Non-invasive analysis of stored red blood cells using diffuse resonance Raman spectroscopy.

A method to acquire the Raman spectra of sub-surface components using diffusely focused radiation in a microscope sampling configuration is described. This procedure generates Raman scattering at various sample depths by producing a converging beam at the back aperture of the objective lens. This method requires illumination of the sample with a defocused laser, while simultaneously increasing the number of CCD pixels that are binned along the spatial axis of the detector. We applied this diffuse sampling method to the analysis of stored red blood cells (RBCs). During storage, biochemical changes to RBCs occur (the "storage lesion"). However, there are no existing non-invasive methods to assess this. We evaluated the instrumental parameters needed to maximize the diffusely scattered signal, including pixel binning, slit width, and bandwidth. We demonstrated the effectiveness of this diffuse resonance Raman spectroscopy (DRRS) method by detecting RBCs through a blood bag segment (1 mm wall thickness). We directly compared the DRRS method to the more common stand-off Raman spectroscopy (SORS) method using both 633 nm and 785 nm excitation. Time-dependent DRRS spectra were used in a multivariate model for classification of RBCs in polymer segments by storage age. Young (6-8 day) RBCs were differentiated from old (35-40) RBCs with 100% sensitivity and 98.5% selectivity. These data indicated that DRRS is a promising, non-invasive technique for acquiring the spectra of sub-surface components, and is particularly applicable when the underlying sample can be resonantly enhanced.

Characterization of Storage-Induced Red Blood Cell Hemolysis Using Raman Spectroscopy.

BACKGROUND: The therapeutic efficacy and safety of stored red blood cells (RBCs) relies on minimal in-bag hemolysis. The accuracy of current methods of measuring hemolysis can suffer as a result of specimen collection and processing artefacts. OBJECTIVE: To test whether Raman spectroscopy could be used to assess hemolysis. METHODS: RBCs were stored for as long as 42 days. Raman spectra of RBCs were measured before and after washing, and hemolysis was measured in supernatant by visible spectroscopy. RESULTS: Raman spectra indicated increased concentrations of oxyhemoglobin (oxyHb) and methemoglobin (metHb), and decreased membrane fluidity with storage age. Changes in oxyHb and metHb were associated with the intraerythrocytic and extracellular fractions, respectively. Hemolysis increased in a storage age-dependent manner. Changes in Raman bands reflective of oxyHb, metHb, and RBC membranes correlated with hemolysis; the most statistically significant change was an increased intensity of metHb and decreased membrane fluidity. CONCLUSIONS: These data suggest that Raman spectroscopy may offer a new label-free modality to assess RBC hemolysis during cold storage.

A rapid and simple chemical method for the preparation of Ag colloids for surface-enhanced Raman spectroscopy using the Ag mirror reaction.

Colloidal silver (Ag) nanoparticles (AgNP) have been widely used for surface-enhanced Raman spectroscopy (SERS) applications. We report a simple, rapid and effective method to prepare AgNP colloids for SERS using the classic organic chemistry Ag mirror reaction with Tollens' reagent. The AgNP colloid prepared with this process was characterized using SEM, and the reaction conditions further optimized using SERS measurements. It was found that Ag mirror reaction conditions that included 20 mM AgNO3, 5 min reaction time, and 0.5 M glucose produced AgNP colloids with an average size of 319.1 nm (s.d ±128.1). These AgNP colloids exhibited a significant SERS response when adenine was used as the reporter molecule. The usefulness of these new AgNP colloids was demonstrated by detecting the nucleotides adenosine 5'-monophosphate (AMP), guanosine 5'-monophosphate (GMP), cytidine 5'-monophosphate (CMP), and uridine 5'-monophosphate (UMP). A detection limit of 500 nM for AMP was achieved with the as-prepared AgNP colloid. The bacterium Mycoplasma pneumoniae was also easily detected in laboratory culture with these SERS substrates. These findings attest to the applicability of this AgNP colloid for the sensitive and specific detection of both small biomolecules and microorganisms.

VARIABLE SELECTION AND BIOMARKER CORRELATION IN THE ANALYSIS OF MYCOPLASMA PNEUMONIAE STRAINS BY SURFACE-ENHANCED RAMAN SPECTROSCOPY.

Mycoplasma pneumoniae is a human respiratory tract pathogen causing chronic bronchitis and atypical or "walking" pneumonia. The major surface protein P1 must form complexes with proteins P30 and P40/P90 in order to function in receptor binding and gliding motility, and variability in P1 and P40/P90 distinguishes the two major M. pneumoniae genotypes. Strains belonging to each genotype can be differentiated with high sensitivity and specificity by utilizing surface-enhanced Raman spectroscopy on silver nanorod arrays. Here we used the variable selection method of Variable Importance in Projection (VIP) to identify Raman bands important in M. pneumoniae strain classification. Furthermore, VIP analysis of mutants lacking P40/P90, or P1and P40/P90, correlated certain Raman bands important in distinguishing genotypes, with specific mycoplasma surface protein composition and presentation. Variable selection, and its correlation with specific mycoplasma surface components, is an important next step in developing this platform for M. pneumoniae detection and genotyping.

Label-Free Detection of Glycan-Protein Interactions for Array Development by Surface-Enhanced Raman Spectroscopy (SERS).

A glyco-array platform has been developed, in which glycans are attached to plasmonic nanoparticles through strain-promoted azide-alkyne cycloaddition. Glycan-protein binding events can then be detected in a label-free manner employing surface-enhanced Raman spectroscopy (SERS). As proof of concept, we have analyzed the binding of Gal1, Gal3, and influenza hemagglutinins (HAs) to various glycans and demonstrated that binding partners can be identified with high confidence. The attraction of SERS for optical sensing is that it can provide unique spectral signatures for glycan-protein complexes, confirm identity through statistical validation, and minimizes false positive results common to indirect methods. Furthermore, SERS is very sensitive and has multiplexing capabilities thereby allowing the simultaneous detection of multiple analytes.

Detection of neuraminidase stalk motifs associated with enhanced N1 subtype influenza A virulence via Raman spectroscopy.

Oligonucleotides corresponding to neuraminidase (NA) stalk motifs that have been associated with enhanced influenza virulence have been identified using surface-enhanced Raman spectroscopy (SERS). 5'-Thiolated ssDNA oligonucleotides were immobilized onto a hexadecyltrimethylammonium bromide (CTAB) coated Au nanoparticles (AuNP). Three synthetic RNA sequences corresponding to specific amino acid deletions in the influenza NA stalk region were attached to the CTAB-modified AuNPs. Two of these sequences were specific to sequences with amino acid deletions associated with increased virulence, and one was a low virulence sequence with no amino acid deletions. Hybridization of synthetic matched and mismatched DNA-RNA complexes were detected based on the intrinsic SERS spectra. In addition, this platform was used to analyze RNA sequences isolated from laboratory grown influenza viruses having the NA stalk motif associated with enhanced virulence, including A/WSN/33/H1N1, A/Anhui/1/2005/H5N, and A/Vietnam/1203/2004/H5N1 strains. Multivariate feature selection methods were employed to determine the specific wavenumbers in the Raman spectra that contributed the most information for class discrimination. A one-way analysis of variance (ANOVA) test identified 884 and 1196 wavenumbers as being highly significant in the high and low virulence spectra, respectively (p < 0.01). A post-hoc Tukey Honestly Significance Difference (HSD) test identified the wavenumbers that played a major role in differentiating the DNA-RNA hybrid classes. An estimate of the spectral variability, based on the Wilcoxon rank sum test, found the major source of variation to be predominately between the different classes, and not within the classes, thus confirming that the spectra reflected real class differences and not sampling artifacts. The multivariate classification methods partial least squares discriminant analysis (PLS-DA) and support vector machine discriminant analysis (SVM-DA) were able to distinguish between different NA stalk-motifs linked to NA-enhanced influenza virus virulence (NA-EIV) with >95% sensitivity and specificity in both synthetic RNA sequences as well as the isolated viral RNA. This study demonstrates the feasibility of SERS for direct identification of influenza NA stalk mutations associated with virulence without sample amplification or labeling.

Specificity and Strain-Typing Capabilities of Nanorod Array-Surface Enhanced Raman Spectroscopy for Mycoplasma pneumoniae Detection.

Mycoplasma pneumoniae is a cell wall-less bacterial pathogen of the human respiratory tract that accounts for > 20% of all community-acquired pneumonia (CAP). At present the most effective means for detection and strain-typing is quantitative polymerase chain reaction (qPCR), which can exhibit excellent sensitivity and specificity but requires separate tests for detection and genotyping, lacks standardization between available tests and between labs, and has limited practicality for widespread, point-of-care use. We have developed and previously described a silver nanorod array-surface enhanced Raman Spectroscopy (NA-SERS) biosensing platform capable of detecting M. pneumoniae with statistically significant specificity and sensitivity in simulated and true clinical throat swab samples, and the ability to distinguish between reference strains of the two main genotypes of M. pneumoniae. Furthermore, we have established a qualitative lower endpoint of detection for NA-SERS of < 1 genome equivalent (cell/µl) and a quantitative multivariate detection limit of 5.3 ± 1 cells/µl. Here we demonstrate using partial least squares- discriminatory analysis (PLS-DA) of sample spectra that NA-SERS correctly identified M. pneumoniae clinical isolates from globally diverse origins and distinguished these from a panel of 12 other human commensal and pathogenic mycoplasma species with 100% cross-validated statistical accuracy. Furthermore, PLS-DA correctly classified by strain type all 30 clinical isolates with 96% cross-validated accuracy for type 1 strains, 98% cross-validated accuracy for type 2 strains, and 90% cross-validated accuracy for type 2V strains.

The multivariate detection limit for Mycoplasma pneumoniae as determined by nanorod array-surface enhanced Raman spectroscopy and comparison with limit of detection by qPCR.

Mycoplasma pneumoniae is a cell wall-less bacterial pathogen of the human respiratory tract that accounts for up to 20% of community-acquired pneumonia. At present, the standard for detection and genotyping is quantitative polymerase chain reaction (qPCR), which can exhibit excellent sensitivity but lacks standardization and has limited practicality for widespread, point-of-care use. We previously described a Ag nanorod array-surface enhanced Raman spectroscopy (NA-SERS) biosensing platform capable of detecting M. pneumoniae in simulated and true clinical throat swab samples with statistically significant specificity and sensitivity. We report here that differences in sample preparation influence the integrity of mycoplasma cells for NA-SERS analysis, which in turn impacts the resulting spectra. We have established a multivariate detection limit (MDL) using NA-SERS for M. pneumoniae intact-cell sample preparations. Using an adaptation of International Union of Pure and Applied Chemistry (IUPAC)-recommended methods for analyzing multivariate data sets, we found that qPCR had roughly 10× better detection limits than NA-SERS when expressed in CFU ml(-1) and DNA concentration (fg). However, the NA-SERS MDL for intact M. pneumoniae was 5.3 ± 1.0 genome equivalents (cells per µl). By comparison, qPCR of a parallel set of samples yielded a limit of detection of 2.5 ± 0.25 cells per µl. Therefore, for certain standard metrics NA-SERS provides a multivariate detection limit for M. pneumoniae that is essentially identical to that determined via qPCR.

Layer-by-layer polyelectrolyte encapsulation of Mycoplasma pneumoniae for enhanced Raman detection.

Mycoplasma pneumoniae is a major cause of respiratory disease in humans and accounts for as much as 20% of all community-acquired pneumonia. Existing mycoplasma diagnosis is primarily limited by the poor success rate at culturing the bacteria from clinical samples. There is a critical need to develop a new platform for mycoplasma detection that has high sensitivity, specificity, and expediency. Here we report the layer-by-layer (LBL) encapsulation of M. pneumoniae cells with Ag nanoparticles in a matrix of the polyelectrolytes poly(allylamine hydrochloride) (PAH) and poly(styrene sulfonate) (PSS). We evaluated nanoparticle encapsulated mycoplasma cells as a platform for the differentiation of M. pneumoniae strains using surface enhanced Raman scattering (SERS) combined with multivariate statistical analysis. Three separate M. pneumoniae strains (M129, FH and II-3) were studied. Scanning electron microscopy and fluorescence imaging showed that the Ag nanoparticles were incorporated between the oppositely charged polyelectrolyte layers. SERS spectra showed that LBL encapsulation provides excellent spectral reproducibility. Multivariate statistical analysis of the Raman spectra differentiated the three M. pneumoniae strains with 97-100% specificity and sensitivity, and low (0.1-0.4) root mean square error. These results indicated that nanoparticle and polyelectrolyte encapsulation of M. pneumoniae is a potentially powerful platform for rapid and sensitive SERS-based bacterial identification.

Identification of virulence determinants in influenza viruses.

To date there is no rapid method to screen for highly pathogenic avian influenza strains that may be indicators of future pandemics. We report here the first development of an oligonucleotide-based spectroscopic assay to rapidly and sensitively detect a N66S mutation in the gene coding for the PB1-F2 protein associated with increased virulence in highly pathogenic pandemic influenza viruses. 5'-Thiolated ssDNA oligonucleotides were employed as probes to capture RNA isolated from six influenza viruses, three having N66S mutations, two without the N66S mutation, and one deletion mutant not encoding the PB1-F2 protein. Hybridization was detected without amplification or labeling using the intrinsic surfaced-enhanced Raman spectrum of the DNA-RNA complex. Multivariate analysis identified target RNA binding from noncomplementary sequences with 100% sensitivity, 100% selectivity, and 100% correct classification in the test data set. These results establish that optical-based diagnostic methods are able to directly identify diagnostic indicators of virulence linked to highly pathogenic pandemic influenza viruses without amplification or labeling.

Identification of mycobacteria based on spectroscopic analyses of mycolic acid profiles.

This report examines lipophilic extracts containing mycolic acids isolated from tuberculosis (MTB) and non-tuberculosis (NTM) mycobacterial strains using chromatography, mass spectrometry (MS), nuclear magnetic resonance (NMR), and Raman spectroscopy. Gas chromatography-MS was used to identify major fatty acid mycolate components, while proton NMR confirmed the presence of characteristic cis- and trans-cyclopropane rings within different mycolic acid sub-types. Surface-enhanced Raman (SERS) spectra were obtained from the mycolic acids extracted from the bacterial cell envelopes of the MTB or NTM mycobacterial species. The Raman spectral profiles were used to develop a classification method based on chemometrics for identification of the mycobacterial species. Multivariate statistical analysis methods, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and partial least squares discriminant analysis (PLS-DA) of the SERS spectra enabled differentiation of NTM mycobacteria from one another with 100% accuracy. These methods are also sensitive enough to differentiate clinically-isolated MTB strains that differed only by the presence or absence of a single extracytoplasmic sigma factor with 83-100% sensitivity and 80-100% specificity. The current work is the first report on discrimination of mycobacteria strains based on the SERS spectra of the constituent mycolic acids in lipophilic extracts. These results suggest that SERS can be used as an accurate and sensitive method for species and strain discrimination in mycobacteria.

Detection of genetic markers related to high pathogenicity in influenza by SERS.

We have developed a method for the detection of genetic markers associated with high pathogenicity in influenza. The assay consists of an array of 5'-thiolated ssDNA oligonucleotides immobilized on the surface of a Ag nanorod substrate that serve as capture probes for the detection of synthetic RNA sequences coding for a genetic mutation in the influenza PB1-F2 protein. Hybridization of the DNA probes to their complementary RNA sequences was detected using surface-enhanced Raman spectroscopy (SERS). Multivariate statistical analysis was used to differentiate the spectra of the complementary DNA probe-RNA target hybrids from those of the non-complementary DNA probes containing a single base pair polymorphism. Hierarchical cluster analysis (HCA) was able to distinguish with 100% accuracy the spectra of the complementary DNA probe-RNA target from the spectra of the immobilized DNA probes alone, or the DNA probes incubated with non-complementary RNA sequences. Linearity of response and limits of sensitivity of the SERS-based assays were determined using a partial least squares (PLS) regression model; detection limits computed by PLS was determined to be ~10 nM. The binding affinity of the DNA probes to their complementary RNA sequences was confirmed using enzyme-linked immunosorbent assay (ELISA); however, the detection limits observed using ELISA were approximately 10× higher (~100 nM) than those determined by PLS analysis of the SERS spectra.

Ag nanorod based surface-enhanced Raman spectroscopy applied to bioanalytical sensing.

Recent progress in substrate nanofabrication has led to the development of Ag nanorod arrays as uniform, reproducible, large area SERS-active substrates with high signal enhancement. These novel nanostructures fabricated by oblique angle vapor deposition (OAD) offer a robust platform for the rapid detection of biological agents and open new perspectives for the development and integration of biomedical diagnostic for clinical and therapeutic applications. Ag nanorod arrays have been investigated as SERS-active substrates for the detection and identification of pathogens, including bacteria and viruses, as well as to evaluate the potential of this biosensing platform for bio-recognition of high affinity events using oligonucleotide-modified substrates. This review summarizes the various nanostructured substrates designed for SERS-based applications, highlights the nanofabrication methodology used to produce Ag nanorod arrays, outlines their morphological and physical properties, and provides a summary of the most recent uses of these substrates for clinical diagnostic and biomedical applications.

Direct optical detection of viral nucleoprotein binding to an anti-influenza aptamer.

We have demonstrated label-free optical detection of viral nucleoprotein binding to a polyvalent anti-influenza aptamer by monitoring the surface-enhanced Raman (SERS) spectra of the aptamer-nucleoprotein complex. The SERS spectra demonstrated that selective binding of the aptamer-nucleoprotein complex could be differentiated from that of the aptamer alone based solely on the direct spectral signature for the aptamer-nucleoprotein complex. Multivariate statistical methods, including principal components analysis, hierarchical clustering, and partial least squares, were used to confirm statistically significant differences between the spectra of the aptamer-nucleoprotein complex and the spectra of the unbound aptamer. Two separate negative controls were used to evaluate the specificity of binding of the viral nucleoproteins to this aptamer. In both cases, no spectral changes were observed that showed protein binding to the control surfaces, indicating a high degree of specificity for the binding of influenza viral nucleoproteins only to the influenza-specific aptamer. Statistical analysis of the spectra supports this interpretation. AFM images demonstrate morphological changes consistent with formation of the influenza aptamer-nucleoprotein complex. These results provide the first evidence for the use of aptamer-modified SERS substrates as diagnostic tools for influenza virus detection in a complex biological matrix.

Detection and differentiation of avian mycoplasmas by surface-enhanced Raman spectroscopy based on a silver nanorod array.

Mycoplasma gallisepticum is a bacterial pathogen of poultry that is estimated to cause annual losses exceeding $780 million. The National Poultry Improvement Plan guidelines recommend regular surveillance and intervention strategies to contain M. gallisepticum infections and ensure mycoplasma-free avian stocks, but several factors make detection of M. gallisepticum and diagnosis of M. gallisepticum infection a major challenge. Current techniques are laborious, require special expertise, and are typically plagued by false results. In this study, we describe a novel detection strategy which uses silver nanorod array-surface-enhanced Raman spectroscopy (NA-SERS) for direct detection of avian mycoplasmas. As a proof of concept for use in avian diagnostics, we used NA-SERS to detect and differentiate multiple strains of avian mycoplasma species, including Acholeplasma laidlawii, Mycoplasma gallinarum, Mycoplasma gallinaceum, Mycoplasma synoviae, and M. gallisepticum, including vaccine strains 6/85, F, and ts-11. Chemometric multivariate analysis of spectral data was used to classify these species rapidly and accurately, with >93% sensitivity and specificity. Furthermore, NA-SERS had a lower limit of detection that was 100-fold greater than that of standard PCR and comparable to that of real-time quantitative PCR. Detection of M. gallisepticum in choanal cleft swabs from experimentally infected birds yielded good sensitivity and specificity, suggesting that NA-SERS is applicable for clinical detection.

Detection of viral nucleoprotein binding to anti-influenza aptamers via SERS.

A highly sensitive surface-enhanced Raman (SERS)-based method for detection of influenza viral nucleoproteins is described. The intrinsic SERS spectrum of the aptamer-nucleoprotein complex provides direct evidence of binding between a polyvalent anti-influenza aptamer and the nucleoproteins of three influenza strains.

Removal of surface contamination and self-assembled monolayers (SAMs) from silver (Ag) nanorod substrates by plasma cleaning with argon.

Surface contamination of surface-enhanced Raman (SERS)-active metallic substrates has been a limitation to the utility of SERS as an analytical technique, potentially affecting surface coverage, spectral reproducibility, and analytical limits of detection. We have developed a simple and versatile cleaning method for SERS-active Ag nanorod arrays that consists of a short (4 min) exposure of the substrate to an Ar(+) plasma in a low-pressure environment. The findings presented here demonstrate that this cleaning procedure essentially eliminates organic background contamination. This procedure works equally well for self-assembled monolayers of thiolates that strongly adsorb onto Au and Ag surfaces. For SERS-active surfaces composed of arrays of Ag nanorods prepared by oblique-angle vapor deposition, we investigated the (1) Raman band intensities, (2) nanorod morphology via scanning electron microscopy, and (3) surface hydrophobicity via static contact angle measurements, as a function of exposure time of the Ag nanorods to the Ar(+) plasma. Short (4 min) exposure to Ar(+) plasma eliminated background contamination but decreased the observed SERS intensity for re-adsorbed analytes by approximately a factor of 2 while leaving the nanorod morphology essentially unchanged. Prolonged exposure to Ar(+) plasma (>10 min) resulted in substantial morphological changes of the Ag nanorod lattice and led to a decrease in the observed SERS intensities by a factor of 10. The results presented here suggest that Ar(+) plasma cleaning is an efficient process for removing carbonaceous and organic contamination as well as thiolate monolayers from SERS-active Ag surfaces, as long as the plasma conditions and exposure times are carefully monitored.

Detection of Mycoplasma pneumoniae in simulated and true clinical throat swab specimens by nanorod array-surface-enhanced Raman spectroscopy.

The prokaryote Mycoplasma pneumoniae is a major cause of respiratory disease in humans, accounting for 20% of all community-acquired pneumonia and the leading cause of pneumonia in older children and young adults. The limitations of existing options for mycoplasma diagnosis highlight a critical need for a new detection platform with high sensitivity, specificity, and expediency. Here we evaluated silver nanorod arrays (NA) as a biosensing platform for detection and differentiation of M. pneumoniae in culture and in spiked and true clinical throat swab samples by surface-enhanced Raman spectroscopy (SERS). Three M. pneumoniae strains were reproducibly differentiated by NA-SERS with 95%-100% specificity and 94-100% sensitivity, and with a lower detection limit exceeding standard PCR. Analysis of throat swab samples spiked with M. pneumoniae yielded detection in a complex, clinically relevant background with >90% accuracy and high sensitivity. In addition, NA-SERS correctly classified with >97% accuracy, ten true clinical throat swab samples previously established by real-time PCR and culture to be positive or negative for M. pneumoniae. Our findings suggest that the unique biochemical specificity of Raman spectroscopy, combined with reproducible spectral enhancement by silver NA, holds great promise as a superior platform for rapid and sensitive detection and identification of M. pneumoniae, with potential for point-of-care application.

Identification of individual genotypes of measles virus using surface enhanced Raman spectroscopy.

A spectroscopic assay based on surface-enhanced Raman spectroscopy (SERS) has been developed for rapid genotyping of the measles virus (MeV). Silver nanorods fabricated using an oblique angle vapor deposition method acted as the SERS-active substrate. The SERS spectra of four separate MeV genotypes, i.e. A, H1, D4 and D9, and two separate negative media control samples were analyzed using multivariate statistical methods. Principal components analysis (PCA) and hierarchical cluster analysis (HCA) successfully separated three of the four MeV genotypes studied. The MeV genotypes used in this study had >96% sequence similarity as monitored using the MeV hemagglutinin (H) gene, and the clustering seen in PCA and HCA mirrored this sequence diversity. For example, the MeV genotypes with the highest sequence diversity (~3%, A and H1) were the most widely separated in the PCA scores plot and HCA dendogram. Conversely, the MeV genotypes with the lowest sequence diversity (~0.5%, D4 and D9) could not be statistically differentiated. However, a supervised chemometric method, partial least squares-discriminant analysis (PLS-DA) was able to separate each of the four MeV strains, the two negative controls, and the background, with >90% sensitivity and >96% selectivity based solely on their inherent SERS spectra. These results demonstrate that SERS, in combination with multivariate statistical methods, is a highly sensitive and rapid viral identification and classification method that can be applied to MeV genotyping.

Rapid and sensitive detection of rotavirus molecular signatures using surface enhanced Raman spectroscopy.

Human enteric virus infections range from gastroenteritis to life threatening diseases such as myocarditis and aseptic meningitis. Rotavirus is one of the most common enteric agents and mortality associated with infection can be very significant in developing countries. Most enteric viruses produce diseases that are not distinct from other pathogens, and current diagnostics is limited in breadth and sensitivity required to advance virus detection schemes for disease intervention strategies. A spectroscopic assay based on surface enhanced Raman scattering (SERS) has been developed for rapid and sensitive detection of rotavirus. The SERS method relies on the fabrication of silver nanorod array substrates that are extremely SERS-active allowing for direct structural characterization of viruses. SERS spectra for eight rotavirus strains were analyzed to qualitatively identify rotaviruses and to classify each according to G and P genotype and strain with >96% accuracy, and a quantitative model based on partial least squares regression analysis was evaluated. This novel SERS-based virus detection method shows that SERS can be used to identify spectral fingerprints of human rotaviruses, and suggests that this detection method can be used for pathogen detection central to human health care.