ArticlePloS one2020
Confocal Raman microscopy to identify bacteria in oral subgingival biofilm models.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 31 citations in OpenAlex.
- Portable Raman spectroscopy combined with machine learning for rapid and label-free recognition of five pathogenic bacteria.Frontiers in microbiology · 2026Article
- The role of salivary metabolomics in chronic periodontitis: bridging oral and systemic diseases.Metabolomics : Official journal of the Metabolomic Society · 2025Review
- Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers.Journal of cellular and molecular medicine · 2024Article
- Omics for deciphering oral microecology.International journal of oral science · 2024Review
- Characterization and morphological methods for oral biofilm visualization: where are we nowadays?AIMS microbiology · 2024Review
- Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids.Journal of biomedical optics · 2023Article
- Identification of foodborne pathogenic bacteria using confocal Raman microspectroscopy and chemometrics.Frontiers in microbiology · 2022Article
- Raman Spectroscopy: A Potential Diagnostic Tool for Oral Diseases.Frontiers in cellular and infection microbiology · 2022Review
- Fast label-free identification of bacteria by synchronous fluorescence of amino acids.Analytical and bioanalytical chemistry · 2021Article
- Recent progress in analyzing the spatial structure of the human microbiome: distinguishing biogeography and architecture in the oral and gut communities.Current opinion in endocrine and metabolic research · 2021Article
- Mapping of a Subgingival Dual-Species Biofilm Model Using Confocal Raman Microscopy.Frontiers in microbiology · 2021Article
- Neutrophil Extracellular Traps Promote the Development and Growth of Human Salivary Stones.Cells · 2020Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of oral disease progression, in relation to the accumulation of subgingival biofilm in gingivitis and periodontitis is limited, due to either the ability to monitor plaque in vitro. When compared, optical spectroscopic techniques offer advantages over traditional destructive or biofilm staining approaches, making it a suitable alternative for the analysis and continued development of three-dimensional structures. In this work, we have developed a confocal Raman spectroscopy analysis approach towards in vitro subgingival plaque models. The main objective of this study was to develop a method for differentiating multiple oral subgingival bacterial species in planktonic and biofilm conditions, using confocal Raman microscopy. Five common subgingival bacteria (Fusobacterium nucleatum, Streptococcus mutans, Veillonella dispar, Actinomyces naeslundii and Prevotella nigrescens) were used and differentiated using a 2-way orthogonal Partial Least Square with Discriminant Analysis (O2PLS-DA) for the collected spectral data. In addition to planktonic growth, mono-species biofilms cultured using the 'Zürich Model' were also analyzed. The developed method was successfully used to predict planktonic and mono-species biofilm species in a cross validation setup. The results show differences in the presence and absence of chemical bands within the Raman spectra. The O2PLS-DA model was able to successfully predict 100% of all tested planktonic samples and 90% of all mono-species biofilm samples. Using this approach we have shown that Confocal Raman microscopy can analyse and predict the identity of planktonic and mono-species biofilm species, thus enabling its potential as a technique to map oral multi-species biofilm models.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.