Effect of Culture Conditions on the Achievable Taxonomic Resolution of Raman Spectroscopy Disclosed by Three <i>Bacillus</i> Species

Hutsebaut, Didier; Maquelin, Kees; Vos, Paul De; Vandenabeele, Peter; Moëns, Luc; Puppels, Gerwin J.

doi:10.1021/ac049228l

Cited by 60 publications

(60 citation statements)

References 26 publications

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“…Recently, Palchaudhuri et al 88 investigated the uptake and metabolism of the five-carbon sugar alcohol xylitol by gram-positive viridian group Streptococcus and two gram-negative Escherichia coli strains. In assessing Bacillus strains, Hutsebaut et al 89 characterized the influence of culture conditions on the ability of Raman spectroscopy to discriminate between Bacillus cereus, Bac i l l u s p u m i l u s , a n d B a c i l l u s licheniformis. They were able to show that the identification of bacterial cells by Raman spectroscopy at the species level is not sensitive to culture conditions.…”

Section: Biological Applicationsmentioning

confidence: 99%

Methods and Applications of Raman Microspectroscopy to Single-Cell Analysis

2013

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Raman spectroscopy is a powerful biochemical analysis technique that allows for the dynamic characterization and imaging of living biological cells in the absence of fluorescent stains. In this review, we summarize some of the most recent developments in the noninvasive biochemical characterization of single cells by spontaneous Raman scattering. Different instrumentation strategies utilizing confocal detection optics, multispot, and line illumination have been developed to improve the speed and sensitivity of the analysis of single cells by Raman spectroscopy. To analyze and visualize the large data sets obtained during such experiments, sophisticated multivariate statistical analysis tools are necessary to reduce the data and extract components of interest. We highlight the most recent applications of single cell analysis by Raman spectroscopy and their biomedical implications that have enabled the noninvasive characterization of specific metabolic states of eukaryotic cells, the identification and characterization of stem cells, and the rapid identification of bacterial cells. We conclude the article with a brief look into the future of this rapidly evolving research area.

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Section: Biological Applicationsmentioning

confidence: 99%

Methods and Applications of Raman Microspectroscopy to Single-Cell Analysis

2013

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“…Raman spectroscopy has previously been used for the rapid phenotypic classification of bacterial genera, including Enterococcus, Streptococcus, Staphylococcus, Mycobacterium, Bacillus (17)(18)(19)(20)(21), and, more recently, Campylobacter (22). The high sensitivity of this technique has been shown to achieve discrimination down to the subspecies level (15).…”

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confidence: 99%

Evidence for Phenotypic Plasticity among Multihost Campylobacter jejuni and C. coli Lineages, Obtained Using Ribosomal Multilocus Sequence Typing and Raman Spectroscopy

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Woodcock

Strachan

et al. 2013

Appl Environ Microbiol

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g Closely related bacterial isolates can display divergent phenotypes. This can limit the usefulness of phylogenetic studies for understanding bacterial ecology and evolution. Here, we compare phenotyping based on Raman spectrometric analysis of cellular composition to phylogenetic classification by ribosomal multilocus sequence typing (rMLST) in 108 isolates of the zoonotic pathogens Campylobacter jejuni and C. coli. Automatic relevance determination (ARD) was used to identify informative peaks in the Raman spectra that could be used to distinguish strains in taxonomic and host source groups (species, clade, clonal complex, and isolate source/host). Phenotypic characterization based on Raman spectra showed a degree of agreement with genotypic classification using rMLST, with segregation accuracy between species (83.95%), clade (in C. coli, 98.41%), and, to some extent, clonal complex (86.89% C. jejuni ST-21 and ST-45 complexes) being achieved. This confirmed the utility of Raman spectroscopy for lineage classification and the correlation between genotypic and phenotypic classification. In parallel analysis, relatively distantly related isolates (different clonal complexes) were assigned the correct host origin irrespective of the clonal origin (74.07 to 96.97% accuracy) based upon different Raman peaks. This suggests that the phenotypic characteristics, from which the phenotypic signal is derived, are not fixed by clonal descent but are influenced by the host environment and change as strains move between hosts.

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“…Due to the changed nutrient and incubation conditions by adaptation to the new matrix, it is probable that the bacterial growth behavior was modified (16,45). Changes caused by these factors become manifest as variations in the bacterial Raman spectra.…”

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confidence: 99%

Raman Spectroscopy as a Potential Tool for Detection of Brucella spp. in Milk

Meisel

Stöckel

Elschner

et al. 2012

Appl Environ Microbiol

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Detection of Brucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possible Brucella isolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identify Brucella from agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of different Brucella, Escherichia, Ochrobactrum, Pseudomonas, and Yersinia spp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% for Brucella from medium and 94% for Brucella from milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detecting Brucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.

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Effect of Culture Conditions on the Achievable Taxonomic Resolution of Raman Spectroscopy Disclosed by Three Bacillus Species

Cited by 60 publications

References 26 publications

Methods and Applications of Raman Microspectroscopy to Single-Cell Analysis

Methods and Applications of Raman Microspectroscopy to Single-Cell Analysis

Evidence for Phenotypic Plasticity among Multihost Campylobacter jejuni and C. coli Lineages, Obtained Using Ribosomal Multilocus Sequence Typing and Raman Spectroscopy

Raman Spectroscopy as a Potential Tool for Detection of Brucella spp. in Milk

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