Confocal Raman microscopy to identify bacteria in oral subgingival biofilm models

Characterization and morphological methods for oral biofilm visualization: where are we nowadays?

The oral microbiome represents an essential component of the oral ecosystem whose symbiotic relationship contributes to health maintenance. The biofilm represents a state of living of microorganisms surrounding themselves with a complex and tridimensional organized polymeric support and defense matrix. The substrates where the oral biofilm adhere can suffer from damages due to the microbial community metabolisms. Therefore, microbial biofilm represents the main etiological factor of the two pathologies of dental interest with the highest incidence, such as carious pathology and periodontal pathology. The study, analysis, and understanding of the characteristics of the biofilm, starting from the macroscopic structure up to the microscopic architecture, appear essential. This review examined the morphological methods used through the years to identify species, adhesion mechanisms that contribute to biofilm formation and stability, and how the action of microbicidal molecules is effective against pathological biofilm. Microscopy is the primary technique for the morphological characterization of biofilm. Light microscopy, which includes the stereomicroscope and confocal laser microscopy (CLSM), allows the visualization of microbial communities in their natural state, providing valuable information on the spatial arrangement of different microorganisms within the biofilm and revealing microbial diversity in the biofilm matrix. The stereomicroscope provides a three-dimensional view of the sample, allowing detailed observation of the structure, thickness, morphology, and distribution of the various species in the biofilm while CLSM provides information on its three-dimensional architecture, microbial composition, and dynamic development. Electron microscopy, scanning (SEM) or transmission (TEM), allows the high-resolution investigation of the architecture of the biofilm, analyzing the bacterial population, the extracellular polymeric matrix (EPS), and the mechanisms of the physical and chemical forces that contribute to the adhesion of the biofilm to the substrates, on a nanometric scale. More advanced microscopic methodologies, such as scanning transmission electron microscopy (STEM), high-resolution transmission electron microscopy (HR-TEM), and correlative microscopy, have enabled the evaluation of antibacterial treatments, due to the potential to reveal the efficacy of different molecules in breaking down the biofilm. In conclusion, evidence based on scientific literature shows that established microscopic methods represent the most common tools used to characterize biofilm and its morphology in oral microbiology. Further protocols and studies on the application of advanced microscopic techniques are needed to obtain precise details on the microbiological and pathological aspects of oral biofilm.

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for clinical relevance, which facilitates the understanding of S. enterica transmission routes and the determination of outbreak sources. Classical serotyping methods via molecular subtyping and genomic markers currently suffer from various limitations, such as labour intensiveness, time consumption, etc. Therefore, there is a pressing need to develop new diagnostic techniques. Surface-enhanced Raman spectroscopy (SERS) is a non-invasive diagnostic technique that can generate Raman spectra, based on which rapid and accurate discrimination of bacterial pathogens could be achieved. To generate SERS spectra, a Raman spectrometer is needed to detect and collect signals, which are divided into two types: the expensive benchtop spectrometer and the inexpensive handheld spectrometer. In this study, we compared the performance of two Raman spectrometers to discriminate four closely associated S. enterica serovars, that is, S. enterica subsp. enterica serovar dublin, enteritidis, typhi and typhimurium. Six machine learning algorithms were applied to analyse these SERS spectra. The support vector machine (SVM) model showed the highest accuracy for both handheld (99.97%) and benchtop (99.38%) Raman spectrometers. This study demonstrated that handheld Raman spectrometers achieved similar prediction accuracy as benchtop spectrometers when combined with machine learning models, providing an effective solution for rapid, accurate and cost-effective identification of closely associated S. enterica serovars.

Omics for deciphering oral microecology

The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.

Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids

SIGNIFICANCE

Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing.

AIM

An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise.

RESULTS

Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility.

CONCLUSIONS

A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.

Identification of foodborne pathogenic bacteria using confocal Raman microspectroscopy and chemometrics

Rapid and accurate identification of foodborne pathogenic bacteria is of great importance because they are often responsible for the majority of serious foodborne illnesses. The confocal Raman microspectroscopy (CRM) is a fast and easy-to-use method known for its effectiveness in detecting and identifying microorganisms. This study demonstrates that CRM combined with chemometrics can serve as a rapid, reliable, and efficient method for the detection and identification of foodborne pathogenic bacteria without any laborious pre-treatments. Six important foodborne pathogenic bacteria including S. flexneri, L. monocytogenes, V. cholerae, S. aureus, S. typhimurium, and C. botulinum were investigated with CRM. These pathogenic bacteria can be differentiated based on several characteristic peaks and peak intensity ratio. Principal component analysis (PCA) was used for investigating the difference of various samples and reducing the dimensionality of the dataset. Performances of some classical classifiers were compared for bacterial detection and identification including decision tree (DT), artificial neural network (ANN), and Fisher's discriminant analysis (FDA). Correct recognition ratio (CRR), area under the receiver operating characteristic curve (ROC), cumulative gains, and lift charts were used to evaluate the performance of models. The impact of different pretreatment methods on the models was explored, and pretreatment methods include Savitzky-Golay algorithm smoothing (SG), standard normal variate (SNV), multivariate scatter correction (MSC), and Savitzky-Golay algorithm 1st Derivative (SG 1st Der). In the DT, ANN, and FDA model, FDA is more robust for overfitting problem and offers the highest accuracy. Most pretreatment methods raised the performance of the models except SNV. The results revealed that CRM coupled with chemometrics offers a powerful tool for the discrimination of foodborne pathogenic bacteria.

A preliminary study on surface bioactivation of polyaryletherketone by UV-grafting with PolyNaSS: influence on osteogenic and antibacterial activities

Polyaryletherketone (PAEK) has good biocompatibility and mechanical properties and thus may have great potential in the fields of reparative medicine and bone intervention. In this study, the key representative PAEKs, polyetheretherketone (PEEK) and polyetherketoneketone (PEKK), were modified by UV grafting with sodium polystyrene sulfonate (polyNaSS) to improve their biocompatibility. Toluidine blue staining and Fourier transform infrared spectroscopic analyses showed that sulfonic acid groups were successfully introduced into PAEK, and the hydrophilicity and protein adsorption capacity of the materials were enhanced in a concentration-dependent manner. The effects of the grafted polyNaSS on osteoinduction and antibacterial properties of PAEK were analyzed in detail. We found that polyNaSS enhanced the viability, alkaline phosphatase activity, calcium mineral deposition, and levels of expression of osteoblast-related genes and proteins of adherent human umbilical cord Wharton's jelly-derived mesenchymal stem cells. In addition, when Escherichia coli, Staphylococcus aureus and Porphyromonas gingivalis were incubated with the materials, bacterial colony counting revealed that grafting of polyNaSS onto PAEK led to more potent inhibition of bacterial adhesion, and polyNaSS-grafted PEKK had stronger antibacterial performance than did polyNaSS-grafted PEEK fabricated under the same grafting conditions. These data show that polyNaSS-grafted PAEK, and particularly polyNaSS-grafted PEKK, may be useful as orthopedic and dental implant materials.

A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.

Raman Spectroscopy: A Potential Diagnostic Tool for Oral Diseases

Oral diseases impose a major health burden worldwide and have a profound effect on general health. Dental caries, periodontal diseases, and oral cancers are the most common oral health conditions. Their occurrence and development are related to oral microbes, and effective measures for their prevention and the promotion of oral health are urgently needed. Raman spectroscopy detects molecular vibration information by collecting inelastic scattering light, allowing a “fingerprint” of a sample to be acquired. It provides the advantages of rapid, sensitive, accurate, and minimally invasive detection as well as minimal interference from water in the “fingerprint region.” Owing to these characteristics, Raman spectroscopy has been used in medical detection in various fields to assist diagnosis and evaluate prognosis, such as detecting and differentiating between bacteria or between neoplastic and normal brain tissues. Many oral diseases are related to oral microbial dysbiosis, and their lesions differ from normal tissues in essential components. The colonization of keystone pathogens, such as Porphyromonas gingivalis, resulting in microbial dysbiosis in subgingival plaque, is the main cause of periodontitis. Moreover, the components in gingival crevicular fluid, such as infiltrating inflammatory cells and tissue degradation products, are markedly different between individuals with and without periodontitis. Regarding dental caries, the compositions of decayed teeth are transformed, accompanied by an increase in acid-producing bacteria. In oral cancers, the compositions and structures of lesions and normal tissues are different. Thus, the changes in bacteria and the components of saliva and tissue can be used in examinations as special markers for these oral diseases, and Raman spectroscopy has been acknowledged as a promising measure for detecting these markers. This review summarizes and discusses key research and remaining problems in this area. Based on this, suggestions for further study are proposed.

Mapping of a Subgingival Dual-Species Biofilm Model Using Confocal Raman Microscopy

Techniques for continuously monitoring the formation of subgingival biofilm, in relation to the determination of species and their accumulation over time in gingivitis and periodontitis, are limited. In recent years, advancements in the field of optical spectroscopic techniques have provided an alternative for analyzing three-dimensional microbiological structures, replacing the traditional destructive or biofilm staining techniques. In this work, we have demonstrated that the use of confocal Raman spectroscopy coupled with multivariate analysis provides an approach to spatially differentiate bacteria in an in vitro model simulating a subgingival dual-species biofilm. The present study establishes a workflow to evaluate and differentiate bacterial species in a dual-species in vitro biofilm model, using confocal Raman microscopy (CRM). Biofilm models of Actinomyces denticolens and Streptococcus oralis were cultured using the “Zürich in vitro model” and were analyzed using CRM. Cluster analysis was used to spatially differentiate and map the biofilm model over a specified area. To confirm the clustering of species in the cultured biofilm, confocal laser scanning microscopy (CLSM) was coupled with fluorescent in vitro hybridization (FISH). Additionally, dense bacteria interface area (DBIA) samples, as an imitation of the clusters in a biofilm, were used to test the developed multivariate differentiation model. This confirmed model was successfully used to differentiate species in a dual-species biofilm and is comparable to morphology. The results show that the developed workflow was able to identify main clusters of bacteria based on spectral “fingerprint region” information from CRM. Using this workflow, we have demonstrated that CRM can spatially analyze two-species in vitro biofilms, therefore providing an alternative technique to map oral multi-species biofilm models.

Fast label-free identification of bacteria by synchronous fluorescence of amino acids

Fast identification of pathogenic bacteria is an essential need for patient's diagnostic in hospitals and environmental monitoring of water and air quality. Bacterial cells consist of a very high amount of biological molecules whose content changes in response to different environmental conditions. The similarity between the molecular compositions of different bacterial cells limits the possibility to find unique markers to enable differentiation among species. Although many biological molecules in the cells absorb at the UV-Vis region, only a few of them can be detected in whole cells by their intrinsic fluorescence. Among these molecules are the amino acids phenylalanine, tyrosine, and tryptophan. In this work, we develop a rapid method for bacterial identification by synchronous fluorescence. We show that we can quantify the concentration for the 3 amino acids without any significant interference from other fluorophores in the cells and that we can differentiate among 6 pathogenic bacterial species by using the concentrations of their amino acids as a bacterial fingerprint. Fluorescent amino acids exist in all living cells. Therefore, this method has the potential to be applicative for the rapid identification of cells from all kinds of organisms.

Recent progress in analyzing the spatial structure of the human microbiome: distinguishing biogeography and architecture in the oral and gut communities

Fueled by technological advances in methods for sample collection and preservation in sequencing studies, and in advances in computational analyses of high content image data, the spatial structure of the human microbiome is coming to light. In this mini-review, we summarize recent developments in our understanding of the structure of two human microbiomes: the lower gut and the oral cavity. We focus on only the most recent literature and we make an important distinction between two forms of spatial structure, governed by scale: biogeography and architecture. By segmenting the study of microbiome spatial structure into two categories, we demonstrate the potential to greatly advance our understanding of the mechanistic principles that link structure and function in the microbiome.

Construction and performance evaluation of a sustained release implant material polyetheretherketone with antibacterial properties

OBJECTIVE

This study aimed to construct a tightly binding antibiotic sustained release system on the polyetheretherketone (PEEK) surface and investigate the cellular activity and antibacterial properties of the new oral implant materials.

METHODS

Low-temperature argon plasma under certain parameters was used to prepare P-PEEK with nano-topology, and chemical deposition technology was adopted to form a polydopamine (PDA) coating on the PEEK surface to build a biological binding platform, PDA/P-PEEK. Subsequently, vancomycin gelatin nanoparticles (Van-GNPs) were prepared by two-step desolvation method. Finally, Van-GNPs were combined with PEEK implant material surface to form a new composite material, Van-GNPs/PEEK. scanning electron microscope (SEM), atomic force microscope (AFM), energy dispersive spectrometer (EDS), and contact angle tester were used to comprehensively characterize the materials. The in vitro release test of Van was performed by dynamic dialysis with ultraviolet spectrophotometer. The cell cytotoxicity and adhesion tests were studied by mouse embryonic osteoblasts. The antibacterial properties were evaluated by bacterial adhesion test, plate colony counting, and antimicrobial ring test with Staphylococcus aureus and Streptococcus mutans.

RESULTS

PEEK was treated with low-temperature argon plasma and attached to PDA to form a biological binding platform. The synthesized Van-GNPs were smooth, round, with uniform particle size distribution, and bound to PEEK to form a new composite material, which can release Van constantly. Cell experiments showed that Van-GNPs/PEEK had no cytotoxicity and had good interaction with osteoblasts. Bacterial experiments showed that surface conjugation with Van-GNPs could significantly improve the antibacterial performance of PEEK against S. aureus and S. mutans.

SIGNIFICANCE

This study demonstrated that Van-GNPs/PEEK have good cellular compatibility and autonomous antibacterial properties, which provide a theoretical basis for the wide application of PEEK in the field of stomatology.

Neutrophil Extracellular Traps Promote the Development and Growth of Human Salivary Stones

Salivary gland stones, or sialoliths, are the most common cause of the obstruction of salivary glands. The mechanism behind the formation of sialoliths has been elusive. Symptomatic sialolithiasis has a prevalence of 0.45% in the general population, is characterized by recurrent painful periprandial swelling of the affected gland, and often results in sialadenitis with the need for surgical intervention. Here, we show by the use of immunohistochemistry, immunofluorescence, computed tomography (CT) scans and reconstructions, special dye techniques, bacterial genotyping, and enzyme activity analyses that neutrophil extracellular traps (NETs) initiate the formation and growth of sialoliths in humans. The deposition of neutrophil granulocyte extracellular DNA around small crystals results in the dense aggregation of the latter, and the subsequent mineralization creates alternating layers of dense mineral, which are predominantly calcium salt deposits and DNA. The further agglomeration and appositional growth of these structures promotes the development of macroscopic sialoliths that finally occlude the efferent ducts of the salivary glands, causing clinical symptoms and salivary gland dysfunction. These findings provide an entirely novel insight into the mechanism of sialolithogenesis, in which an immune system-mediated response essentially participates in the physicochemical process of concrement formation and growth.