Biomedical subjects

Gregory P Stone

Publications and source records attributed to Gregory P Stone.

3 recordsLinked to original sources

PubMed2006

Autonomous reovirus strain classification using filament-coupled antibodies.

We previously described a filament-based antibody recognition assay (FARA) that generates ELISA-like sandwich structures immobilized on a filament. FARA allows the coupling of antibodies to precise locations along a filament, on-line fluorescence detection of captured pathogen, and feedback-directed filament motion. These properties suggest that this approach might be useful as an automated means to rapidly classify unknown pathogens. In this report, we describe validation of the novel decision tree aspect of this technology using mammalian reovirus. Based on available antibodies, we developed a decision tree algorithm to detect virus with increasing specificity at each level of the tree. Using three strains of reovirus and a bacteriophage control, our system correctly classified the reovirus strains at a concentration of 2 x 10(12) virions ml(-1) and M13K07 phage at 3 x 10(11) virions ml(-1). Classification of reovirus strain type 3 Dearing (T3D) required three levels of testing: general reovirus classification in level 1, serotype 3 classification in level 2, and final T3D strain classification in level 3. Strain T3SA + also required three levels of testing before a final classification was returned in level 3. Classification of strain type 1 Lang (T1L) required two levels of testing. M13K07 phage detection required only one level of testing for classification. These results indicate that automated pathogen classification using FARA is feasible. Furthermore, the simplicity of the design could be exploited for development of more complex sub-classification networks with additional levels and branches.

Antibodies, Viral↗

PubMed2005

Virus detection using filament-coupled antibodies.

Two attractive features of ELISA are the specificity of antibody-antigen recognition and the sensitivity achieved by enzymatic amplification. This report describes the development of a non-enzymatic molecular recognition platform adaptable to point-of-care clinical settings and field detection of biohazardous materials. This filament-antibody recognition assay (FARA) is based on circumferential bands of antibody probes coupled to a 120 microm diameter polyester filament. One advantage of this design is that automated processing is achieved by sequential positioning of filament-coupled probes through a series of 25-60 microL liquid filled microcapillary chambers. This approach was evaluated by testing for the presence of M13KO7 bacterial virus using anti-M13KO7 IgG(1) monoclonal antibody coupled to a filament. Filament motion first positioned the antibodies within a microcapillary tube containing a solution of M13KO7 virus before moving the probes through subsequent chambers, where the filament-coupled probes were washed, exposed to a fluorescently labeled anti-M13K07 antibody, and washed again. Filament fluorescence was then measured using a flatbed microarray scanner. The presence of virus in solution produced a characteristic increase in filament fluorescence only in regions containing coupled antibody probes. Even without the enzymatic amplification of a typical ELISA, the presence of 8.3 x 10(8) virus particles produced a 30-fold increase in fluorescence over an immobilized negative control antibody. In an ELISA comparison study, the filament-based approach had a similar lower limit of sensitivity of approximately 1.7 x 10(7) virus particles. This platform may prove attractive for point-of-care settings, the detection of biohazardous materials, or other applications where sensitive, rapid, and automated molecular recognition is desired.

Antibodies, Monoclonal↗

PubMedDate not supplied

Adaptive virus detection using filament-coupled antibodies.

We recently reported the development of a filament-antibody recognition assay (FARA), in which the presence of virions in solution initiates the formation of enzyme-linked immunosorbent assay (ELISA)-like antibody complexes. The unique features of this assay are that processing is achieved by motion of a filament and that, in the presence of a virus, antibody-virus complexes are coupled to the filament at known locations. In this work, we combine the unique features of this assay with a 638-nm laser-based optical detector to enable adaptive control of virus detection. Integration of on-line fluorescence detection yields approximately a five-fold increase in signal-to-noise ratio (SNR) compared to the fluorescence detection method reported previously. A one-minute incubation with an M13K07 test virus is required to detect 10(10) virionsml, and 40 min was required to detect 10(8) virionsml. In tests of the components of an adaptive strategy, a 30-min virus (3.3 x 10(10) virionsml) incubation time, followed by repositioning the filament-captured virus either within the detecting antibody chamber, (20 microg ml) or within the virus chamber, found an increase in signal roughly proportional to the cumulative residence times in these chambers. Furthermore, cumulative fluorescence signals observed for a filament-captured virus after repeated positioning of the filament within the virus chamber are similar to those observed for a single long incubation time. The unique features of the FARA-like design combined with online optical detection to direct subsequent bioprocessing steps provides new flexibility for developing adaptive molecular recognition assays.

Antigen-Antibody Complex↗