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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<sup>−10</sup> to 10<sup>0</sup> are indicated; std, DNA size standard (350 kbp); +, positive control (277 kbp). Starting concentration, 1.8×10<sup>9</sup> 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