vis spectroscopy, transmission electron microscopy (TEM) and zeta potential while the surface morphology was characterized by fluorescence microscopy, atomic force microscopy (AFM) and Raman spectroscopy. The UV-vis and zeta potential results showed that there was successful conjugation of SeNPs and AuNCs to anti-HIV gp41 antibodies and fluorescence microscopy showed that antibodies immobilized on glass substrates were able to capture intact HIV pseudoviruses. Furthermore, AFM also confirmed the capturing HIV pseudoviruses and we were able to differentiate between substrates with and without the HIV pseudoviruses. Raman spectroscopy confirmed the presence of biomolecules related to HIV and therefore this system has potential in HIV biosensing applications.