Detection and classification of single viruses

Because of the devastating potential for rapid infection from a small amount of biological agents, biological weapons are likely candidates for future terrorist attacks. Through recent events we have already experienced the magnitude of the threat associated with biological agents. Examples are the disruption to our government caused by Anthrax spores or the economic harm caused by the SARS outbreak. Warfare viruses are especially dangerous because there are no existing cures. Early detection is the only defense against this threat, but because of the very small size of viruses it is extremely challenging to detect them. Today, this requires complex and expensive equipment and highly trained personal, and due to this complexity and cost, these means cannot be made widely available.
We believe that optical sensors can be developed to provide an accurate, simple, and affordable way of detecting small biological agents. There are many challenges remaining to build this sensor, but our studies show that a real-time single-virus detector is possible.
Viruses and other biological species can be characterized according to size, shape, and optical / spectroscopic properties. These properties allow them to be distinguished from other biological species and from other particulates such as dust particles.

Optical force for virus size and shape assessment

We developed a technique, where size and shape of a nanometer-size particle (virus particles can be considered as nanoparticles) are measured by detecting the optical gradient force. While being carried by fluid inside a flow-cell (see figure below), nanoparticle motion is perturbed by a strongly focused laser beam due to the optical force. Back-scattered light is detected by a photodiode which is integrated into a feedback loop with the modulator, which prevents clumps of viruses or other large particles from being trapped and thus from blocking the detector. The light scattered in forward direction is used to track particle position with respect to the focus.

Schematic of the optical gradient forces sensor

The particle motion perturbation is reflected in the temporal asymmetry of the detector signal. Such signal asymmetry yields information about the force exerted on the particles by the laser focus. Large particles, which experience strong forces while moving trough the laser focus, correspond to a highly asymmetric detector signal, whereas small particles pass the laser focus almost unperturbed thus rendering a symmetric signal.

Distribution for a sample of mixed 50nm and 100nm radius polystyrene beads in water based on force measurement

The outlined scheme is well suited for the detection of ellipsoidal particles. In addition to the optical force, the laser focus exerts a torque on the oddly shaped particles. When ellipsoidal particles move in random orientations towards the laser focus, the focus forces the particles to align in a certain direction. A change in orientation results in a change of the scattered field which can be seen as the modulation of the differential signal from the quadrant detector. The modulation frequency therefore provides information about eccentricity of the particles.

Background-free detection of viruses

Current optical detection methods which are well developed for single micrometer size particles, cannot be applied to to nanoparticles due to a strong signal dependence on particle size. Typically, such sensors consist of a light source which illuminates a sample volume of an aerosol or a liquid flow containing the particles of interest. An off-axis detectors measures power of scattered light. The latter is a function of particle properties such as size, concentration, and optical density. In the tens of nanometers size regime particles act as dipoles, therefore the power of scattered light is proportional to the sixth power of particles size. Lowering the detection size limits for the existing detectors places an impossible requirement on noise optimization. Therefore, a signal which has a weaker particle size dependence can allow access to smaller particles.
The detection scheme is schematically shown in the figure below. Using the electroosmotic effect, a particle solution is transported through a microfluidic channel. A laser beam is split by a beamsplitter into two perpendicular paths. One path serves as a reference for later interferometric recombination and the other path is focused with an objective lens into a single pre-selected nanochannel. The lateral dimensions of the nanochannels are comparable to the size of the laser focus ensuring that no more than one particle crosses the focus at any time. The backscattered light from a particle passing through the laser focus is collected with the same objective and is then recombined with the reference beam and directed onto a split photodetector. The power of the reference beam can be arbitrarily attenuated.

Schematic for the background-free interferometric single particle detection.

The intensity distribution on the detector surface is calculated as where subscript r denotes reference beam and s denotes scattered field. The signal measured by the split detector corresponds to the difference between two halves of the detector surface normalized by the total power incident on the detector. As the result, the signal is proportional to the interferometric term only. The interferometric term is proportional to the scattered field amplitude, which has a weaker particle size dependence, compared to the conventional sensors (third power of particle size).

(a) Data acquired for a mix of 15nm and 50nm polystyrene beads in water and (b) for a mix of 7nm and 20nm gold particles in water.

Live virus detection

The above principle of interferometric particle detection can be applied to a sample containing live viruses:

Data acquired Influenza A virus and 100nm polystyrene beads in HEPES

Raman scattering for chemically specific virus recognition

Different to elastic light scattering, inelastic light scattering results in an energy change of the scattered radiation. Examples of inelastic scattering are fluorescence and Raman scattering. In the latter, an incident photon interacts with the molecular vibrational modes of a sample. As a result, the spectrum of the scattered radiation contains vibrational lines that provide a unique and characteristic fingerprint for the chemical composition of a sample. Thus, Raman scattering can provide information about the inner protein structure of a virus and can be used to recognize different strains of the same virus family.
In the current project, we combine nanoparticle sizing methods with inelastic light scattering in order to add chemical specificity to the detection process. Such sensor would have the property of being able to sense smallest amounts of dangerous viruses, for example near buildings, luggage, or waste water. A single virus will be classified according to its size, shape, and its optical and spectroscopic properties.

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