Volatile Compounds Are Involved in Cellular Crosstalk and Upregulation

Bacterial Volatile Organic Compounds as Potential Caries and Periodontitis Disease Biomarkers

Oral diseases represent a significant global health and economic burden, necessitating the development of effective diagnostic tools. This study investigates the volatile organic compound (VOC) profiles of bacteria associated with dental caries and periodontal disease to explore their potential as diagnostic biomarkers. Four microbial strains-Streptococcus mutans (700610), Streptococcus sanguis (NCO 2863), Porphyromonas gingivalis (ATCC 33277), and Fusobacterium nucleatum (PK1594)-were cultured (N = 24), alongside intraoral samples (N = 60), from individuals with common oral diseases. Headspace VOCs were analyzed using gas chromatography-mass spectrometry (GC-MS), and statistical analyses were conducted by applying non-parametric Wilcoxon and Kruskal-Wallis tests. VOC identification was performed using the NIST14 database. Strain-specific VOC signatures were identified, with P. gingivalis and F. nucleatum exhibiting distinct profiles from each other and from Streptococcus strains. Comparative analysis of disease cohorts revealed statistically significant differences at multiple retention times between caries, gingivitis, and periodontitis. These findings suggest that VOC profiling enables differentiation between bacterial strains and disease phenotypes, supporting their potential application as diagnostic biomarkers for oral diseases. This study establishes a foundational framework for VOC-based diagnostic methodologies in dental pathology.

Non-contact immunological signaling for highly-efficient regulation of the transcriptional map of human monocytes

The different immune system cells communicate and coordinate a response using a complex and evolved language of cytokines and chemokines. These cellular interactions carry out multiple functions in distinct cell types with numerous developmental outcomes. Despite the plethora of different cytokines and their cognate receptors, there is a restricted number of signal transducers and activators to control immune responses. Herein, we report on a new class of immunomodulatory signaling molecules based on volatile molecules (VMs, namely, volatile organic compounds [VOCs]), by which they can affect and/or control immune cell behavior and transcriptomic profile without any physical contact with other cells. The study demonstrates the role of VMs by analyzing non-contact cell communication between normal and cancerous lung cells and U937 monocytes, which are key players in the tumor microenvironment. Integrated transcriptome and proteome analyses showed the suggested regulatory role of VMs released from normal and cancer cells on neighboring monocytes in several molecular pathways, including PI3K/AKT, PPAR, and HIF-1. Presented data provide an initial platform for a new class of immunomodulatory molecules that can potentially mirror the genomic and proteomic profile of cells, thereby paving the way toward non-invasive immunomonitoring.

Noninvasive Pregestational Genetic Testing of Embryos Using Smart Sensors Array

Pregestational genetic testing of embryos is the conventional tool in detecting genetic disorders (fetal aneuploidy and monogenic disorders) for in vitro fertilization (IVF) procedures. The accepted clinical practice for genetic testing still depends on biopsy, which has the potential to harm the embryo. Noninvasive genetic prenatal testing has not yet been achieved. In this study, embryos with common genetic disorders created through IVF were tested with an artificially intelligent nanosensor array. Volatile organic compounds emitted by the culture fluid of embryos were analyzed with chemical gas sensors. The obtained results showed significant discrimination between the embryos with different genetic diseases and their wild-types. Embryos were obtained from the same clinical center for avoiding differences based on clinical and demographical characteristics. The achieved discrimination accuracy was 81% for PKD disease, 90% for FRAX disease, 85% for HOCM disease, 90% for BRCA disease, and 100% for HSCR disease. These proof-of-concept findings might launch the development of a noninvasive approach for early assessment of embryos by examining the culture fluid of the embryos, potentially enabling noninvasive diagnosis and screening of genetic diseases for IVF.

Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers

Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi-sensitive nano-based structured films is developed and used to detect and stage cancer. As a proof-of-concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease-monitoring tool for cancer.

Non-Invasive Staging of In Vitro Mice Embryos by Means of Volatolomics

Current methods for embryo selection are limited. This study assessed a novel method for the prediction of embryo developmental potential based on the analysis of volatile organic compounds (VOCs) emitted by embryo samples. The study included mice embryos monitored during the pre-implantation period. Four developmental stages of the embryos were tested, covering the period from 1 to 4 days after fecundation. In each stage, the VOCs released by the embryos were collected and examined by employing two different volatolomic techniques, gas-chromatography coupled to mass-spectrometry (GC-MS) and a nanoarray of chemical gas sensors. The GC-MS study revealed that the VOC patterns emanating from embryo samples had statistically different values at different stages of embryo development. The sensor nanoarray was capable of classifying the developmental stages of the embryos. The proposed volatolomics analysis approach for embryos presents a promising potential for predicting their developmental stage. In combination with conventional morphokinetic parameters, it could be effective as a predictive model for detecting metabolic shifts that affect embryo quality before preimplantation.

Targeted volatolomics of human monocytes: Comparison of 2D-GC/TOF-MS and 1D-GC/Orbitrap-MS methods

Blood is a complex biological matrix providing valuable information on nutritional, metabolic, and immune status. The detection of blood biomarkers requires sensitive analytical methods because analytes are at very low concentrations. Peripheral blood monocytes play a crucial role in inflammatory processes, and the metabolites released by monocytes during these processes might serve as important signalling molecules and biomarkers of particular physiological states. Headspace solid-phase microextraction (HS-SPME) combined with two different mass spectrometric platforms, two-dimensional (2D) gas chromatography coupled to time-of-flight mass spectrometry (2D-GC/TOF-MS) and one-dimensional gas chromatography coupled to Orbitrap mass spectrometry (GC/Orbitrap-MS), were applied for the investigation of volatile organic compounds (VOCs) produced by human peripheral blood monocytes. An optimized method was subsequently applied for the characterization of changes in VOCs induced by lipopolysaccharides (LPS) and zymosan (ZYM) stimulation. Overall, the 2D-GC/TOF-MS and the 1D-GC/Orbitrap-MS analyses each yielded about 4000 and 400 peaks per sample, respectively. In total, 91 VOCs belonging to eight different chemical classes were identified. The samples were collected in two fractions, conditioned media for monitoring extracellularly secreted molecules and cell pellet samples to determine the intracellular composition of VOCs. Alcohols, ketones, and hydrocarbons were the main chemical classes of the metabolic profile identified in cell fractions. Aldehydes, acids and cyclic compounds were characteristic of the conditioned media fraction. Here we demonstrate that HS-SPME-2D-GC/TOF-MS is more suitable for the identification of specific VOC profiles produced by human monocytes than 1D-GC/Orbitrap-MS. We define the signature of VOCs occurring early after monocyte activation and characterise the signalling compounds released by immune cells into media.

An Update on the Use of Exhaled Breath Analysis for the Early Detection of Lung Cancer

Lung cancer has historically been the main responsible for cancer associated deaths. Owing to this is our current inability to screen for and diagnose early pathological findings, preventing us from a timely intervention when cure is still achievable. Over the last decade, together with the extraordinary progress in therapeutical alternatives in the field, there has been an ongoing search for a biomarker that would allow for this. Numerous technologies have been developed but their clinical application is yet to come. In this review, we provide an update on volatile organic compounds, a non-invasive method that can hold the key for detecting early metabolic pathway changes in carcinogenesis. For its compilation, web-based search engines of scientific literature such as PubMed were explored and reviewed, using articles, research, and papers deemed meaningful by authors discretion. After a brief description, we depict how this technique can complement current methods and present the value of electronic noses in the identification of the “breathprint”. Lastly, we bring some of the latest updates in the field together with the current limitations and final remarks.

Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test.