Source: https://patents.google.com/patent/JP2007524389A/en
Timestamp: 2020-03-28 22:24:43
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Matched Legal Cases: ['Application No. 60', 'Application No. 10', '§ 119', 'Application No. 09', 'Application No. 09', 'Application No. 09', 'Application No. 10', 'Application No. 10', 'Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60']

JP2007524389A - Wide-field method for detecting pathogenic microorganisms - Google Patents
Wide-field method for detecting pathogenic microorganisms Download PDF
JP2007524389A
JP2007524389A JP2006517613A JP2006517613A JP2007524389A JP 2007524389 A JP2007524389 A JP 2007524389A JP 2006517613 A JP2006517613 A JP 2006517613A JP 2006517613 A JP2006517613 A JP 2006517613A JP 2007524389 A JP2007524389 A JP 2007524389A
JP2006517613A
ウルフェ，ジュリアンヌ
ダブリュ．，ジュニア ガードナー，チャールズ
シー． シュバイツァー，ロバート
ジェイ． トレド，パトリック
ピー． ネルソン，マシュー
バンニ，ジー．スティーブン
エス． マイヤー，ジョン
ケムイメージ コーポレイション
2003-06-27 Priority to US10/608,470 priority Critical patent/US7057721B2/en
2004-06-24 Application filed by ケムイメージ コーポレイション filed Critical ケムイメージ コーポレイション
2004-06-24 Priority to PCT/US2004/020266 priority patent/WO2005060380A2/en
2007-08-30 Publication of JP2007524389A publication Critical patent/JP2007524389A/en
Pathogenic microorganisms are detected and classified in a wide field of view by digital pattern recognition of their spectral patterns along with Raman light dispersion from the pathogenic microorganisms.
The present invention relates to the fields of chemical analysis and biological analysis, and more specifically to the use of wide-field Raman and fluorescence spectroscopy to quickly identify biological agents and pathogens.
CROSS REFERENCE TO RELATED APPLICATIONS This application is based on US Provisional Application No. 60 / 347,806, filed January 10, 2002, and US Patent Application No. 10 / 339,807, filed January 10, 2003. Claim priority in accordance with 35 USC § 119 (e). This document is incorporated herein in its entirety, including objects.
Population of terrorists as chemical and / or infectious biological agents as weapons of mass destruction threatens the lives of the people. Social interest has increased, especially in the American population, as terrorists have become aware of the use of biological agents, such as anthrax. The nightmare image of tens of thousands of innocent victims who are infected and dying has shaken almost everyone. Bacterial wars and chemical wars are critical not only for the loss of life, but also for the loss of the US economy. The Centers for Disease Control estimates that the loss of 100,000 lives will have an economic impact of $ 29 billion. The mass destruction capabilities of bacterial warfare agents ("BWAs") and chemical warfare agents (CWAs) are considered by many to equal or even exceed the mass destruction capabilities of nuclear weapons. Nuclear weapons, although very broad, have the potential to affect a finite area, and the use of such weapons is immediately apparent after that fact. On the other hand, BWAs and CWAs are virtually borderless and have the potential to spread quietly and unchecked through residents far from ground zero. Similarly, techniques for the immediate detection and quantification of very low levels of radioactive contamination are widely used, but unfortunately such techniques for BWAs and CWAs at comparable levels are not reliable. And not widely available and often not quick.
The mental impact of this type of fear is also quite significant. The general public is increasingly aware of emerging pathogens. The fear of the unseen nature of BWAs and CWAs is in itself a very effective terrorist weapon. In addition to this perception, there is a real threat due to the incredible progress of biotechnology. At present, it is possible to remodel the most toxic bacteria or viruses and to increase both pathogenicity and resistance to conventional treatments. The revolution in molecular biology has been ongoing for over 30 years, resulting in an increase in the number of people with technical expertise to potentially create such weapons of mass destruction. In the era of developed world traffic, it is likely that any type of BWA will be quickly sprayed on a global scale in a fairly short period of time, and the general public is well aware of this fact.
Conventional methods of identifying pathogens using biological tools such as specific antibodies, genetic markers, or growth in culture are basically time consuming and require considerable manual manipulation. In addition, as new BWAs and CWAs are created, these conventional tools are likely to become less effective. As the use of BWAs and CWAs by terrorists has become a reality, there is an increasing need for methods that can detect and classify small quantities of such substances immediately and accurately without contacting them at the molecular level. There is a need for a method that is cost effective and easy to use so that this method can be widely deployed. There is also a need for methods that help to better understand the biological and chemical basis of such weapons agents and the potential impact on the human body. In addition, the knowledge gained through such molecular analysis helps to identify new targets for therapeutic and prophylactic drugs.
SUMMARY OF THE INVENTION A wide field observation and spectroscopic detection system, also described as a molecular spectroscopic identification system, for Raman, fluorescence, UV-visible reflection / absorption and / or near-infrared (BIRs for characterization of BWAs and CWAs ( A system using NIR) reflection / absorption spectroscopy techniques is disclosed.
Optical spectroscopy is a widely used approach for elemental, molecular, or chemical analysis ranging from compounds to organic molecules. Molecular analysis using vibrational spectroscopy makes it possible to measure the detailed structure and chemical properties of various substances. Such a method is ideal for uniform simple substances such as drugs, plastics, polymers and the like. Organic biological molecules are often much more complex materials. Microorganisms are remarkably complex, and even the smallest unit, one cell, is composed of intricate functional biological structures, each of which is made from a complex organic biopolymer that is unique to the structure. Microorganisms contain functional units such as nuclei, microfibers, protoplasts, pigments, mitochondria, endoplasmic reticulum, microvilli, lysosomes, central bodies, Golgi bodies, and various protective layers. These complex structures and structural / chemical variations create biodiversity that complicates optical analysis.
Current analytical optical measurements of materials typically fall into one of two categories. In one category, a group of pure substances can be used as macrosamples, i.e. to measure in a large sample volume, and the second category is a microvolume analysis technique for analyzing a small amount of object. Is used. In conventional situations, macroscopic sampling does not have the sensitivity to detect low concentrations of pathogens and does not have a particularly important need for assessing BWAs and CWAs. On the other hand, microvolume analysis methods allow to focus on individual micro objects by using highly focused excitation beams. Such focused beam optical methods are effective for inorganic and organic particles, but not for microorganisms due to their biodiversity and high sensitivity to irradiation. There are two forms of biodiversity. One form results from variations in signals from different locations in the microorganism. That is, the sampling probe is smaller than the organism. In another form, it results from small changes between organisms of the same type. Furthermore, biological microorganisms can be degraded or “burned” under the high power density of the highly focused illumination beam. This requires reducing the optical radiation to the microorganisms so as not to destroy the organism, and thereby collecting the optical radiation for a long time to compensate for the reduced emission intensity. In order to reduce the effects of biodiversity, it is also necessary to sample many small objects. Thus, the use of optical microanalysis to sample many organisms continuously is thereby time consuming. Our approach removes these limitations by averaging the optical emissions from a few pathogenic microorganisms using wide-field and wide-field optical excitation. The sensitivity obtained makes it possible to detect and reliably identify a few microorganisms even in the presence of a matrix of external substances, so-called “masking agents”.
Infrared, Raman, visible light reflection, fluorescence, and near-infrared optical spectroscopy have been applied with limited success for the detection of microorganisms. Infrared and Raman spectroscopy can provide fingerprint information for a significant number of spectra. On the other hand, fluorescence can be used if specific fluorescence characteristics occur. Many materials have a broad fluorescence background under visible radiation complicates the application of optical dispersion techniques. Such fluorescence creates a significant spectral background that obscure the spectral pattern of other objects in the field of view being analyzed. The background typically varies along the support, particularly when working with actual samples containing a variety of components or mixture of components. We have found that the fluorescence background dependent on these spaces can be significantly reduced by irradiating the optical probe beam to an area slightly larger than the sampling area. This reduction is called photo bleaching. With the use of a wide field of view, photobleaching to areas containing a small number of microorganisms allows the present invention to be routinely and accurately applied to detect such microorganisms.
Removing the interfering fluorescent signal is different from other methods that add fluorescence help. Fluorescent ligands designed to bind to specific biomolecules that are characteristic of these organisms can be introduced. Such ligands usually include several bioactive agents, such as bioactive agents that recognize and bind to specific biomolecular structures, such as antibodies. Here, the fluorescent ligand acts as a marker, label or tag for these organisms or parts of the organisms. While such external fluorescent markers / tags can provide contrast and aid optical detection of specific biological features, organisms, or biomaterials, they are expensive, time consuming, and further manipulations to the detection process It is necessary to use a reagent that is a problem of consumability.
Optical methods such as Raman and infrared also have a much weaker signal from biopolymers compared to the signal from pure drugs, and thus have some benefit from signal amplification to detect low concentrations . The method can include multiple reflections from the sample to amplify the resulting signal in the infrared. However, the method requires specialized sample size or sampling arrangement, which will limit application or increase the cost of the sampling device. In Raman spectroscopy, the signal can be increased by using a special support. The support increases the 3-7 digit Raman signal. However, not all molecules bind to the SERS active surface, which limits the application of such an approach. Our invention does not require a special support and improves the signal-to-noise ratio by using a wide field of view.
Resonance Raman has been used in biological systems by exciting biomolecules or organisms using high energy optical radiation (wavelengths less than about 400 nm) to increase the Raman signal. While the Raman signal is increased at resonance conditions, the higher excitation energy excites the electronic state of the biomolecule, thereby resulting in greater laser power absorption and heating the sample, which degrades or damages microorganisms. sell. Furthermore, the optical components and UV detectors required to support UV illumination and detection are also more expensive and specialized than commonly used visible light optical components.
The present invention is a wide-field optical spectroscopy for the detection of pathogenic microorganisms, avoiding many of the disadvantages and limitations of many possible optical spectrometers that can be applied to detect low concentrations of microorganisms. Teaching how to use Our wide-field molecular spectroscopy is based on several approaches to enable fairly reliable measurements that were not anticipated or recognized by the prior art, despite the wide body of Raman spectroscopy being performed today. Reducing artifacts and specific sampling problems. Our method utilizes optical spectroscopy systems, our wide field emission approach, and digital spectral pattern recognition systems to recognize pathogenic microorganisms. Unlike conventional methods, the methods provide high sensitivity and provide identification of pathogenic microorganisms that are reliable and practical.
An important element of the present invention is that in addition to using a wide field of view to radiate and emit a control region of the target support, the optical emission from the same region of the wide field is collected and analyzed. There is. We define a wide field of view as the area that is equal to or larger than the microorganism in this study. Our invention uses several methods to solve some fatal problems that arise with conventional optical methods used to identify microorganisms.
The most widely used Raman method for studying biological systems with a microscope utilizes micro-Raman spectroscopy. Here, the already focused laser's closely focused beam results in an illumination spot that is about 1 micron or less in size, maximizing the Raman signal intensity on the target of interest. Such a closely focused beam can destroy microorganisms while attempting to measure them. The reduction in the power of the irradiation beam requires a long data acquisition time. In addition, the use of such a small spot size can lead to non-reproducible signals given the biodiversity of the microorganism, since the signal is distributed to various locations in the specimen being analyzed. In addition, the fluorescent background signal typically varies with time and in different regions of the sample and further interferes with the detection of pathogenic microorganisms.
The present invention considers previously overlooked methodologies for targeting, irradiating and detecting microorganisms, thereby representing a novel approach for microorganism detection. Targeting may be some suspicious characteristic that is characteristic of the pathogen masking substance or various characteristics of the pathogen itself, such as shape, size, or color of the spore, various characteristics of the powder, aggregate or mass, and within the subject This is done by finding a region of the support that has fluorescent features and the like. This can be done via manual inspection or using automated image recognition technology from an optical viewing device. Once targeting was complete, a smaller region was chosen to increase the magnification and to collect a large solid angle of optical emission resulting from Raman or fluorescence excitation within the target region. When observing with an optical observation means, the region observes a wide field of view rather than observing a single microscope object. The spectroscopic excitation source then illuminated a wide field peripheral region at a sufficiently high output, allowing the region to photobleach and obtain a stable optical spectrum. A small overflow will acquire data in the immediate adjacent area within the next irradiated area, as well as eliminating spectral changes associated with small shifts or variations in sample position during the acquisition of the spectrum. There are advantages in terms. An illumination approach that uses a wide range of illumination over a region that is substantially larger than a wide field of view does not provide sufficient output for proper photobleaching. Acquisition of Raman scattered light is performed over a wide field to fully collect and average spectra from a small number of microorganisms, which are then analyzed for spectral characteristics of the pathogenic microorganisms. The wide field sampling approach offers several decisive advantages over the point or line focused excitation source used for Raman spectroscopy. Unlike other optical microanalysis methods, we utilize a non-confocal infinity corrected optical system and observe a wide field target area with an objective lens that provides a high numerical aperture To do. In contrast to other methods of focusing the output on the subject of study, we blur the optical beam over the wide field of view used. The method generally enables the following improvements over currently used spectroscopic methods.
1. Photobleaching of sufficient area of the sample under investigation reduces the overall fluorescence background signal, increases the signal-to-noise ratio, and reduces the signal-to-noise ratio typically encountered with conventional microanalyzers Avoid local fluorescence fluctuations.
2. Wide field illumination reduces biosignal diversity, improves thermal management, increases signal levels and reproducibility.
3. Wide field luminescence improves the signal-to-noise ratio of the target pathogenic microorganism.
4). The ability to manually or automatically visualize and select a region of the support based on an objective measure of the specimen or target microorganism, such as the inherent size of the organism pair, increases the signal to noise ratio.
5). The use of a similar wide field of view for illumination, illumination, and emission ensures that a well-defined and appropriate area based on the support is selected for analysis.
6). The configuration and approach used allows low-cost compact spectrometers, for example, spectrometers with simple chromatic dispersion elements with sufficient resolution to detect the spectral elements emitted from the sample being investigated. The effective use of such scalable optical elements in a wide field of view allows such inspection systems to be scaled down to smaller sizes and hence a portable handheld unit. To do.
7). Various supports can be used for the microorganisms for analysis, thereby increasing the flexibility of the method. Many materials from which materials can be produced, such as paper, can be used as a support.
Extensive illumination and detection requires several simple sample preparations. Sample preparation involves collecting the sample and placing the sample in a thin uniform layer. Selecting a target area for such a specimen requires creating the correct image profile, eg, size and shape. The target density determines the field of view used and the required illumination intensity. Both of these are based on calibration data obtained or calculated in advance. Such calibration curves are easily created by those skilled in the art.
In one embodiment, Raman and / or fluorescence microspectroscopy can be used to detect, classify, and / or identify BWAs, CWAs, and non-threat compounds. These microdispersion spectroscopy methods detect, classify, and identify substances that contain a single bacterium. Appropriate digital analysis of the resulting Raman spectra can resolve target microbial signals from BWAs and CWAs in the presence of non-threat “masking” compounds.
In another embodiment, fluorescence and Raman macrospectroscopy can be used to detect, classify, and / or identify BWAs, CWAs, and non-threat compounds. These macrospectroscopy techniques can detect, classify, and identify (ie, detect and identify aggregated bacteria and endospores) sub-millimeter size particles of BWAs and CWAs. In addition, fluorescence and Raman macrospectroscopy can detect, classify, and identify BWAs and CWAs in the presence of non-threatening “masking” compounds when appropriate data analysis techniques are applied.
In another embodiment, Raman optical fiber based spectroscopy can detect, classify, and / or identify BWAs, CWAs, and threat-free compounds when appropriate data analysis techniques are applied.
These different embodiments can utilize a computer analysis method that compares all observed optical spectra with known optical spectra obtained under similar conditions to identify microorganisms.
The above systems and methodologies are applied in various modes. The system is applied as a laboratory or transportable outdoor Raman spectrometer integrating a dispersive Raman spectrometer and a digital data analysis module. The system is also applied as a UV / Vis / NIR fluorescence, Raman, or UV / Vis / NIR / Mid-IR absorption / reflection macroscope system, such as ChemImage's CONDOR macroscope. Instead, the system is applied as a laboratory or field fiberscope, eg, ChemImage's RAVEN endoscope. Either application mode can be used separately or combined with each other to achieve the desired speed and result. In addition, high area detection method tools can be scaled down to the size of the large area being investigated, thereby allowing the required hardware to be miniaturized, for local sampling and / or remote analysis. Enables portable devices with potential.
Spectroscopic techniques are applied to sensors designed to detect, classify and identify BWAs, CWAs, and non-threat compounds at room temperature. A schematic diagram of such a sensor is shown in FIG. The vacuum created by the air sampling pump pulled room temperature air through the filter along the sample inlet. The filter material comprises porous polypropylene or cellulose in the form of a disc or roll. Fine particles in the air are trapped on the surface of the filter media and kept in the field of view of the spectroscopic imaging system. The source specifically chosen for the type of molecular spectroscopy used irradiates a large area of the trapped particles and induces Raman or fluorescence emission from the sample. The emission is collected and refocused on the detector, which measures the emitted light at a continuous wavelength and creates a data file that is used for further analysis. The inlet to the detector can be an imaging optical fiber or can be a conventional optical material. BWAs, CWAs, and non-threat compounds were detected, classified, and / or identified using modified chemometric techniques along with known spectral databases.
The system can be automated through the use of robotic or BWAs, CWAs, and mixed macro / micro devices to target threat-free drugs. Laser ablation and / or chemical ablation are used to automate the system and irradiate the targeted BWAs and CWAs.
Various data processing methods can be used in the system. A weighted spectral data subtraction routine can be used to reduce contributions from the support or microscope slide. Alternatively, multiple image analyzes related to principal factor analysis and subsequent factor rotation can be used for pure molecular feature differences in BWAs, CWAs, and threat-free “masking” compounds.
Raman chemical imaging and spectroscopy are well covered by the following US patents and US applications assigned to the assignee of the present invention: US Pat. No. 6,002,476; US filed Jul. 19, 2000 Application No. 09 / 619,371, US Application No. 09 / 800,953 filed March 7, 2001, US Application No. 09 / 976,391 filed October 12, 2001; June 2002 U.S. Application No. 10 / 185,090 filed on 28th; U.S. Application No. 10 / 184,580 filed on Jun. 28, 2002; U.S. Provisional Application No. 60 / filed on Jul. 19, 1999 No. 144,518; US provisional application 60 / 347,806 filed January 10, 2002; US provisional application 60 / 187,560 filed March 7, 2000; filed October 13, 2000 US Provisional Patent Application No. 60 / 239,969; US filed June 28, 2001 Provisional Application No. 60 / 301,708; US Provisional Application No. 60 / 422,604, filed October 31, 2002.
The patents and patent applications identified above are hereby incorporated by reference, including references.
Spectroscopy is the study of the interaction between light and matter. When excited by an external energy source, the light is caused by the substance to have a characteristic wavelength (i.e. color) in the electromagnetic spectrum (including γ-rays, X-rays, ultraviolet (UV), visible light, infrared, electromagnetic waves, and radio frequencies). Absorbed, reflected, transmitted, emitted or dispersed. These characteristic wavelengths can lead to the identification of the elemental and / or molecular composition of the substance. Experiments typically consist of a light source, light-dispersing elements (ie prisms, gratings) to create a spectrum and detector.
In Raman spectroscopy, the photons of interest are scattered by the material. If the incident light is monochromatic light (single wavelength), as is the case when using a laser source, then a small fraction of the dispersed radiation is the frequency of the laser (wavelength). It is different. Furthermore, the frequency of the dispersed light is specific to the molecular species present. This phenomenon is known as the Raman effect.
In Raman spectroscopy, the energy level of a molecule is probed by monitoring the change in frequency present in the dispersed light. A typical experiment consists of a monochromatic light source (usually a laser) that is directed at the sample. Several phenomena then occur including Raman scattering, which is monitored using a spectrometer and a charge coupled device (CCD) detector.
Similar to the infrared spectrum, the Raman spectrum reveals the molecular composition of the material, eg specific functional groups present in organic and inorganic molecules. Raman is useful because it exhibits a characteristic “fingerprint” spectrum according to various sorting rules. Adhering to peak shape, peak position, and selection rules can be used to measure molecular conformational information (crystal phase, order, strain, particle size, etc.). Unlike infrared spectroscopy, a single Raman spectrometer can be applied simultaneously to organic and inorganic molecular characterization. Other advantages of Raman over conventional infrared spectroscopy include the ability to analyze water phase materials and the ability to analyze materials with little or no sample preparation. Inhibitors of the use of Raman spectroscopy as opposed to infrared spectroscopy include the relatively weak nature of the Raman phenomenon and interference caused by fluorescence. In the past decades, many important techniques have been widely used that have enabled scientists to overcome the problems associated with Raman spectroscopy. These techniques include high sensitivity solid state lasers, laser blocking filters, and silicon CCD detectors.
In fluorescence spectroscopy, photons are emitted from a substance following an excitation step in which photon absorption occurs. Experiments typically involve a multicolor excitation source such as a mercury (Hg) or xenon (Xe) lamp or a monochromatic source such as a laser for sample excitation. A portion of the emitted radiation is then directed into a dispersive monochromator that is fitted with a detection device such as a CCD. By measuring the fluorescence spectrum from the substance, qualitative and quantitative information from inorganic and organic chemical species can be estimated. Compared to Raman spectroscopy, fluorescence is more sensitive than originally. A detection limit of one billionth is common. On the other hand, fluorescence is less selective than Raman, and not all chemical systems show fluorescence.
Molecular UV / visible light and NIR absorption spectroscopy are UV / visible light (185-780 nm (54,054-12,800 cm −1 )) and NIR (780 nm - 2.5 μM (12,800-4000 cm −1 )). Includes absorption of photons through each of the spectral regions. Typical devices include detection devices such as deuterium or quartz tungsten halogen lamps, dispersive elements such as monochromatic spectrometers or interferometers, and SiCCD or InGaAs focal plane array detectors. Absorption measurements based on UV visible or NIR radiation find numerous applications for qualitative and quantitative detection of inorganic and organic species. The NIR spectrum is obtained from the band combination and overlap of the base mid-infrared band. Like fluorescence, the absorption spectrum is quite sensitive, but the selectivity is only moderate.
Raman spectroscopy is a versatile technique and would be well suited for the analysis of simple and complex dissimilar materials. Applications of spectroscopic analysis range from analysis of polymer blends to analysis of defect states in semiconductor materials, inclusions in human breast tissue, characterization of corrosion samples, and detection, classification, and identification of BWAs and CWAs. Wide-field Raman spectroscopy combined with digital spectral analysis is qualitative and quantitative about molecular composition quickly, at low cost, and faster than other spectroscopy and imaging or “wet” chemical methods Provide information.
Wide-field Raman spectroscopy and digital spectrum processing combine Raman, fluorescence, UV / visible absorption / reflection, and NIR absorption / reflection spectroscopy, respectively, with digital processing for molecule-specific analysis of substances. is there. This special technique makes it possible to record the spectrum of the sample at discrete wavelengths (energy). Spectra were generated from all points on the sample surface by adjusting the Raman spectrometer over a range of wavelengths and intermittently collecting the signal intermittently. Depending on the material and the selected spectroscopic method, depth-related information can be obtained by using different excitation wavelengths or by obtaining spectroscopic information at the focal plane. Contrast within the material is created under study based on the relative amount of Raman scattering, fluorescence emission, UV / visible absorption / reflection, or NIR absorption / reflection created by different species placed through the sample. Quantitative chemistry using digital analysis methods such as correlation analysis, principal component analysis (PCA), and factor axis rotation, such as multivariate curve resolution (MCR), as spectra are generated from several constituent materials at once Analyzes etc. are applied to the spectral data, and otherwise, additional information that would otherwise be lost by normal univariate analysis is extracted.
Instantaneous Bacillus anthracis detection system based on wide-field Raman spectrometer There are many peripheral configurations based on wide-field Raman spectroscopy that meet the requirements of the main equipment described above as necessary for an effective instantaneous anthrax detection system Exists. These configurations include platforms based on microscopes, macroscopes, endoscopes, air sampler designs, or handheld designs. Each of them is briefly described below.
Microscope-based system The wide-field microspectroscopy system included a solid-state laser for sample excitation (Raman and laser-induced fluorescence only), the base of an optical reflection microscope, in one platform. The base here comprises an infinite correction microscope objective, an automated XYZ translational microscope stage, and a quartz tungsten halogen (QTH) lamp and / or a mercury (Hg) lamp. Also part of the microscope system is an analog color charge coupled device (CCD) detector for normal optical image acquisition, and a spectrometer dielectric or other bandpass filter, and for spectral acquisition This is an optical monochromator equipped with a CCD detector. Such monochromatic spectrometers are sold in many types including adjustable filters, line or spot focused dispersive elements, or Fourier transform spectrometers. Includes room temperature or optionally cooled IR FPA for IR image capture or thermoelectrically cooled (TE) Si CCD detector for UV / visible, and fluorescence spectrum capture. Remote, UV, visible or NIR illumination is directed to the sample in a reflective configuration using a QTH source or other broad white light source such as a metal halide, Hg arc lamp or Xe arc lamp, or QTH or optical reflection A suitable source of the microscope platform is used to direct the sample in the transmitted light configuration. In Raman or laser induced fluorescence experiments, laser radiation is directed to the sample through the use of a Raman illuminator. Light dispersion, emission, reflection, or transmission is collected from a sample placed on an automated XYZ translational microscope stage through an infinite correlation microscope object. In each illumination scheme, wide field illumination is chosen to optimize the quality and reliability and integrity of the original sample in the study.
Normal optical imaging of luminescence uses a mirror or beam splitter or prism arrangement inserted in the turret wheel of the microscope and is imaged with an analog or digital color or monochromatic charge coupled device (CCD) or CMOS detector. Can be obtained. The entire spectrum is acquired over a wide field of view / area collected, or magnified spectroscopy images are combined through image spectroscopy and NIR or mid-infrared focusing surface array (FPA) detector (IR spectroscopy imaging ) Or Si CCD detector (for UV / visible absorption / reflection, fluorescence and Raman spectroscopic imaging). IR FPA is typically composed of indium gallium arsenide (InGaAs), but other IR sensitive materials such as platinum silicide (PtSi), indium arsenide (InSb) or mercury cadmium telluride (HgCdTe) It can consist of.
A central processing unit, typically a Pentium® computer, is used to collect and process spectral intensity versus wavelength. Analog color CCD, IR FPA, and / or SiCCD, automated XYZ translational microscope stage controlled via controller, and liquid crystal or other imaging spectrometer (through appropriate imaging spectroscopy controller) are commercially available Software, eg, ChemAcquire (ChemImage Corporation) in combination with ChemAnalyze (ChemImage Corporation).
The following types of spectrometers can also be utilized: fixed filter spectrometers; grating-based spectrometers; Fourier transform spectrometers; or acousto-optic spectrometers. Polarity independent interferometers such as: Michelson interferometer; Sagnac interferometer; Twynam-Green interferometer; Mach-Zehnder interferometer can be used as a filter. A spectrometer design that allows optical expansion to smaller sizes allows for a more portable and deployable device.
Wide-field spectroscopy is used for depth measurement, through the method of moving the sample through focusing in the Z-axis direction, collecting data inside and outside the focal plane, and the volume profile of the sample within the software Can be reconfigured. For samples with some volume (bulk material, surface, interface, interface), volumetric spectroscopic imaging has been shown to be useful for failure analysis, product development, and commonly performed property monitoring. There is also the possibility of performing quantitative analysis simultaneously with depth analysis. Volumetric imaging can be performed in a non-contact mode through the use of numerical aperture confocal technology without modifying the sample. The confocal technique allows samples to be measured at discontinuous focal planes. The resulting spectral profile is processed, reconstructed, and visualized. Computerized optical cutting reconstruction techniques based on various strategies are performed, including, for example, nearest neighbors and repetitive shapes.
Microscopic wide-field optical spectroscopy systems have the distinct advantage of being able to detect, classify, identify and visualize, for example, BWAs down to a single cell. These systems boast a spectral resolution of 8 cm −1 and a spatial depth of about 200 nm in a numerical aperture shape method.
Macroscope-based systems Wide-field macro-spectroscopy systems include an illumination source (typically a QTH, Xe, Hg, or other metal halide lamp), a barrier optical filter (s) in a single platform. ) And a light orientation module (ie, direct light bundle, optical fiber, or liquid light guide irradiation). Analog color charge coupled device (CCD) detectors are used for conventional optical and digital image acquisition. Raman wavelength selection is performed using an imaging or non-imaging spectrometer. The detector is either a room temperature or optionally cooled NIR FPA for NIR image capture, or a thermoelectrically cooled (TE) SiCCD detector for UV / visible and fluorescent image capture.
UV, visible or NIR irradiation is directed to the sample in the reflected light arrangement using a QTH source or other broad white light source such as a metal halide, Hg arc lamp, or Xe arc lamp, or QTH, or Direct illumination, optical fiber, or other suitable source through a liquid light guide is used to direct the sample in the transmitted light arrangement. Radiated, reflected, or transmitted light is collected through a macro lens from a sample located on the macroscopic sample base.
Normal optical images of samples are imaged using mirrors, beam splitters or prisms inserted into the acquisition stack of the macroscope, and with analog or digital color or monochromatic charge-coupled devices (CCD) or CMOS detectors Can be obtained. In the Raman spectroscopic mode, spectroscopic information is obtained via an imaging or non-imaging spectrometer. Focal plane array (FPA) detectors (for NIR spectroscopic imaging) or Si CCD detectors (for UV / visible absorption / reflection, fluorescence and Raman spectroscopic imaging) can be used to complement this. NIR / FPA is typically indium gallium arsenide (InGaAs), but other NIR sensitive materials such as platinum silicide (PtSi), indium arsenide (InS® b), or telluride It can be composed of mercury cadmium.
A central processing unit, typically a Pentium® computer, is used for spectral data collection and processing. Analog color CCDs, NIR FPA and / or SiCCDs and liquid crystal imaging spectrometers, or other imaging spectrometers (through a suitable imaging spectrometer controller) are available from commercially available software such as ChemAcquire (ChemImage Corporation). Operated in combination with (ChemImage Corporation).
The use of a macroscope-based system has the advantage of allowing immediate detection of potential BWAs and CWAs over a larger area. Previous work has shown the ability to image 0.01 mm defects on 200 mm semiconductor wafers using a macroscope system.
Endoscope-based system Raman spectroscopy is widely practiced in laboratory facilities that primarily use research-quality light microscopy techniques as image acquisition platforms. However, Raman spectroscopy is also applied to in situ industrial process monitoring and in vivo clinical analysis. Both industrial and clinical facilities require compact and lightweight equipment suitable for remote field testing that often cannot be accommodated by conventional spectroscopy equipment.
A fairly wide field of view spectroscopy system with digital analysis capabilities has been developed. An imaging endoscope system coupled to the spectroscopy system provides spectral analysis for real-time video inspection capabilities. The endscope is connected to a video CCD for real-time video imaging in the analysis area. This allows for rapid visual screening of the sample. Endoscope tips are made to filter both laser irradiation and collected Raman scattering and fluorescence emission (Raman and fluorescence applications). The light from the laser delivery fiber is filtered so that Raman laser information can be visualized within 200 cm -1 of the laser line. The distal end of the Raman endoscope is resistant to the surrounding environment, resistant to continuous operation at high temperatures, and maintains high signal-to-background (S / B) performance while maintaining zero It was shown to operate at ~ 315 ° C. The distal end is connected to a microscope-based system that allows remote operation of dispersion spectroscopy and spectral imaging.
The use of an endoscope-based wide-field Raman spectroscopy system has the advantage of being able to detect the presence of suspected BWAs and CWAs at a remote location, such as in a box or envelope.
Room temperature air sensor system The room temperature air sensor system consists of two parts, a sampling system and a spectroscopic imaging system. The key to the sampling system is the optical block schematically shown in FIG. The block must support a portion of the filter media and provide a complete hermetic seal around the sample area. The block must be easy to open and thus be able to place a new filter (discontinuous filter) or a new part of the filter (continuous filter) in the sampling / optical path.
The sampling system has an inlet that is open to the air to be tested. Its dimensions are optimized for the expected range of sampling flow rates and particle sizes. For particulate or aerosol sampling, it is important that the inlet must not have a sharp curve or low linear velocity region that can cause particle deposition prior to the collection filter. The sampling system also has a sampling pump and provides suction to draw room temperature air through the filter. The expected flow rate is in the range of 0.5-2.0 L / min, and the expected suction is in the range of 100 in.-H 2 O (180 mm-Hg).
Sampling systems are typically not run continuously, but rather with a series of discrete sampling periods. At the end of each period, it is necessary to replace the filter media. This can be done by the operator or automatically. With continuous sampling, the filter media is a tape-like configuration and new filter samples can be placed in the optical block by a tape drive mechanism similar to the drive of an audio cassette.
Once the microparticles were trapped in the filter media, wide field spectroscopy was used to detect and classify the presence of BWA or CWA. Raman imaging can be used if the excitation source is a laser that is coupled to the optical block using conventional or optical fibers and the light is equally applied to the entire sampling region. In another configuration, a light source comprised of a broad UV / Vis, filtered UV / Vis, or UV / Vis laser can be used to excite autofluorescence. The imaging detector is a liquid crystal ready type, or another imaging and spectroscopy type as described above, and a CCD or other camera array to image the sampling area at multiple wavelengths. Can be used. Coupling the detector to the optical block can be based on optical fibers or through conventional optical techniques. The detector data was processed using chemometric and image analysis tools such as those found in ChemAnalyze software (ChemImage Corporation).
A typical operation mode of this type of room temperature air monitor is usually performed as a series of sampling periods, during which a spectroscopic image measurement for a certain period is performed. Results from previous and current sampling periods are interpreted by the system computer, which shows the results and can trigger warnings and danger alarms, or the building turns off external air intake, etc. Several actions can be initiated.
Hand-held biological threat detectors The current spectroscopic based biological threat detection system is designed to produce and focus the irradiation, collect radiation or scattered light, and perform the individual spectral analysis required. Depending on the component, it is limited in size and weight. One advantage of the wide-field method of pathogenic microorganism detection is simplicity, which allows the design, layout, and integration of excitation and detection systems.
The functional and structural requirements of the method will allow each embedded component to be miniaturized without significant performance degradation or limitation. For example, a low-cost, compact spectrometer consisting of a wavelength tunable filter or MOEMS fabricated wavelength dispersive elements with sufficient resolution to detect the spectral elements emitted from the specimen being examined. Can be designed and assembled. Advances in active pixel CMOS CCD detectors or avalanche photodiodes allow small compact sensors to detect and spatially resolve the resulting spectrum. The effective use of such measurable metrology optics in the wide field method makes it suitable for scaling down the overall size and weight of such a detection system, thereby creating a portable handheld unit. Made possible.
Results Spectra created using conventional spectroscopy methods can potentially reveal a great deal of information about the molecular properties of BWAs and CWAs. The wide field spectroscopy presented herein makes this practical and reliable, and also allows for the detection of single bacteria if necessary. This also makes it possible to characterize bacterial spores in the presence of non-threatening “masking” agents and represents a significant problem in the detection and identification of BWAs and CWAs. Difficulties remain in distinguishing spores from different bacterial species. FIG. 2 shows dispersed wide-field Raman spectra of three different bacterial spore types. Despite genetic and morphological similarities, wide-field Raman spectroscopy was used to distinguish well among different bacterial spores.
FIG. 3 shows how wide-field fluorescence spectroscopy images obtained through imaging spectroscopy can be used to distinguish bacterial spore types. The fluorescence spectrum at the bottom of the figure was obtained from the color-code box region linked to the fluorescence fluorescence spectroscopy image. This shows that Bacillus subtilis spores and Bacillus pumilus spores show maximum fluorescence peaks at 540 nm and 630 nm, respectively.
FIG. 4 is the result of a rapid wide-field spectroscopic test of an unknown sample provided by the American Military Pathology Institute (AFIP). These samples include 4 samples containing 6 unknown powders and BG spore samples.
FIG. 4A shows a wide field Raman spectrum (green laser excitation) of 6 unknown powders through a vial.
FIG. 4B shows wide field Raman spectra (red laser excitation) of 6 unknown powders.
4C-4D (Samples 1331-002) show the results of the first wide-field Raman, IR, and SEM-EDS of 6 unknown powders. The sample is an inorganic substance and looks like talc.
4E-4F (samples 1325-002) show the results of the second wide-field Raman, IR, and SEM-EDS of the 6 unknown sample ends. The sample is organic and looks like starch, probably corn starch.
4G-4H (Samples 1303-002) show the results of the third wide-field Raman, IR, and SEM-EDS of 6 unknown powders. The sample is organic, looks like starch, and is probably corn starch.
4I-4N (Samples 1291-006) show the results of wide field Raman, IR, and SEM-EDS of the remaining unknown powder. There are three different types of powder in this sample. All three are organic contents and two of the three are quite rich in aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex.
FIG. 4O shows wide-field Raman spectra and images of two regular white powders that are readily distinguished by Raman chemical imaging.
FIG. 4P shows a wide field Raman spectrum of sample BG spores compared to commercial BG spores. The Raman spectrum of a mixture of two samples is shown as well. Raman indicates that the samples are similar and nearly identical.
FIG. 4Q shows a wide-field Raman image in which two similar spores are distinguished based on the difference in autofluorescence.
FIG. 5 shows the results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The wide field Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. Details are as follows.
FIG. 5A shows raw data of wide field Raman spectra of BT and suspension residues. The residue is obtained from the suspension.
FIG. 5B shows a wide field spectrum of BT and residue corrected for background. Both the spore spectrum and the residue spectrum were divided by the spectrum of the microscope slide.
FIG. 5C shows raw data for Raman spectra of BC and suspension residues.
FIG. 5D shows the background corrected BC and residue Raman spectra.
FIG. 5E shows microscope slide background corrected sample BT, BC, and BG dispersion spectral overlay. These spectra were different. This difference is greatest in the fingerprint area.
FIG. 5F shows the superposition of 3 spores after subtracting the baseline and normalizing to the CH region spectral feature (˜2950 cm −1 ).
FIG. 6 shows how wide-field Raman spectroscopy can be applied to distinguish between multiple bacterial strains within a single species.
FIG. 7 shows how wide-field Raman spectroscopy is applied to distinguish between the same species and strains of bacteria growing under different conditions.
FIG. 8 shows wide field Raman spectroscopy of various regions of interest in Bacillus anthracis spores and the ability to distinguish reproducibly between similar materials.
FIG. 9 shows how the wide-field Raman spectroscopy can be applied to distinguish between live and non-live endospores in measuring actual threat levels. Whether it can be applied to distinguish common variables.
FIG. 10 shows the wide-field fluorescence and Raman signal-to-noise ratio as a function of the existing spores and the overall sensitivity of the method.
FIG. 11 shows the ROC analysis of the wide field Raman spectroscopy results, showing the specificity of the method to distinguish anthrax from other analogues.
12 shows handheld pathogen microbial detection measuring approximately 6 ″ × 3 ″ × 1 ″ and is based on a wide-field Raman method, where the particular unit is a stacked or modular functional layer comprising a display and It consists of a top layer containing the user interface, an illuminator, spectrometer, sensor, and an intermediate layer surrounding the control electronics, and a lower layer with a sampling module, each layer tailored to specific needs or functional needs. For example, the sampling module is different for sampling pathogens in different environments and is shown for room temperature air monitoring or surface detection mode.The lower layer sampling module can be a variety of liquids such as water or blood. To sample the pathogens in Can be exchanged for others.
Anthrax spores were used for wide-field Raman in the Biohazard Laboratory. Different anthrax spore species were distinguished by the wide-field Raman method (FIG. 6). In addition, wide field Raman spectroscopy was used to distinguish the same species and strains grown under different environmental conditions and / or growth media (FIG. 7). The capability can have normal useful research applications. Wide field Raman spectroscopy was then used to distinguish viable endospores from viable endospores (FIG. 9). The viability of suspected spores is a critical variable in measuring the actual threat in question.
The inventor would expect that with the wide-field Raman method and the resulting spectral profile, the following pathogenic microorganisms have room to be detected and classified for species, strains, and viability: Cryptospo Lysia; Escherichia coli; plague (Yersinia pestis); smallpox (variola major); tularemia (Francisella tularensis); brucellosis (Brucella species ( Brucella)); Clostridium perfringens; nasal polyp (Burkholderia mallei); snout (Burkholderia pseudomallei); parrot (Chlamydia psittaci) Q fever (Coxiella burnetii); Typhoid fever (Rickettsia prow azekii)); Vibrio; Giardia; Candida albicans; Enterococcus faecalis; Staphylococcus epidermidis; Staphyococer enterus aerogenes); Corynebacterium diphtheriae; Pseudomonas aeruginosa; Acinetobacter calcoaceticus (Klebsiella pneumerovirus); (E.g. Ebola virus and Marburg virus), viruses (e.g. Lassa fever and Macpovirus), and alphaviruses (e.g. Venezuelan equine encephalitis, Eastern equine encephalitis, and Western horse brain).
Advanced spectral analysis and chemical metrology tools take these differences as differences in Raman or fluorescence spectra and identify species as in FIG. A similar approach can be applied to create an image by taking spectra obtained sequentially from at least two different regions of the surface of the substrate under investigation. The following are typical algorithms for performing such analyses.
1) Divide original image by background image (obtained without sample) 2) cosmic filtering on the resulting image (median filtering for pixels whose values differ significantly from the mean of the neighborhood) 3) Use an alignment method to compensate for small sample movements during data collection 4) Apply spatial averaging filter 5) Spectral normalization (for variable radiation passing through the sample) (Helps to correct)
6) Spectral running average for each set of 3 spectral points 7) Extract the set of frames corresponding to 550 to 620 nm. The spectra for both bacterial spores (Bacillus subtilis var niger and Bacillus pumilus) are substantially linear over this range. Bacillus subtilis bar niger has a positive slope, and Bacillus pumilus has a negative slope.
8) Create a single frame image where each intensity value is the slope of the spectral sub-region (from the last image). The slope is measured through the application of the least squares method.
9) Scale the resulting image from 0 to 4095. Keep track of points 0-4095 corresponding to 0 (zero point) in the previous image.
10) Create a mask image from the following sequential steps:
a) Calculate from the arrayed image (third step) a single frame “brightest” image where the intensity of each pixel is the maximum intensity value for each spectrum b) the brightest image 0-4095 C) create a binarized image from the measured image, where all pixels whose intensity exceeds 900 in the new image are set to 1 in the new image, and Set all pixels with an intensity less than 900 to zero.
A value of 900 was chosen by examination of the histogram associated with the measured image. A further improvement to the algorithm is to automatically choose by numerically analyzing the histogram for a given image.
11) Multiply the measured image from step 9 with the masked image from step 10; This limits visual display to only the area corresponding to the spore. The result is a grayscale image, intensity values below zero point defined in step 9 correspond to Bacillus pumilus, and intensity values above zero point correspond to Bacillus subtilis burner.
12) The final RGB image was then created by setting all “negative” values to red and all “positive” values to green.
In applying high-throughput, non-contact, a real time, with high precision, without little preparation or preparation detect BWAs and CWAs, classification, and a great need exists to be identified. A user base of equipment suitable for purpose analysis of BWAs and CWAs consists of Hazardous Substances (HAZMAT) teams, government and private facilities with high potential threats, postal facilities, universities, industrial and medical laboratories, and the like.
The benefits to target users of systems that immediately detect anthrax or other microbial threats will be substantial. When configured with a macroscopic version of the technology, spectroscopic imaging is used to quickly assess suspected BWAs and CWAs over a large area based on fluorescence, NIR, and / or UV / visible light reactions Can be done. When configured in the microscope mode, positive detection, classification, identification, and visualization of suspected BWAs and CWAs can be made. When configured in Endscope mode, BWAs and CWAs can be detected, classified, identified, and visualized remotely. When configured in FAST mode, BWAs and CWAs can be detected, classified, identified, and visualized with a microscope remotely or in real time. When configured as an air sampling device, BWAs and CWAs can be clearly detected.
When done in combination, the effectiveness of characterizing BWAs and CWAs seems to be enhanced. The benefits include but are not limited to:
• Fast wide-area scanning to detect suspected BWAs and CWAs • Positive detection, classification, identification, and visualization of suspected BWAs and CWAs • Non-contact type • Will only require a small sample preparation? Or sample preparation is not required Remote detection, classification, identification, and visualization of suspected BWAs and CWAs in solid or gas samples Real-time detection, classification, identification, and visualization of suspected BWAs and CWAs in solid or gas samples Visualization will be included.
Specific applications of wide-field imaging and spectroscopy systems for immediate anthrax detection include the following:
• Detection of threats and threat-free “masking” agents • Spatial distribution of BWAs and CWAs • Spatial distribution of BWAs and CWAs leading to a single bacterial spore.
Advantages over currently available technologies Conventional approaches for detection of BWAs and CWAs are based on inoculation methods, enzyme-linked immunosorbent assay (ELISA) methods, BioThreat Alert (BTA) test strips, DNA-based Includes testing, DNA chip analysis, and mass spectrometry. The inoculation method involves inoculating an animal with a suspected culture or specimen and then observing the development of the disease. There are disadvantages to this approach that, in addition to animal abuse, also involves the tremendous amount of time required to reach the point of detection.
The ELISA test includes antibody detection. The technique is also time consuming and has a large number of false positives (irrelevant antibodies react non-specifically with antigen) and, worse, false negatives (interfering compounds in the blood or not sufficiently concentrated for detection) I suffer from a lot of antibodies. In addition, patients test positive for antibodies long after the patient recovers.
The BTA test strip is a small plastic device that is quite similar to the home pregnancy test. The test strip includes a specific antibody on the strip that changes color indicating the presence of a biothreat agent. A negative result means that no biothreat agent is present within the detection limit of the strip. Results are obtained in a relatively short period (15 minutes), but there are many false negatives and false positives.
DNA-based tests by recognizing gene sequences detect biological agents. While more sensitive than BTA test strips, DNA-based tests are sensitive to masking agents and include very long detection times. DNA chip analysis involves immobilizing DNA strands on Si or glass wafer chips. The DNA binds or hybridizes to the complementary DNA strand of the sample being tested. A specially designed microscope detects where the DNA hybridizes. Amplification is accomplished by the polymerase chain reaction (PCR). It is reported that detection of biological threat agents is possible within minutes.
The limitations of DNA-based methods are double. First, DNA methods are designed to detect biological threat agents through unique DNA sequences. Therefore, each DNA test is specific to one biological threat agent, and if it is desired to detect additional biological threat agents, additional test reagents must be developed. The second limitation relates to false negative and false positive problems that arise due to ambient contamination. It is well known that DNA testing has problems in producing correct results in “real” samples.
Mass spectrometry (MS) uses the pattern of mass fragments when cells or spores are subjected to an ionization process under high vacuum to characterize an organism. Mass spectrometry has the benefit of highly sensitive detection, but requires a sophisticated sampling system to deliver a representative sample to the ionization device. The main limitation of MS is that it requires the use of a high vacuum pump that is inherently delicate and effective. A further limitation is that mass spectrometry is a destructive technique as opposed to spectrochemical imaging, which is a completely non-destructive technique.
Alternative techniques / opportunities include micro-probes or microscopes based on micro-spectroscopy, including Raman, fluorescence, NIR, etc., which are rapid, non-contact and accurate detection of BWAs and CWAs. These types of tools may detect, classify, identify, and visualize BWAs and CWAs in the presence of BWAs, CWAs, and / or threat-free “masking” agents in local or remote environments—prior art Provides features that don't give. Such tools reduce false positives and legislator outbreaks, and provide a way to determine in real minutes whether a real biological threat exists.
Other Spectroscopy-Based Methods Spectroscopic techniques compete with previously described techniques, including infrared (IR) spectroscopy. IR spectroscopy does not compete because of the difficulty of strong water absorption in IR. As a result, the BWA • IR spectrum has a false strong water signal.
Obviously, many modifications and variations of the present invention are possible within the scope of the above teachings. Therefore, it is to be understood that the invention can be practiced within the scope of the appended claims beyond what has been specifically described.
FIG. 1 is a schematic diagram of room temperature air BWA and CWA sensors based on optical spectroscopic detection. FIG. 2 shows wide-field dispersed Raman spectra of three different bacterial spores containing anthrax analogs. FIG. 3 is a micro image field of fluorescence spectroscopy of two different bacterial spores. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. FIG. 4A shows the dispersed Raman spectra (green laser excitation) of 6 unknown powders through the vial. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. FIG. 4B shows the dispersed Raman spectra (red laser excitation) of 6 unknown powders. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4C-4E (samples 1331-002) show the results of the first dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is an inorganic substance and looks like talc. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4C-4E (samples 1331-002) show the results of the first dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is an inorganic substance and looks like talc. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4E-4F (samples 1325-002) show the results of the second dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is organic, looks like starch, and is probably corn starch. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4E-4F (samples 1325-002) show the results of the second dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is organic, looks like starch, and is probably corn starch. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4G-4H (samples 1303-002) show the results of the third dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is organic, looks like starch, and is probably corn starch. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4G-4H (samples 1303-002) show the results of the third dispersed Raman, IR, and SEM-EDS of 6 unknown samples. The sample is organic, looks like starch, and is probably corn starch. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. 4I-4N (Samples 1291-006) show the results of the dispersed Raman, IR, and SEM-EDS of the remaining unknown samples. There are three different types of powder in this sample. All three are organic and two of the three are quite aluminosilicates. One of the powders appears to be an aromatic hydrocarbon complex. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. FIG. 4O shows the Raman spectrum of a common white powder used as a masking agent. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. FIG. 4P shows the difference in Raman spectra of various Bacillus spores. FIGS. 4A-4Q show the results of a preliminary phase of dispersion spectroscopy testing of samples sent by the US Army Pathology Institute (AFIP), an expert in analyzing the objectives of biological threat detection techniques. These samples include 6 unknown powders and BG spore samples. FIG. 4Q shows a wide-field Raman image in which two similar spores are identified based on the difference in autofluorescence, where two similar spores differentiate. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5A shows the raw data of the dispersion Raman spectrum of BT and suspension residue. The residue is obtained from the suspension. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5B shows the background corrected BT and residue spectra. Both the spore spectrum and the residue spectrum were divided by the spectrum of the microscope slide. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5C shows the raw data of the dispersed Raman spectra of BC and suspended residues. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5D shows the background corrected BC and residue dispersion Raman spectra. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5E shows microscope slide background corrected sample BT, BC, and BG dispersion spectral overlay. The spectrum was different. The difference is greatest in the fingerprint area. Figures 5A-5F show results from additional spore samples specifically selected. This is because there are inherent difficulties in identifying the species. These include Bacillus touringensis (BT), Bacillus cereus (BC), and BG. The Raman spectra from the three spores are different. These differences suggest a good opportunity to distinguish anthrax from threatless bacteria. The details are as follows. FIG. 5F shows the superposition of 3 spores after subtracting the baseline and normalizing to the CH region spectral feature (˜2950 cm −1 ). FIG. 6 shows how Raman spectra can be applied to distinguish between multiple bacterial strains within a single species. FIG. 7 shows how the Raman spectrum is applied to distinguish between the same species and strains of bacteria growing under different conditions. FIG. 8 shows the reproducibility of the measurement of different areas of Anthrax spores. FIG. 9 shows how the distributed Raman spectrum can be applied to distinguish between live and non-live endospores, distinguishing critical variables in measuring actual threat levels It can be applied to FIG. 10 shows the S / N ratio obtained in fluorescence or Raman spectrum detection using the wide field method. This quantifies the ability to detect low concentrations of microorganisms. FIG. 11 shows the ROC curve obtained from the wide field method and the high sensitivity and digital spectrum analysis high sensitivity and dispersion spectroscopy showing selectivity in anthrax detection. FIG. 12 shows a hand-held pathogenic microorganism detection unit based on the wide-field Raman method of the present invention.
A method for examining the presence of anthrax (Bacillus anthracis) on a support, comprising:
a) Select a first region from the surface of the support, where the first region is wide enough to contain a small number of anthrax organisms, then b) within the first region for further investigation And c) irradiating the wide field + the surrounding area of the wide field with sufficient energy to photobleach the illuminated area, and then d) Raman from the wide field Collecting said shifted light, and then e) analyzing said Raman shifted light for characteristic patterns of anthrax microorganisms.
The method of claim 1, further comprising repeating steps a) -e) for the second region.
The method of claim 1, wherein the analyzing step comprises analyzing the strain of anthrax microorganisms.
The method of claim 1, wherein the analyzing step comprises analyzing the viability of the anthrax microorganism.
The method of claim 1, wherein the analyzing step comprises analyzing a growth medium on which the anthrax microorganism has been grown.
A method for investigating the presence of pathogenic microorganisms on a support comprising:
a) Select a first region from the surface of the support, where the first region is wide enough to contain a small number of pathogenic microorganisms, and then b) within the first region for further investigation Select a wide field of view, then c) irradiate the wide field + the surrounding area of the wide field with sufficient energy to photobleach the illuminated area, and then d) Raman shift from the wide field of view And e) analyzing the Raman-shifted light for a characteristic pattern of pathogenic microorganisms.
The method of claim 6, further comprising repeating steps a) -e) for the second region.
The method of claim 6, wherein the analyzing step comprises analyzing the strain of the pathogenic microorganism.
The method of claim 6, wherein the analyzing step comprises analyzing the viability of the pathogenic microorganism.
The method according to claim 6, wherein the analyzing step comprises analyzing a growth medium on which the pathogenic microorganism has grown.
7. The method of claim 6, wherein Raman shifted light from a wide field of view passes through a point, line, or image focus type spectrometer.
The method according to claim 6, wherein the pathogenic microorganism is anthrax spores.
The method according to claim 6, wherein the pathogenic microorganism is protozoa.
The method according to claim 6, wherein the pathogenic microorganism is a Cryptosporidium microorganism.
The method according to claim 6, wherein the pathogenic microorganism is an Escherichia coli microorganism.
The method according to claim 6, wherein the pathogenic microorganism is an Escherichia coli 157 microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a plague (Yersinia pestis) microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a variola ajor microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Tularemia (Francisella tularensis) microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Brucella (Brucela species) microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Clostridium perfringens microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Salmonella microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Shigella microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a bursal (Burkholderia mallei) microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Burkholderia pseudomallei microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a parrot disease (Chlamydia psittci) microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a Q fever (Coxiella burnetii) microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a typhus (Rickettsia prowazekii) microorganism.
7. The method according to claim 6, wherein the pathogenic microorganism is a Vibrio cholerae microorganism.
The pathogenic microorganisms include: filovirus (eg, Ebola virus and Marburg virus), virus (eg, Lassa fever and Macpovirus), and alphavirus (eg, Venezuelan equine encephalitis, eastern equine encephalitis, and western equine). The method according to claim 6, which is selected from the group of encephalitis.
The method of claim 6, wherein the pathogenic microorganism is a Giardia microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a Candida albicans microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is an Enterococcus faecalis microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Staphylococcus epidermidis microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Staphylococcus aureus microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is an Enterobacter aerogenes microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Corynebacterium diphtheriae microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Pseudomonas aeruginosa microorganism.
The method according to claim 6, wherein the pathogenic microorganism is an Acinetobacter calcoaceticus microorganism.
The method according to claim 6, wherein the pathogenic microorganism is a Klebsiella pneumoniae microorganism.
7. The method of claim 6, wherein the pathogenic microorganism is a Serratia marcescens microorganism.
The method according to claim 6, wherein the irradiation light is in an ultraviolet spectral region having a wavelength of less than 410 nm.
The method according to claim 6, wherein the irradiation light is in a visible light spectrum region having a wavelength of 410 nm to 780 nm.
The method according to claim 6, wherein the irradiation light is in a near infrared spectral region having a wavelength of 780 nm to 2500 nm.
The method of claim 6, wherein the analyzing step comprises analyzing a strain of pathogenic microorganisms.
The method of claim 6, wherein the analyzing step comprises analyzing the viability of pathogenic microorganisms.
The method of claim 6, wherein the miniaturized component is used to enable a handheld detector.
JP2006517613A 2002-01-10 2004-06-24 Wide-field method for detecting pathogenic microorganisms Pending JP2007524389A (en)
US10/608,470 US7057721B2 (en) 2002-01-10 2003-06-27 Wide field method for detecting pathogenic microorganisms
PCT/US2004/020266 WO2005060380A2 (en) 2003-06-27 2004-06-24 Wide field method for detecting pathogenic microorganisms
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