Composition for personal growth : program design and evaluation.

<p>Two categories were used for cross-validation of the model, either type 1 or type 2. Clinical isolates were treated as an unknown class and cross-validated sensitivity, specificity, and class error were based on their classification prediction score with their respective reference strain control class. CV, cross-validated.</p><p>Cross-validated PLS-DA modeling statistics for the prediction performance for NA-SERS typing of individual type 1 and 2 <i>M</i>. <i>pneumoniae</i> clinical isolates.</p

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

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

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

PCR analysis of serial dilutions of <i>M. pneumoniae</i> strain II-3.

<p>Dilutions 10⁻¹⁰ to 10⁰ are indicated; std, DNA size standard (350 kbp); +, positive control (277 kbp). Starting concentration, 1.8×10⁹ CFU/ml.</p

Differentiation of <i>M. pneumoniae</i> strains.

<p>(<b>A</b>) Average spectra (n = 15) of <i>M. pneumoniae</i> strains with formalin background, baseline corrected and offset; and (<b>B</b>) first derivative spectra from panel A demonstrating strong similarities but also clear differences (boxes) among the strains.</p

PLS-DA of throat swabs spiked with serial dilutions of <i>M. pneumoniae</i>.

a<p>abbreviations same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013633#pone-0013633-t001" target="_blank">Table 1</a>.</p

PLS-DA of true clinical throat swab samples from different individuals.

<p>Gray symbols, samples previously shown to be <i>M. pneumoniae-</i>negative (Mp-negative) by culture and real-time PCR from five persons; open symbols, samples previously shown to be <i>M. pneumoniae-</i>positive (Mp-positive) by culture and real-time PCR from five persons. Five or six spectra were collected for each sample, in duplicate.</p

PLS-DA of NA-SERS specificity and sensitivity in discriminating three <i>M. pneumoniae</i> strains and two negative controls (formalin and water).

a<p>abbreviations the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013633#pone-0013633-t001" target="_blank">Table 1</a>; single model generated using 12 latent variables accounting for 88% of the total variance for all serial dilutions of each strain.</p

Principal Component and Hierarchal Cluster Analyses.

<p>Chemometric analysis was conducted on the spectral data from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013633#pone-0013633-g002" target="_blank">Figure 2</a>. (<b>A</b>) PC scores plot 1vs. 3 of <i>M. pneumoniae</i> strains FH, M129, and II-3, as indicated. 77% of the variance was captured in PC1 and 3% in PC3 to distinguish the strains. (<b>B</b>) HCA of pre-processed spectra of <i>M. pneumoniae</i> strains FH (dashed lines), M129 (solid lines), and II-3 (bold lines). Four spectra from strain II-3 were misclassified with FH (at left).</p