On-line profiling of volatile compounds produced in vitro by pathogenic oral bacteria

Modern approaches for detection of volatile organic compounds in metabolic studies focusing on pathogenic bacteria: Current state of the art

Pathogenic microorganisms produce numerous metabolites, including volatile organic compounds (VOCs). Monitoring these metabolites in biological matrices (e.g., urine, blood, or breath) can reveal the presence of specific microorganisms, enabling the early diagnosis of infections and the timely implementation of targeted therapy. However, complex matrices only contain trace levels of VOCs, and their constituent components can hinder determination of these compounds. Therefore, modern analytical techniques enabling the non-invasive identification and precise quantification of microbial VOCs are needed. In this paper, we discuss bacterial VOC analysis under in vitro conditions, in animal models and disease diagnosis in humans, including techniques for offline and online analysis in clinical settings. We also consider the advantages and limitations of novel microextraction techniques used to prepare biological samples for VOC analysis, in addition to reviewing current clinical studies on bacterial volatilomes that address inter-species interactions, the kinetics of VOC metabolism, and species- and drug-resistance specificity.

Antibiotic treatment and supplemental hemin availability affect the volatile organic compounds produced by P. gingivalis in vitro

We have measured the changes in the production of volatile organic compounds (VOCs) by the oral pathogen Porphyromonas gingivalis, when treated in vitro with the antibiotic amoxicillin. We have also measured the VOC production of P. gingivalis grown in the presence and absence of supplemental hemin. Planktonic bacterial cultures were treated with different amounts of amoxicillin in the lag phase of the bacterial growth. Planktonic bacteria were also cultured with and without supplemental hemin in the culture medium. Concentrations of VOCs were measured with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and further molecular identification was done with gas chromatography-mass spectrometry (GC-MS) using solid phase microextraction (SPME) for sampling. The cell growth of P. gingivalis in the cultures was estimated with optical density measurements at the wavelength of 600 nm (OD₆₀₀). We found that the production of methanethiol, hydrogen sulfide and several short- to medium-chain fatty acids was decreased with antibiotic treatment using amoxicillin. Compounds found to increase with the antibiotic treatment were butyric acid and indole. In cultures without supplemental hemin, indole and short- to medium-chain fatty acid production was significantly reduced. Acetic acid production was found to increase when supplemental hemin was not available. Our results suggest that the metabolic effects of both antibiotic treatment and supplemental hemin availability are reflected in the VOCs produced by P. gingivalis and could be used as markers for bacterial cell growth and response to threat. Analysis of these volatiles from human samples, such as the exhaled breath, could be used in the future to rapidly monitor response to antibacterial treatment.

Volatile composition of the morning breath

We have measured the composition of volatile organic compounds (VOCs) in the morning breath of 30 healthy individuals before and after tooth brushing. The concentrations of VOCs in the breath samples were measured with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and further identification was performed with a combination of solid phase microextraction (SPME) and offline gas chromatography-mass spectrometry (GC-MS). We hypothesize that compounds, whose concentrations significantly decreased in the breath after tooth brushing are largely of microbial origin. In this study, we found 35 such VOCs. Out of these, 33 have been previously connected to different oral niches, such as salivary and subgingival bacteria. We also compared the concentrations of the 35 VOCs found in increased amounts in the morning breath to their respective odor thresholds to evaluate their ability to cause odor. Compounds that could contribute to the breath odor include many volatile sulfur compounds, such as methanethiol, hydrogen sulfide, dimethyl sulfide, and 2-methyl-1-propanethiol, but also other VOCs, such as acetic acid, butyric acid, valeric acid, acetaldehyde, octanal, phenol, indole, ammonia, isoprene, and methyl methacrylate.

Identifying volatile in vitro biomarkers for oral bacteria with proton-transfer-reaction mass spectrometry and gas chromatography-mass spectrometry

We have measured the volatile fingerprints of four pathogenic oral bacteria connected to periodontal disease and dental abscess: Porphyromonas gingivalis (three separate strains), Prevotella intermedia, Prevotella nigrescens and Tannerella forsythia. Volatile fingerprints were measured in vitro from the headspace gas of the bacteria cultured on agar. Concrete identification of new and previously reported bacterial volatiles were performed by a combination of solid phase microextraction (SPME) and offline gas chromatography-mass spectrometry (GC-MS). We also studied the effect of the reduced electric field strength (E/N) on the fragmentation patterns of bacterial volatiles in online proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). We aimed to discover possible new biomarkers for the studied oral bacteria, as well as to validate the combination of GC-MS and PTR-MS for volatile analysis. Some of the most promising compounds produced include: 1-Methyl-1,2,3,4-tetrahydroisoquinoline (1MeTIQ), indole, and a cascade of sulphur compounds, such as methanethiol, dimethyl disulphide (DMDS) and dimethyl trisulphide (DMTS). We also found that several compounds, especially alcohols, aldehydes and esters, fragment significantly with the PTR-MS method, when high E/N values are used. We conclude that the studied oral bacteria can be separated by their volatile fingerprints in vitro, which could have importance in clinical and laboratory environments. In addition, using softer ionization conditions can improve the performance of the PTR-MS method in the volatile analysis of certain compounds.

Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker

In this work, we have designed and simulated a graphene field effect transistor (GFET) with the purpose of developing a sensitive biosensor for methanethiol, a biomarker for bacterial infections. The surface of a graphene layer is functionalized by manipulation of its surface structure and is used as the channel of the GFET. Two methods, doping the crystal structure of graphene and decorating the surface by transition metals (TMs), are utilized to change the electrical properties of the graphene layers to make them suitable as a channel of the GFET. The techniques also change the surface chemistry of the graphene, enhancing its adsorption characteristics and making binding between graphene and biomarker possible. All the physical parameters are calculated for various variants of graphene in the absence and presence of the biomarker using counterpoise energy-corrected density functional theory (DFT). The device was modelled using COMSOL Multiphysics. Our studies show that the sensitivity of the device is affected by structural parameters of the device, the electrical properties of the graphene, and with adsorption of the biomarker. It was found that the devices made of graphene layers decorated with TM show higher sensitivities toward detecting the biomarker compared with those made by doped graphene layers.

Volatilomes of Bacterial Infections in Humans

Sense of smell in humans has the capacity to detect certain volatiles from bacterial infections. Our olfactory senses were used in ancient medicine to diagnose diseases in patients. As humans are considered holobionts, each person's unique odor consists of volatile organic compounds (VOCs, volatilome) produced not only by the humans themselves but also by their beneficial and pathogenic micro-habitants. In the past decade it has been well documented that microorganisms (fungi and bacteria) are able to emit a broad range of olfactory active VOCs [summarized in the mVOC database (http://bioinformatics.charite.de/mvoc/)]. During microbial infection, the equilibrium between the human and its microbiome is altered, followed by a change in the volatilome. For several decades, physicians have been trying to utilize these changes in smell composition to develop fast and efficient diagnostic tools, particularly because volatiles detection is non-invasive and non-destructive, which would be a breakthrough in many therapies. Within this review, we discuss bacterial infections including gastrointestinal, respiratory or lung, and blood infections, focusing on the pathogens and their known corresponding volatile biomarkers. Furthermore, we cover the potential role of the human microbiota and their volatilome in certain diseases such as neurodegenerative diseases. We also report on discrete mVOCs that affect humans.