Raman Chemical Imaging Spectroscopy Reagentless Detection and Identification of Pathogens:  Signature Development and Evaluation

Kalasinsky, Kathryn S.; Hadfield, Ted L.; Shea, April A.; Kalasinsky, V. F.; Nelson, Matthew P.; Neiss, Jason H.; Drauch, Amy; Vanni, G Steven; Treado, Patrick J.

doi:10.1021/ac0700575

Cited by 135 publications

(90 citation statements)

References 56 publications

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“…5 have a sharp rising edge on the shorter wavenumber side, and resolved peak structures on the longer wavenumber side. The peak profile observed here is similar to the profiles (with shoulder structures on the longer wavenumber side) of the Raman spectra of Bacillus anthracis (Ba), B.cereus (Bc), B. globigii (Bg), and B. thuringiensis (Bt) measured using Raman chemical imaging microscopy [58]. Similarly, Raman spectra of waterborne pathogens also have this shoulder on the longer wavenumber side [59].…”

Section: Comparison Of Ptrs Spectra Of Three Pollens and One Type Of supporting

confidence: 76%

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Wang

Pan

Hill

et al. 2015

Journal of Quantitative Spectroscopy and Radiative Transfer

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a b s t r a c tPhotophoretic trapping-Raman spectroscopy (PTRS) is a new technique for measuring Raman spectra of particles that are held in air using photophoretic forces. It was initially demonstrated with Raman spectra of strongly-absorbing carbon nanoparticles (Pan et al.[44] (Opt Express 2012)). In the present paper we report the first demonstration of the use of PTRS to measure Raman spectra of absorbing and weakly-absorbing bioaerosol particles (pollens and spores). Raman spectra of three pollens and one smut spore in a size range of 6.2-41.8 mm illuminated at 488 nm are shown. Quality spectra were obtained in the Raman shift range of 1600-3400 cm À 1 in this exploratory study. Distinguishable Raman scattering signals with one or a few clear Raman peaks for all four aerosol particles were observed within the wavenumber region 2940-3030 cm À 1 . Peaks in this region are consistent with previous reports of Raman peaks in the 1600-3400 cm À 1 range for pollens and spores excited at 514 nm measured by a conventional Raman spectrometer. Noise in the spectra, the fluorescence background, and the weak Raman signals in most of the 1600-3400 cm À 1 region make some of the spectral features barely discernable or not discernable for these bioaerosols except the strong signal within 2940-3030 cm À 1 . Up to five bands are identified in the three pollens and only two bands appear in the fungal spore, but this may be because the fungal spore is so much smaller than any of the pollens. The fungal spore signal relative to the air-nitrogen Raman band is approximately 10 times smaller than that ratio for the pollens. The five bands are tentatively assigned to the CH 2 symmetric stretch at 2948 cm À 1 , CH 2 Fermi resonance stretch at 2970 cm À 1 , CH 3 symmetric stretch at 2990 cm À 1 , CH 3 out-of-plane end asymmetric stretch at 3010 cm À 1 , and unsaturated ¼ CH stretch at 3028 cm À 1 . The two dominant bands of the up-to-five Raman bands in the 2940-3030 cm À 1 region have a consistent band spacing of 25 cm À 1 in all four aerosols. Finally we discuss improvements to the PTRS that should provide a system which can trap a higher fraction of particle types and obtain Raman spectra over a larger range (e.g., 200-3600 cm À 1 ) than those achieved here.Published by Elsevier Ltd.

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Section: Comparison Of Ptrs Spectra Of Three Pollens and One Type Of supporting

confidence: 76%

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Wang

Pan

Hill

et al. 2015

Journal of Quantitative Spectroscopy and Radiative Transfer

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“…Raman spectra of microbial cells vary between different taxa (55,56), and even between individual cells of the same microbial strain that have experienced different growth conditions (57), because they reflect the cellular chemical composition. Consequently, using information from the entire Raman spectrum to quantify cellular C-D abundance of a microbial cell in a complex sample will not be trivial if the study is not focused on a specific strain and sufficiently defined growth conditions.…”

Section: Resultsmentioning

confidence: 99%

Tracking heavy water (D ₂ O) incorporation for identifying and sorting active microbial cells

Berry

Mader

Lee

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

391

512

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Microbial communities are essential to the function of virtually all ecosystems and eukaryotes, including humans. However, it is still a major challenge to identify microbial cells active under natural conditions in complex systems. In this study, we developed a new method to identify and sort active microbes on the single-cell level in complex samples using stable isotope probing with heavy water (D 2 O) combined with Raman microspectroscopy. Incorporation of D 2 O-derived D into the biomass of autotrophic and heterotrophic bacteria and archaea could be unambiguously detected via C-D signature peaks in single-cell Raman spectra, and the obtained labeling pattern was confirmed by nanoscaleresolution secondary ion MS. In fast-growing Escherichia coli cells, label detection was already possible after 20 min. For functional analyses of microbial communities, the detection of D incorporation from D 2 O in individual microbial cells via Raman microspectroscopy can be directly combined with FISH for the identification of active microbes. Applying this approach to mouse cecal microbiota revealed that the host-compound foragers Akkermansia muciniphila and Bacteroides acidifaciens exhibited distinctive response patterns to amendments of mucin and sugars. By Ramanbased cell sorting of active (deuterated) cells with optical tweezers and subsequent multiple displacement amplification and DNA sequencing, novel cecal microbes stimulated by mucin and/ or glucosamine were identified, demonstrating the potential of the nondestructive D 2 O-Raman approach for targeted sorting of microbial cells with defined functional properties for singlecell genomics.ecophysiology | single-cell microbiology | carbohydrate utilization | nitrifier | Raman microspectroscopy M icroorganisms play a vital role in many environments. They mediate global biogeochemical cycles, catalyze biotechnological processes, and contribute to health and disease in the human body. The in situ study of microbial activity in natural and engineered ecosystems is therefore of great interest. For this purpose, several elegant methods have been established that use either transcriptional or translational activity of community members (i.e., metatranscriptomics, metaproteomics) (1-3) or the incorporation of isotopically labeled substrates into biomolecules (4-10) to infer the ecophysiology of microbes in such systems. However, these bulk techniques do not offer sufficient spatial resolution to study microbial activities at the micrometer scale. Therefore, important information can be overlooked because microbial communities are frequently spatially structured (e.g., biofilms) (11) and contain populations with life cycles (12,13). Furthermore, even apparently identical cells in clonal populations can have strongly divergent activities (14).Consequently, microbial ecophysiology is ideally studied also at the level of the single cell, but only a restricted number of approaches exist for determining physiological properties of individual cells in a microbial community. For exa...

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“…A significant contribution from protein Raman bands is evident in the first spectral component due to the appearance of the Amid I [30][31][32], aromatic breathing [28] and CH stretching peaks at 1653, 1002 and 1444 cm -1 , respectively (Figure 1.C). Glycoproteins and mucin could make the major contribution to this component [47,48]. Several strong Raman peaks of the second component are assigned to acetates (632, 1295, 1434, and 1744 cm -1 ) [49][50][51] and carbohydrates (323 cm -1 and 521 cm -1 ) [46,52], which are also present in saliva [53][54][55].…”

Section: Raman Spectroscopic Signature Of Salivamentioning

confidence: 99%

Discriminant Analysis of Raman Spectra for Body Fluid Identification for Forensic Purposes

Sikirzhytski

Virkler

Lednev

et al. 2010

AIP Conference Proceedings

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Detection and identification of blood, semen and saliva stains, the most common body fluids encountered at a crime scene, are very important aspects of forensic science today. This study targets the development of a nondestructive, confirmatory method for body fluid identification based on Raman spectroscopy coupled with advanced statistical analysis. Dry traces of blood, semen and saliva obtained from multiple donors were probed using a confocal Raman microscope with a 785-nm excitation wavelength under controlled laboratory conditions. Results demonstrated the capability of Raman spectroscopy to identify an unknown substance to be semen, blood or saliva with high confidence.

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Raman Chemical Imaging Spectroscopy Reagentless Detection and Identification of Pathogens: Signature Development and Evaluation

Cited by 135 publications

References 56 publications

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Tracking heavy water (D ₂ O) incorporation for identifying and sorting active microbial cells

Discriminant Analysis of Raman Spectra for Body Fluid Identification for Forensic Purposes

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Raman Chemical Imaging Spectroscopy Reagentless Detection and Identification of Pathogens: Signature Development and Evaluation

Cited by 135 publications

References 56 publications

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Photophoretic trapping-Raman spectroscopy for single pollens and fungal spores trapped in air

Tracking heavy water (D 2 O) incorporation for identifying and sorting active microbial cells

Discriminant Analysis of Raman Spectra for Body Fluid Identification for Forensic Purposes

Contact Info

Product

Resources

About

Tracking heavy water (D ₂ O) incorporation for identifying and sorting active microbial cells