Surface-enhanced Raman spectroscopy of microorganisms: limitations and applicability on the single-cell level

Author(s): Ruben Weiss ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵ , Márton Palatinszky ⁶ ^, ⁷ ^, ⁸ ^, ⁹ ^, ¹⁰ , Michael Wagner ⁶ ^, ⁷ ^, ⁸ ^, ⁹ ^, ¹⁰ , Reinhard Niessner ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵ , Martin Elsner ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵ , Michael Seidel ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵ , Natalia P. Ivleva ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵

Publication date (Electronic): 2019

Journal: The Analyst

Publisher: Royal Society of Chemistry (RSC)

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Abstract

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies.

Abstract

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies. An emerging technique to analyse microbes at single-cell resolution is surface-enhanced Raman spectroscopy (surface-enhanced Raman scattering: SERS). Optimised SERS procedures enable fast analytical read-outs with specific molecular information, providing insight into the chemical composition of microbiological samples. Knowledge about the origin of microbial SERS signals and parameter(s) affecting their occurrence, intensity and/or reproducibility is crucial for reliable SERS-based analyses. In this work, we explore the feasibility and limitations of the SERS approach for characterizing microbial cells and investigate the applicability of SERS for single-cell sorting as well as for three-dimensional visualization of microbial communities. Analyses of six different microbial species (an archaeon, two Gram-positive bacteria, three Gram-negative bacteria) showed that for several of these organisms distinct features in their SERS spectra were lacking. As additional confounding factor, the physiological conditions of the cells (as influenced by e.g., storage conditions or deuterium-labelling) were systematically addressed, for which we conclude that the respective SERS signal at the single-cell level is strongly influenced by the metabolic activity of the analysed cells. While this finding complicates the interpretation of SERS data, it may on the other hand enable probing of the metabolic state of individual cells within microbial populations of interest.

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Complete nitrification by Nitrospira bacteria

Holger Daims, Elena Lebedeva, Petra Pjevac … (2015)

Nitrification, the oxidation of ammonia via nitrite to nitrate, has always been considered as a two-step process catalyzed by chemolithoautotrophic microorganisms oxidizing either ammonia or nitrite. No known nitrifier carries out both steps, although complete nitrification should be energetically advantageous. This functional separation has puzzled microbiologists for a century. Here we report on the discovery and cultivation of a completely nitrifying bacterium from the genus Nitrospira, a globally distributed group of nitrite oxidizers. The genome of this chemolithoautotrophic organism encodes both the pathways for ammonia and nitrite oxidation, which are concomitantly expressed during growth by ammonia oxidation to nitrate. Genes affiliated with the phylogenetically distinct ammonia monooxygenase and hydroxylamine dehydrogenase genes of Nitrospira are present in many environments and were retrieved on Nitrospira-contigs in new metagenomes from engineered systems. These findings fundamentally change our picture of nitrification and point to completely nitrifying Nitrospira as key components of nitrogen-cycling microbial communities.

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Roland Hatzenpichler, Elena Lebedeva, Eva Spieck … (2008)

The recent discovery of ammonia-oxidizing archaea (AOA) dramatically changed our perception of the diversity and evolutionary history of microbes involved in nitrification. In this study, a moderately thermophilic (46 degrees C) ammonia-oxidizing enrichment culture, which had been seeded with biomass from a hot spring, was screened for ammonia oxidizers. Although gene sequences for crenarchaeotal 16S rRNA and two subunits of the ammonia monooxygenase (amoA and amoB) were detected via PCR, no hints for known ammonia-oxidizing bacteria were obtained. Comparative sequence analyses of these gene fragments demonstrated the presence of a single operational taxonomic unit and thus enabled the assignment of the amoA and amoB sequences to the respective 16S rRNA phylotype, which belongs to the widely distributed group I.1b (soil group) of the Crenarchaeota. Catalyzed reporter deposition (CARD)-FISH combined with microautoradiography (MAR) demonstrated metabolic activity of this archaeon in the presence of ammonium. This finding was corroborated by the detection of amoA gene transcripts in the enrichment. CARD-FISH/MAR showed that the moderately thermophilic AOA is highly active at 0.14 and 0.79 mM ammonium and is partially inhibited by a concentration of 3.08 mM. The enriched AOA, which is provisionally classified as "Candidatus Nitrososphaera gargensis," is the first described thermophilic ammonia oxidizer and the first member of the crenarchaeotal group I.1b for which ammonium oxidation has been verified on a cellular level. Its preference for thermophilic conditions reinvigorates the debate on the thermophilic ancestry of AOA.

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Discrimination of bacteria using surface-enhanced Raman spectroscopy.

Roger M Jarvis, Royston Goodacre (2004)

Raman spectroscopy has recently been shown to be a potentially powerful whole-organism fingerprinting technique and is attracting interest within microbial systematics for the rapid identification of bacteria and fungi. However, while the Raman effect is so weak that only approximately 1 in 10(8) incident photons are Raman scattered (so that collection times are in the order of minutes), it can be greatly enhanced (by some 10(3)-10(6)-fold) if the molecules are attached to, or microscopically close to, a suitably roughened surface, a technique known as surface-enhanced Raman scattering (SERS). In this study, SERS, employing an aggregated silver colloid substrate, was used to analyze a collection of clinical bacterial isolates associated with urinary tract infections. While each spectrum took 10 s to collect, to acquire reproducible data, 50 spectra were collected making the spectral acquisition times per bacterium approximately 8 min. The multivariate statistical techniques of discriminant function analysis (DFA) and hierarchical cluster analysis (HCA) were applied in order to group these organisms based on their spectral fingerprints. The resultant ordination plots and dendrograms showed correct groupings for these organisms, including discrimination to strain level for a sample group of Escherichia coli, which was validated by projection of test spectra into DFA and HCA space. We believe this to be the first report showing bacterial discrimination using SERS.