FIELD

The present disclosure relates to a method and apparatus for rapidly detecting and identifying protein-based compounds including bacteria, virus, drugs, or tissue abnormalities, and more particularly a portable Raman spectroscopy based spectroscope which is adaptable for examining mucosal surfaces (nares, oral, ear), interrogating a wound site and/or inspection of a potentially contaminated object or surface for protein-based compounds including MRSA or other pathogens. The device can be adapted to interrogate tissue specimens, stool, urine, serum or secretions.

BACKGROUND

This section provides background information related to the present disclosure which is not necessarily prior art.

Methicillin resistance ofStaphylococcus aureus(MRSA) is determined by the mecA gene which is carried by a mobile genetic element, designated staphylococcal cassette chromosome mec (SCCmec). MecA encodes a beta-lactam-resistant penicillin-binding protein called PBP2a (or PBP2′). Beta-lactam antibiotics normally bind to PBPs in the cell wall disrupting the synthesis of the peptidoglycan layer which results in bacterium death. However, since the beta-lactam antibiotics cannot bind to PBP2a, synthesis of the peptidoglycan layer and the cell wall continues. While the mechanism responsible for mecA transfer is still obscure, evidence supports horizontal transfer of the mecA gene between different staphylococcal species. Typically MRSA is diagnosed using culture based methods.

The Clinical and Laboratory Standards Institute (CLSI) recommends the cefoxitin disk diffusion test supplemented with the latex agglutination test for PBP2a. Phenotypic expression of resistance can vary depending on the growth conditions, as well as on the presence of subpopulations of staphylococci that may coexist (susceptible and resistant) within a culture making susceptibility testing by standard microbiological methods potentially problematic. In addition, culture takes time, usually 1 to 5 days. Faster techniques of MRSA screening by molecular methods, such as Polymerase Chain Reaction (PCR), have been developed to test for the mecA gene that confers resistance to methicillin, oxacillin, nafcillin, and dicloxacillin and other similar antibiotics. Such techniques, while faster, still take hours and are sent out to labs. In addition, commercially available molecular approaches (used for screening) are unable to detect mecA-variants of MRSA.

Raman spectroscopy is a reagentless, non-destructive, technique that can provide the unique spectral fingerprint of a chemical and/or molecule allowing for target identification without sample preparation. With this technique, a sample is irradiated with a specific wavelength of light whereby a small component, approximately 1 in 107photons, is in-elastically scattered (at wavelengths shifted from the incident radiation). The inelastic scattering of photons, due to molecular vibrations that change the molecule's polarizability, provide chemical and structural information uniquely characteristic of the targeted substance. Raman Spectroscopy can be extremely useful in fully characterizing a material's composition, and allows for relatively fast identification of unknown materials with the use of a Raman spectral database. In addition, since Raman Spectroscopy is a non-contact and non-destructive technique, it is well suited for in-situ, in-vitro and in-vivo analysis.

Raman Spectroscopy has high potential for screening of bacteria, virus, drugs, as well as tissue abnormalities since it: 1) is practical for a large number of molecular species; 2) can provide rapid identification; and 3) can be used for both qualitative and quantitative analysis. A portable or handheld micro Raman based detection instruments would be useful to reliably and rapidly assessStaphylococcus aureusstrains in wounds or nasal passages. Rapid assessment and typing would enable tracking the spread of such pathogens and could significantly decrease the number of hospital-acquired infections and the associated costs in treatment thereof.

SUMMARY

This section provides a general summary of the disclosure, and is not a comprehensive disclosure of its full scope or all of its features.

A hand-held Raman spectroscopy based device system for mucosal examination (nares, oral, ear) and wound interrogation provides a method for rapid and cost effective screening of bacteria, virus, drugs, and tissue abnormalities. The device is a nonintrusive automated near-real-time-point-of-care detection system that can enable healthcare providers to render better patient management and optimize clinical outcomes. The device includes a disposable tip element having dimensions that are small enough to fit into a small body cavity, such as the nostril. Three types of tip elements may be employed with this system—one for direct nasal interrogation, one with vacuum suction and filter, and one with proximity optics for wound interrogation. The tip element and the device enclose an assembly of optical components which allow for Raman spectral measurement that can provide the unique spectral fingerprint of a chemical and/or molecule allowing for target identification without sample preparation.

The device incorporates signal processing and identification algorithms for signal conditioning and target detection. Combinations of ultra-high resolution micro-filters in discrete regions (e.g., quadrants) of an area on the imaging detector array provide specific analysis of target spectral peaks. Each region or quadrant allows for discrete spectral band detection with each micro-filter providing specific wavenumber detection for spectral analysis. Discrete Raman spectral bands that distinguish a targeted substance from background interference are used to develop learning algorithms that serve as a basis for detection and target identification. By obtaining data at discrete spectral regions instead of over the entire spectral rage, acquisition time as well as spectral contributions from confounding background interference will be reduced or eliminated allowing for near-real-time assessment.

Methods for identification of pathogens in fluidic samples using Raman spectroscopy also form a part of the present disclosure. These methods show use a limited number of discrete spectra peaks to sample key molecular identifiers of a wide range of potential targets for specific pathogen detection. As a result, the apparatus and methods described herein can be customized for a host of target materials and implemented in a relatively small, portable form factor. In essence, an adapted system is provided, which can be readily modified to change target needs by means of a built-in learning algorithm. An exemplary learning algorithm was developed under a United States Department of Defense program for real-time pathogen detection in water as well as for real-time identification of cancer cells from tissue samples and may be adapted into a detection protocol. After pre-processing is complete, a Discriminant Function Analysis (DFA) is used to classify samples. DFA predicts membership in a group. The independent variables are the predictors and the dependent variables are the groups, based on an assumption of multivariate normality. This resulting data is used to modify the Raman-based spectral analysis executed in the hand held device.

Further areas of applicability will become apparent from the description provided herein. The description and specific examples in this summary are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.

