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Parnas M, McLane-Svoboda AK, Cox E, McLane-Svoboda SB, Sanchez SW, Farnum A, Tundo A, Lefevre N, Miller S, Neeb E, Contag CH, Saha D. Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor. Biosens Bioelectron 2024; 261:116466. [PMID: 38850736 DOI: 10.1016/j.bios.2024.116466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 05/24/2024] [Accepted: 06/02/2024] [Indexed: 06/10/2024]
Abstract
Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.
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Affiliation(s)
- Michael Parnas
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Autumn K McLane-Svoboda
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Elyssa Cox
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Summer B McLane-Svoboda
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Simon W Sanchez
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Alexander Farnum
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Anthony Tundo
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Noël Lefevre
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Sydney Miller
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Emily Neeb
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Christopher H Contag
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Microbiology, Genetics & Immunology, Michigan State University, East Lansing, MI, USA
| | - Debajit Saha
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Neuroscience Program, Michigan State University, East Lansing, MI, USA.
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Wang Y, Tang Z, Zhao T, Yang J, Zhang W, Li X, Huan T. BreathXplorer: Processing Online Breathomics Data Generated from Direct Analysis Using High-Resolution Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1818-1825. [PMID: 39052287 DOI: 10.1021/jasms.4c00152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
Nontargeted breath analysis in real time using high-resolution mass spectrometry (HRMS) is a promising approach for high coverage profiling of metabolites in human exhaled breath. However, the information-rich and unique non-Gaussian metabolic signal shapes of real-time HRMS-based data pose a significant challenge for efficient data processing. This work takes a typical real-time HRMS technique as an example, i.e. secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), and presents BreathXplorer, an open-source Python package designed for the processing of real-time exhaled breath data comprising multiple exhalations. BreathXplorer is composed of four main modules. The first module applies either a topological algorithm or a Gaussian mixture model (GMM) to determine the start and end points of each exhalation. Next, density-based spatial clustering of applications with noise (DBSCAN) is employed to cluster m/z values belonging to the same metabolic feature, followed by applying an intensity relative standard deviation (RSD) filter to extract real breath metabolic features. BreathXplorer also offers functions of (1) feature alignment across the samples and (2) associating MS/MS spectra with their corresponding metabolic features for downstream compound annotation. Manual inspection of the metabolic features extracted from SESI-HRMS breath data suggests that BreathXplorer can achieve 100% accuracy in identifying the start and end points of each exhalation and acquire accurate quantitative measurements of each breath feature. In a proof-of-concept study on exercise breathomics using SESI-HRMS, BreathXplorer successfully reveals the significantly changed metabolites that are pertinent to exercise. BreathXplorer is publicly available on GitHub (https://github.com/HuanLab/breathXplorer). It provides a powerful and convenient-to-use tool for the researchers to process breathomics data obtained by directly analysis using HRMS.
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Affiliation(s)
- Yukai Wang
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
| | - Zhifeng Tang
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Key Laboratory of Speed Capability Research, Jinan University, Guangzhou 510632, China
| | - Tingting Zhao
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
| | - Jianming Yang
- Guangdong Provincial Key Laboratory of Speed Capability Research; Su Bingtian Center for Speed Research and Training; School of Physical Education, Jinan University, Guangzhou 510632, China
| | - Wei Zhang
- Guangdong A-HealthX Technologies Co., Ltd, Dongguan 523830, China
| | - Xue Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Key Laboratory of Speed Capability Research, Jinan University, Guangzhou 510632, China
| | - Tao Huan
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
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Pangerl J, Sukul P, Rück T, Fuchs P, Weigl S, Miekisch W, Bierl R, Matysik FM. An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone. PHOTOACOUSTICS 2024; 38:100604. [PMID: 38559568 PMCID: PMC10973644 DOI: 10.1016/j.pacs.2024.100604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/08/2024] [Accepted: 03/20/2024] [Indexed: 04/04/2024]
Abstract
In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.
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Affiliation(s)
- Jonas Pangerl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany
- Institute of Analytical Chemistry, Chemo- and Biosensing, University of Regensburg, Regensburg 93053, Germany
| | - Pritam Sukul
- Rostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany
| | - Thomas Rück
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany
| | - Patricia Fuchs
- Rostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany
| | - Stefan Weigl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany
| | - Wolfram Miekisch
- Rostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany
| | - Rudolf Bierl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany
| | - Frank-Michael Matysik
- Institute of Analytical Chemistry, Chemo- and Biosensing, University of Regensburg, Regensburg 93053, Germany
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Kim KB, Sohn MS, Min S, Yoon JW, Park JS, Li J, Moon YK, Kang YC. Highly Selective and Reversible Detection of Simulated Breath Hydrogen Sulfide Using Fe-Doped CuO Hollow Spheres: Enhanced Surface Redox Reaction by Multi-Valent Catalysts. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2308963. [PMID: 38461524 DOI: 10.1002/smll.202308963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/19/2024] [Indexed: 03/12/2024]
Abstract
The precise and reversible detection of hydrogen sulfide (H2S) at high humidity condition, a malodorous and harmful volatile sulfur compound, is essential for the self-assessment of oral diseases, halitosis, and asthma. However, the selective and reversible detection of trace concentrations of H2S (≈0.1 ppm) in high humidity conditions (exhaled breath) is challenging because of irreversible H2S adsorption/desorption at the surface of chemiresistors. The study reports the synthesis of Fe-doped CuO hollow spheres as H2S gas-sensing materials via spray pyrolysis. 4 at.% of Fe-doped CuO hollow spheres exhibit high selectivity (response ratio ≥ 34.4) over interference gas (ethanol, 1 ppm) and reversible sensing characteristics (100% recovery) to 0.1 ppm of H2S under high humidity (relative humidity 80%) at 175 °C. The effect of multi-valent transition metal ion doping into CuO on sensor reversibility is confirmed through the enhancement of recovery kinetics by doping 4 at.% of Ti- or Nb ions into CuO sensors. Mechanistic details of these excellent H2S sensing characteristics are also investigated by analyzing the redox reactions and the catalytic activity change of the Fe-doped CuO sensing materials. The selective and reversible detection of H2S using the Fe-doped CuO sensor suggested in this work opens a new possibility for halitosis self-monitoring.
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Affiliation(s)
- Ki Beom Kim
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Myung Sung Sohn
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Sunhong Min
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Ji-Wook Yoon
- Department of Information Materials Engineering, Division of Advanced Materials Engineering, Jeonbuk National University, Jeonju, 54896, Republic of Korea
| | - Jin-Sung Park
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Ju Li
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Young Kook Moon
- Department of Functional Ceramics, Ceramic Materials Division, Korea Institute of Materials Science (KIMS), Changwon, 51508, Republic of Korea
| | - Yun Chan Kang
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
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Yang T, Li Z, Chen S, Lan T, Lu Z, Fang L, Zhao H, Li Q, Luo Y, Yang B, Shu J. Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms. JOURNAL OF HAZARDOUS MATERIALS 2024; 470:134151. [PMID: 38554517 DOI: 10.1016/j.jhazmat.2024.134151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/01/2024]
Abstract
Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent attention from researchers, the link between exhaled breath and ozone-induced injury remains poorly understood. This study aimed to identify novel exhaled biomarkers in ozone-exposed mice using ultra-sensitive photoinduced associative ionization time-of-flight mass spectrometry and machine learning. Distinct ion peaks for acetonitrile (m/z 42, 60, and 78), butyronitrile (m/z 70, 88, and 106), and hydrogen sulfide (m/z 35) were detected. Integration of tissue characteristics, oxidative stress-related mRNA expression, and exhaled breath condensate free-radical analysis enabled a comprehensive exploration of the relationship between ozone-induced biological responses and potential biomarkers. Under similar exposure levels, C57BL/6 mice exhibited pulmonary injury characterized by significant inflammation, oxidative stress, and cardiac damage. Notably, C57BL/6 mice showed free radical signals, indicating a distinct susceptibility profile. Immunodeficient non-obese diabetic Prkdc-/-/Il2rg-/- (NPI) mice exhibited minimal biological responses to pulmonary injury, with little impact on the heart. These findings suggest a divergence in ozone-induced damage pathways in the two mouse types, leading to alterations in exhaled biomarkers. Integrating biomarker discovery with comprehensive biopathological analysis forms a robust foundation for targeted interventions to manage health risks posed by ozone exposure.
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Affiliation(s)
- Teng Yang
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen Li
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China; Binzhou Institute of Technology, Weiqiao-UCAS Science and Technology Park, Binzhou, Shandong Province 256606, China.
| | - Siwei Chen
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ting Lan
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhongbing Lu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Longfa Fang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems. Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020 China
| | - Huan Zhao
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qirun Li
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinwei Luo
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China; Binzhou Institute of Technology, Weiqiao-UCAS Science and Technology Park, Binzhou, Shandong Province 256606, China
| | - Bo Yang
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinian Shu
- National Engineering Laboratory for VOCs Pollution Control Material & Technology, University of Chinese Academy of Sciences, Beijing 100049, China
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Karunanethy M, Tripathi R, Panchagnula MV, Rengaswamy R. User authentication system based on human exhaled breath physics. PLoS One 2024; 19:e0301971. [PMID: 38648227 PMCID: PMC11034670 DOI: 10.1371/journal.pone.0301971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
This work, in a pioneering approach, attempts to build a biometric system that works purely based on the fluid mechanics governing exhaled breath. We test the hypothesis that the structure of turbulence in exhaled human breath can be exploited to build biometric algorithms. This work relies on the idea that the extrathoracic airway is unique for every individual, making the exhaled breath a biomarker. Methods including classical multi-dimensional hypothesis testing approach and machine learning models are employed in building user authentication algorithms, namely user confirmation and user identification. A user confirmation algorithm tries to verify whether a user is the person they claim to be. A user identification algorithm tries to identify a user's identity with no prior information available. A dataset of exhaled breath time series samples from 94 human subjects was used to evaluate the performance of these algorithms. The user confirmation algorithms performed exceedingly well for the given dataset with over 97% true confirmation rate. The machine learning based algorithm achieved a good true confirmation rate, reiterating our understanding of why machine learning based algorithms typically outperform classical hypothesis test based algorithms. The user identification algorithm performs reasonably well with the provided dataset with over 50% of the users identified as being within two possible suspects. We show surprisingly unique turbulent signatures in the exhaled breath that have not been discovered before. In addition to discussions on a novel biometric system, we make arguments to utilise this idea as a tool to gain insights into the morphometric variation of extrathoracic airway across individuals. Such tools are expected to have future potential in the area of personalised medicines.
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Affiliation(s)
- Mukesh Karunanethy
- Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Rahul Tripathi
- Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Mahesh V. Panchagnula
- Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Raghunathan Rengaswamy
- Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
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Saeki Y, Maki N, Nemoto T, Inada K, Minami K, Tamura R, Imamura G, Cho-Isoda Y, Kitazawa S, Kojima H, Yoshikawa G, Sato Y. Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array. Lung Cancer 2024; 190:107514. [PMID: 38447302 DOI: 10.1016/j.lungcan.2024.107514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 02/12/2024] [Accepted: 02/24/2024] [Indexed: 03/08/2024]
Abstract
INTRODUCTION Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning. METHODS Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning. RESULTS Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively. CONCLUSION Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.
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Affiliation(s)
- Yusuke Saeki
- Department of Thoracic Surgery, University of Tsukuba, Ibaraki, Japan
| | - Naoki Maki
- Department of Thoracic Surgery, University of Tsukuba, Ibaraki, Japan
| | - Takahiro Nemoto
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), Ibaraki, Japan; Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Ibaraki, Japan
| | - Katsushige Inada
- Department of Medical Oncology, Ibaraki Prefectural Central Hospital, Ibaraki, Japan
| | - Kosuke Minami
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), Ibaraki, Japan; Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Ibaraki, Japan; International Center for Young Scientists (ICYS), National Institute for Materials Science (NIMS), Ibaraki, Japan
| | - Ryo Tamura
- World Premier International (WPI) Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Ibaraki, Japan; Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan; Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science (NIMS), Ibaraki, Japan; Center for Basic Research on Materials, National Institute for Materials Science (NIMS), Ibaraki, Japan
| | - Gaku Imamura
- Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Ibaraki, Japan; World Premier International (WPI) Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Ibaraki, Japan; Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
| | - Yukiko Cho-Isoda
- Department of Medical Oncology, Ibaraki Prefectural Central Hospital, Ibaraki, Japan
| | - Shinsuke Kitazawa
- Department of Thoracic Surgery, University of Tsukuba, Ibaraki, Japan
| | - Hiroshi Kojima
- Department of Medical Oncology, Ibaraki Prefectural Central Hospital, Ibaraki, Japan; Ibaraki Clinical Education and Training Center, University of Tsukuba Hospital, Ibaraki, Japan
| | - Genki Yoshikawa
- Center for Functional Sensor & Actuator (CFSN), Research Center for Functional Materials, National Institute for Materials Science (NIMS), Ibaraki, Japan; Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Ibaraki, Japan; Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, Ibaraki, Japan
| | - Yukio Sato
- Department of Thoracic Surgery, University of Tsukuba, Ibaraki, Japan.
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8
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Shi Y, Fang J. Directly Self-Assembly of Aligned Ag NWs Films at the Air-Water Interface for the Detection of Pathogens in Artificial Breath Aerosols. Anal Chem 2024; 96:2474-2480. [PMID: 38294198 DOI: 10.1021/acs.analchem.3c04475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Exhaled aerosols from humans, containing various pathogens, are crucial for early disease diagnosis. However, the traditional pathogen detection methods, such as polymerase chain reaction, are often slow and cumbersome due to complex sampling and procedures. This study introduces a novel, direct, and label-free detection method for pathogens in respiratory aerosols, utilizing a highly aligned silver nanowire (Ag NW) film combined with a filter membrane (Ag NWs@filter) as a surface-enhanced Raman spectroscopy-active substrate. A large-scale, ordered silver nanowire film was developed through a simplified self-assembly process. This process eliminates the need for an organic phase and complex surface modifications of Ag NWs, which are common in other preparation methods. Subsequently, the fabricated Ag NWs@filter demonstrated its capability to continuously capture and efficiently preconcentrate pathogens from aerosols, achieving a remarkable detection limit of 3 × 103 CFU/mL, demonstrated using Escherichia coli (E. coli) as a model pathogen. Moreover, the classification between E. coli and Pseudomonas aeruginosa achieved an overall accuracy of 96.5% by the principal component analysis with linear discriminant analysis models. The success of this sensing strategy illustrates its potential in detecting and identifying a variety of biomarkers present in respiratory aerosols, marking a significant step forward in the field of pathogen detection.
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Affiliation(s)
- Yafei Shi
- China Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- School of Electronics Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Jixiang Fang
- China Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
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9
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Khokhar M. Non-invasive detection of renal disease biomarkers through breath analysis. J Breath Res 2024; 18:024001. [PMID: 38099568 DOI: 10.1088/1752-7163/ad15fb] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 12/14/2023] [Indexed: 01/06/2024]
Abstract
Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry (MS), gas chromatography (GC), and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.
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Affiliation(s)
- Manoj Khokhar
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
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Marzoog B. Breathomics Detect the Cardiovascular Disease: Delusion or Dilution of the Metabolomic Signature. Curr Cardiol Rev 2024; 20:68-76. [PMID: 38318837 PMCID: PMC11327829 DOI: 10.2174/011573403x283768240124065853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/04/2024] [Accepted: 01/15/2024] [Indexed: 02/07/2024] Open
Abstract
Volatile organic compounds (VOCs) can be subdivided into exogenous and endogenous categories based on their origin. Analyzing the endogenous VOCs can provide insights into maintaining the internal organs' homeostasis. Despite the ongoing development and the current understanding, studies have suggested a link between cardiovascular metabolic alterations in patients with ischemic heart disease and elevated levels of ethane and isoprene detectable through exhaled breath analysis. Conversely, patients with chronic heart failure exhibit elevated acetone and pentane in their exhaled air. These substances originate from disturbances in the heart tissue, including cellular and subcellular modulations. Hypothetically, ethane levels in the exhaled breath analysis can demonstrate the severity of ischemic heart disease and, consequently, the risk of death in the next 10 years due to cardiovascular disease (CVD). Real-time direct mass spectrometry is the preferred method for assessing VOCs in exhaled breath analysis. The accuracy of this analysis depends on several factors, including the selection of the relevant breath fraction, the type of breath collection container (if used), and the pre-concentration technique.
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Affiliation(s)
- Basheer Marzoog
- World-Class Research Center, Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
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11
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Sola-Martínez RA, Zeng J, Awchi M, Gisler A, Arnold K, Singh KD, Frey U, Díaz MC, de Diego Puente T, Sinues P. Preservation of exhaled breath samples for analysis by off-line SESI-HRMS: proof-of-concept study. J Breath Res 2023; 18:011002. [PMID: 38029449 DOI: 10.1088/1752-7163/ad10e1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/29/2023] [Indexed: 12/01/2023]
Abstract
Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of allm/zsignals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.
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Affiliation(s)
- Rosa A Sola-Martínez
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Jiafa Zeng
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Mo Awchi
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Amanda Gisler
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
| | - Kim Arnold
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Kapil Dev Singh
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Urs Frey
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Pediatric Respiratory Medicine, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Manuel Cánovas Díaz
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Teresa de Diego Puente
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Pablo Sinues
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
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12
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Ain Nazir NU, Shaukat MH, Luo R, Abbas SR. Novel breath biomarkers identification for early detection of hepatocellular carcinoma and cirrhosis using ML tools and GCMS. PLoS One 2023; 18:e0287465. [PMID: 37967076 PMCID: PMC10651033 DOI: 10.1371/journal.pone.0287465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 06/06/2023] [Indexed: 11/17/2023] Open
Abstract
According to WHO 2019, Hepatocellular carcinoma (HCC) is the fourth highest cause of cancer death worldwide. More precise diagnostic models are needed to enhance early HCC and cirrhosis quick diagnosis, treatment, and survival. Breath biomarkers known as volatile organic compounds (VOCs) in exhaled air can be used to make rapid, precise, and painless diagnoses. Gas chromatography and mass spectrometry (GCMS) are utilized to diagnose HCC and cirrhosis VOCs. In this investigation, metabolically generated VOCs in breath samples (n = 35) of HCC, (n = 35) cirrhotic, and (n = 30) controls were detected via GCMS and SPME. Moreover, this study also aims to identify diagnostic VOCs for distinction among HCC and cirrhosis liver conditions, which are most closely related, and cause misleading during diagnosis. However, using gas chromatography-mass spectrometry (GC-MS) to quantify volatile organic compounds (VOCs) is time-consuming and error-prone since it requires an expert. To verify GC-MS data analysis, we present an in-house R-based array of machine learning models that applies deep learning pattern recognition to automatically discover VOCs from raw data, without human intervention. All-machine learning diagnostic model offers 80% sensitivity, 90% specificity, and 95% accuracy, with an AUC of 0.9586. Our results demonstrated the validity and utility of GCMS-SMPE in combination with innovative ML models for early detection of HCC and cirrhosis-specific VOCs considered as potential diagnostic breath biomarkers and showed differentiation among HCC and cirrhosis. With these useful insights, we can build handheld e-nose sensors to detect HCC and cirrhosis through breath analysis and this unique approach can help in diagnosis by reducing integration time and costs without compromising accuracy or consistency.
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Affiliation(s)
- Noor ul Ain Nazir
- Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology (NUST), Islamabad, Pakistan
- Department of Electrical Engineering and Computer Science, The Henry Samueli School of Engineering, University of California, Irvine, Irvine, CA, United States of America
| | | | - Ray Luo
- Departments of Chemical and Biomolecular Engineering, Materials Science and Engineering and Biomedical Engineering, the University of California, Irvine, Irvine, CA, United States of America
- Department of Molecular Biology and Biochemistry, School of Biological Sciences, University of California, Irvine, Irvine, CA, United States of America
| | - Shah Rukh Abbas
- Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology (NUST), Islamabad, Pakistan
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13
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Banga I, Paul A, Poudyal DC, Muthukumar S, Prasad S. Recent Advances in Gas Detection Methodologies with a Special Focus on Environmental Sensing and Health Monitoring Applications─A Critical Review. ACS Sens 2023; 8:3307-3319. [PMID: 37540230 DOI: 10.1021/acssensors.3c00959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
With the expansion of the Internet-of-Things (IoT), the use of gas sensors in the field of wearable technology, smart devices, and smart homes has increased manifold. These gas sensors have two key applications─one is the detection of gases present in the environment and the other is the detection of Volatile Organic Compounds (VOCs) that are found in the breath. In this review, we focus systematically on the advancements in the field of various spectroscopic methods such as mass spectrometry-based analysis and point-of-care approach to detect VOCs and gases for environmental monitoring and disease diagnosis. Additionally, we highlight the development of smart sensors that work on the principle of electrochemical detection and provide examples of the same through an extensive literature review. At the end of this review, we highlight various challenges and future perspectives.
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Affiliation(s)
- Ivneet Banga
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States
| | - Anirban Paul
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States
| | - Durgasha C Poudyal
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States
| | - Sriram Muthukumar
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States
- EnLiSense LLC, 1813 Audubon Pondway, Allen, Texas 75013, United States
| | - Shalini Prasad
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States
- EnLiSense LLC, 1813 Audubon Pondway, Allen, Texas 75013, United States
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14
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Savito L, Scarlata S, Bikov A, Carratù P, Carpagnano GE, Dragonieri S. Exhaled volatile organic compounds for diagnosis and monitoring of asthma. World J Clin Cases 2023; 11:4996-5013. [PMID: 37583852 PMCID: PMC10424019 DOI: 10.12998/wjcc.v11.i21.4996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/08/2023] [Accepted: 07/06/2023] [Indexed: 07/26/2023] Open
Abstract
The asthmatic inflammatory process results in the generation of volatile organic compounds (VOCs), which are subsequently secreted by the airways. The study of these elements through gas chromatography-mass spectrometry (GC-MS), which can identify individual molecules with a discriminatory capacity of over 85%, and electronic-Nose (e-NOSE), which is able to perform a quick onboard pattern-recognition analysis of VOCs, has allowed new prospects for non-invasive analysis of the disease in an "omics" approach. In this review, we aim to collect and compare the progress made in VOCs analysis using the two methods and their instrumental characteristics. Studies have described the potential of GC-MS and e-NOSE in a multitude of relevant aspects of the disease in both children and adults, as well as differential diagnosis between asthma and other conditions such as wheezing, cystic fibrosis, COPD, allergic rhinitis and last but not least, the accuracy of these methods compared to other diagnostic tools such as lung function, FeNO and eosinophil count. Due to significant limitations of both methods, it is still necessary to improve and standardize techniques. Currently, e-NOSE appears to be the most promising aid in clinical practice, whereas GC-MS, as the gold standard for the structural analysis of molecules, remains an essential tool in terms of research for further studies on the pathophysiologic pathways of the asthmatic inflammatory process. In conclusion, the study of VOCs through GC-MS and e-NOSE appears to hold promise for the non-invasive diagnosis, assessment, and monitoring of asthma, as well as for further research studies on the disease.
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Affiliation(s)
- Luisa Savito
- Department of Internal Medicine, Unit of Respiratory Pathophysiology and Thoracic Endoscopy, Fondazione Policlinico Universitario Campus Bio Medico, Rome 00128, Italy
| | - Simone Scarlata
- Department of Internal Medicine, Unit of Respiratory Pathophysiology and Thoracic Endoscopy, Fondazione Policlinico Universitario Campus Bio Medico, Rome 00128, Italy
| | - Andras Bikov
- Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, United Kingdom
- Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Pierluigi Carratù
- Department of Internal Medicine "A.Murri", University of Bari "Aldo Moro", Bari 70124, Italy
| | | | - Silvano Dragonieri
- Department of Respiratory Diseases, University of Bari, Bari 70124, Italy
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15
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Riccio G, Berenguer CV, Perestrelo R, Pereira F, Berenguer P, Ornelas CP, Sousa AC, Vital JA, Pinto MDC, Pereira JAM, Greco V, Câmara JS. Differences in the Volatilomic Urinary Biosignature of Prostate Cancer Patients as a Feasibility Study for the Detection of Potential Biomarkers. Curr Oncol 2023; 30:4904-4921. [PMID: 37232828 DOI: 10.3390/curroncol30050370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/18/2023] [Accepted: 04/25/2023] [Indexed: 05/27/2023] Open
Abstract
Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed.
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Affiliation(s)
- Giulia Riccio
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Univesità Cattolica del Sacro Cuore, 00168 Rome, Italy
- Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Cristina V Berenguer
- CQM-Centro de Química da Madeira, NPRG, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
| | - Rosa Perestrelo
- CQM-Centro de Química da Madeira, NPRG, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
| | - Ferdinando Pereira
- Serviço de Urologia, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM-Serviço de Saúde da Região Autónoma da Madeira, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
| | - Pedro Berenguer
- Centro de Investigação Dra Maria Isabel Mendonça, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
- RO-RAM-Registo Oncológico da Região Autónoma da Madeira, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
| | - Cristina P Ornelas
- Centro de Saúde do Bom Jesus, SESARAM, EPERAM, Rua das Hortas, nº67, 9050-024 Funchal, Portugal
| | - Ana Célia Sousa
- Centro de Investigação Dra Maria Isabel Mendonça, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
| | - João Aragão Vital
- Serviço de Urologia, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM-Serviço de Saúde da Região Autónoma da Madeira, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
| | - Maria do Carmo Pinto
- Serviço de Urologia, Hospital Dr. Nélio Mendonça, SESARAM, EPERAM-Serviço de Saúde da Região Autónoma da Madeira, Avenida Luís de Camões, nº57, 9004-514 Funchal, Portugal
| | - Jorge A M Pereira
- CQM-Centro de Química da Madeira, NPRG, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
| | - Viviana Greco
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Univesità Cattolica del Sacro Cuore, 00168 Rome, Italy
- Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - José S Câmara
- CQM-Centro de Química da Madeira, NPRG, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
- Departamento de Química, Faculdade de Ciências Exatas e Engenharia, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
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16
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Bhandari MP, Polaka I, Vangravs R, Mezmale L, Veliks V, Kirshners A, Mochalski P, Dias-Neto E, Leja M. Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota? Molecules 2023; 28:molecules28083488. [PMID: 37110724 PMCID: PMC10141340 DOI: 10.3390/molecules28083488] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 04/11/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
It has been shown that the gut microbiota plays a central role in human health and disease. A wide range of volatile metabolites present in exhaled breath have been linked with gut microbiota and proposed as a non-invasive marker for monitoring pathological conditions. The aim of this study was to examine the possible correlation between volatile organic compounds (VOCs) in exhaled breath and the fecal microbiome by multivariate statistical analysis in gastric cancer patients (n = 16) and healthy controls (n = 33). Shotgun metagenomic sequencing was used to characterize the fecal microbiota. Breath-VOC profiles in the same participants were identified by an untargeted gas chromatography-mass spectrometry (GC-MS) technique. A multivariate statistical approach involving a canonical correlation analysis (CCA) and sparse principal component analysis identified the significant relationship between the breath VOCs and fecal microbiota. This relation was found to differ between gastric cancer patients and healthy controls. In 16 cancer cases, 14 distinct metabolites identified from the breath belonging to hydrocarbons, alcohols, aromatics, ketones, ethers, and organosulfur compounds were highly correlated with 33 fecal bacterial taxa (correlation of 0.891, p-value 0.045), whereas in 33 healthy controls, 7 volatile metabolites belonging to alcohols, aldehydes, esters, phenols, and benzamide derivatives correlated with 17 bacterial taxa (correlation of 0.871, p-value 0.0007). This study suggested that the correlation between fecal microbiota and breath VOCs was effective in identifying exhaled volatile metabolites and the functional effects of microbiome, thus helping to understand cancer-related changes and improving the survival and life expectancy in gastric cancer patients.
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Affiliation(s)
| | - Inese Polaka
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
| | - Reinis Vangravs
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
| | - Linda Mezmale
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
- Riga East University Hospital, LV-1038 Riga, Latvia
- Faculty of Residency, Riga Stradins University, LV-1007 Riga, Latvia
| | - Viktors Veliks
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
| | - Arnis Kirshners
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
| | - Pawel Mochalski
- Institute of Chemistry, Jan Kochanowski University of Kielce, PL-25406 Kielce, Poland
- Institute for Breath Research, University of Innsbruck, A-6850 Dornbirn, Austria
| | - Emmanuel Dias-Neto
- Laboratory of Medical Genomics, A.C.Camargo Cancer Center, Sao Paulo 01508-010, Brazil
| | - Marcis Leja
- Institute of Clinical and Preventive Medicine, University of Latvia, LV-1586 Riga, Latvia
- Digestive Diseases Center GASTRO, LV-1079 Riga, Latvia
- Faculty of Medicine, University of Latvia, LV-1586 Riga, Latvia
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17
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Pangerl J, Moser E, Müller M, Weigl S, Jobst S, Rück T, Bierl R, Matysik FM. A sub-ppbv-level Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor - Characterization and Multi-Component Spectra Recording in Synthetic Breath. PHOTOACOUSTICS 2023; 30:100473. [PMID: 36970564 PMCID: PMC10033733 DOI: 10.1016/j.pacs.2023.100473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 02/24/2023] [Accepted: 03/09/2023] [Indexed: 06/18/2023]
Abstract
Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8263 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbv in terms of ethanol and 250 pptv regarding acetone, our system is among the best performing presented so far.
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Affiliation(s)
- Jonas Pangerl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
- Institute of Analytical Chemistry, Chemo, and Biosensors, University of Regensburg, 93053 Regensburg, Germany
| | - Elisabeth Moser
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
- Faculty of Informatics, Technical University of Munich, 85748 Garching, Germany
| | - Max Müller
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
- Institute of Analytical Chemistry, Chemo, and Biosensors, University of Regensburg, 93053 Regensburg, Germany
| | - Stefan Weigl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
| | - Simon Jobst
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
- Institute of Analytical Chemistry, Chemo, and Biosensors, University of Regensburg, 93053 Regensburg, Germany
| | - Thomas Rück
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
| | - Rudolf Bierl
- Sensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, 93053 Regensburg, Germany
| | - Frank-Michael Matysik
- Institute of Analytical Chemistry, Chemo, and Biosensors, University of Regensburg, 93053 Regensburg, Germany
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18
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Nakano-Baker O, Fong H, Shukla S, Lee RV, Cai L, Godin D, Hennig T, Rath S, Novosselov I, Dogan S, Sarikaya M, MacKenzie JD. Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19. Biosens Bioelectron 2023; 229:115237. [PMID: 36965380 PMCID: PMC10027305 DOI: 10.1016/j.bios.2023.115237] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 02/25/2023] [Accepted: 03/16/2023] [Indexed: 03/25/2023]
Abstract
Exhaled human breath contains a rich mixture of volatile organic compounds (VOCs) whose concentration can vary in response to disease or other stressors. Using simulated odorant-binding proteins (OBPs) and machine learning methods, we designed a multiplex of short VOC- and carbon-binding peptide probes that detect a characteristic "VOC fingerprint". Specifically, we target VOCs associated with COVID-19 in a compact, molecular sensor array that directly transduces vapor composition into multi-channel electrical signals. Rapidly synthesizable, chimeric VOC- and solid-binding peptides were derived from selected OBPs using multi-sequence alignment with protein database structures. Selective peptide binding to targeted VOCs and sensor surfaces was validated using surface plasmon resonance spectroscopy and quartz crystal microbalance. VOC sensing was demonstrated by peptide-sensitized, exposed-channel carbon nanotube transistors. The data-to-device pipeline enables the development of novel devices for non-invasive monitoring, diagnostics of diseases, and environmental exposure assessment.
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Affiliation(s)
| | - Hanson Fong
- University of Washington Dept. of Materials Science and Engineering, USA
| | | | - Richard V Lee
- University of Washington Dept. of Materials Science and Engineering, USA
| | - Le Cai
- University of Washington Dept. of Materials Science and Engineering, USA
| | - Dennis Godin
- University of Washington Dept. of Biochemistry, USA
| | - Tatum Hennig
- University of Washington Dept. of Atmospheric Chemistry, USA
| | - Siddharth Rath
- University of Washington Dept. of Materials Science and Engineering, USA
| | - Igor Novosselov
- University of Washington Depts. of Mechanical Engineering, Occupational and Environmental Health Sciences, USA
| | - Sami Dogan
- University of Washington School of Dentistry, USA
| | - Mehmet Sarikaya
- University of Washington Depts. of Materials Science and Engineering, Chemical Engineering, Oral Health Sciences, USA
| | - J Devin MacKenzie
- University of Washington Depts. of Materials Science and Engineering, Mechanical Engineering, USA
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19
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Awchi M, Sinues P, Datta AN, García-Gómez D, Singh KD. UHPLC-MS/MS-Based Identity Confirmation of Amino Acids Involved in Response to and Side Effects from Antiseizure Medications. J Proteome Res 2023; 22:990-995. [PMID: 36812155 PMCID: PMC9990125 DOI: 10.1021/acs.jproteome.2c00835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Real-time breath analysis using secondary electrospray ionization coupled with high-resolution mass spectrometry is a fast and noninvasive method to access the metabolic state of a person. However, it lacks the ability to unequivocally assign mass spectral features to compounds due to the absence of chromatographic separation. This can be overcomed by using exhaled breath condensate and conventional liquid chromatography-mass spectrometry (LC-MS) systems. In this study, to the best of our knowledge, we confirm for the first time the presence of six amino acids (GABA, Oxo-Pro, Asp, Gln, Glu, and Tyr) previously reported to be involved in response to and side effects from antiseizure medications in exhaled breath condensate and by extension in exhaled human breath. Raw data are publicly available at MetaboLights with the accession number MTBLS6760.
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Affiliation(s)
- Mo Awchi
- University Children's Hospital Basel, University of Basel, Spitalstrasse 33, 4056 Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Gewerbestrasse 14, 4123 Allschwil, Switzerland
| | - Pablo Sinues
- University Children's Hospital Basel, University of Basel, Spitalstrasse 33, 4056 Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Gewerbestrasse 14, 4123 Allschwil, Switzerland
| | - Alexandre N Datta
- University Children's Hospital Basel, University of Basel, Spitalstrasse 33, 4056 Basel, Switzerland
| | - Diego García-Gómez
- Department of Analytical Chemistry, University of Salamanca, Plaza de los Caídos s/n, 37008 Salamanca, Spain
| | - Kapil Dev Singh
- University Children's Hospital Basel, University of Basel, Spitalstrasse 33, 4056 Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Gewerbestrasse 14, 4123 Allschwil, Switzerland
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20
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van Liere ELSA, van Dijk LJ, Bosch S, Vermeulen L, Heymans MW, Burchell GL, de Meij TGJ, Ramsoekh D, de Boer NKH. Urinary volatile organic compounds for colorectal cancer screening, a systematic review and meta-analysis. Eur J Cancer 2023; 186:69-82. [PMID: 37030079 DOI: 10.1016/j.ejca.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND The faecal immunochemical test (FIT) suffers from suboptimal performance and participation in colorectal cancer (CRC) screening. Urinary volatile organic compounds (VOCs) may be a useful alternative. We aimed to determine the diagnostic potential of urinary VOCs for CRC/adenomas. By relating VOCs to known pathways, we aimed to gain insight into the pathophysiology of colorectal neoplasia. METHODS A systematic search was performed in PubMed, EMBASE and Web of Science. Original studies on urinary VOCs for CRC/adenoma detection with a control group were included. QUADAS-2 tool was used for quality assessment. Meta-analysis was performed by adopting a bivariate model for sensitivity/specificity. Fagan's nomogram estimated the performance of combined FIT-VOC. Neoplasm-associated VOCs were linked to pathways using the KEGG database. RESULTS Sixteen studies-involving 837 CRC patients and 1618 controls-were included; 11 performed chemical identification and 7 chemical fingerprinting. In all studies, urinary VOCs discriminated CRC from controls. Pooled sensitivity and specificity for CRC based on chemical fingerprinting were 84% (95% CI 73-91%) and 70% (95% CI 63-77%), respectively. The most distinctive individual VOC was butanal (AUC 0.98). The estimated probability of having CRC following negative FIT was 0.38%, whereas 0.09% following negative FIT-VOC. Combined FIT-VOC would detect 33% more CRCs. In total 100 CRC-associated urinary VOCs were identified; particularly hydrocarbons, carboxylic acids, aldehydes/ketones and amino acids, and predominantly involved in TCA-cycle or alanine/aspartate/glutamine/glutamate/phenylalanine/tyrosine/tryptophan metabolism, which is supported by previous research on (colorectal)cancer biology. The potential of urinary VOCs to detect precancerous adenomas or gain insight into their pathophysiology appeared understudied. CONCLUSION Urinary VOCs hold potential for non-invasive CRC screening. Multicentre validation studies are needed, especially focusing on adenoma detection. Urinary VOCs elucidate underlying pathophysiologic processes.
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Affiliation(s)
- Elsa L S A van Liere
- Amsterdam University Medical Centres, Department of Gastroenterology and Hepatology, Amsterdam, the Netherlands; Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands; Vrije Universiteit, School of Medicine, Amsterdam, the Netherlands.
| | - Laura J van Dijk
- Amsterdam University Medical Centres, Department of Gastroenterology and Hepatology, Amsterdam, the Netherlands; Vrije Universiteit, School of Medicine, Amsterdam, the Netherlands
| | - Sofie Bosch
- Amsterdam University Medical Centres, Department of Gastroenterology and Hepatology, Amsterdam, the Netherlands; Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands
| | - Louis Vermeulen
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands; Amsterdam UMC location University of Amsterdam, Laboratory for Experimental Oncology and Radiobiology, Centre for Experimental and Molecular Medicine, Amsterdam, the Netherlands; Cancer Centre Amsterdam, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Martijn W Heymans
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam, the Netherlands
| | - George L Burchell
- Medical Library, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Tim G J de Meij
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Paediatric Gastroenterology, Amsterdam, the Netherlands
| | - Dewkoemar Ramsoekh
- Amsterdam University Medical Centres, Department of Gastroenterology and Hepatology, Amsterdam, the Netherlands; Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands; Vrije Universiteit, School of Medicine, Amsterdam, the Netherlands
| | - Nanne K H de Boer
- Amsterdam University Medical Centres, Department of Gastroenterology and Hepatology, Amsterdam, the Netherlands; Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Amsterdam, the Netherlands; Vrije Universiteit, School of Medicine, Amsterdam, the Netherlands
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21
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Guo Y, Hou Y, Lv C, Ma X, Yang M, Jin Y, Li B, Liu W. Tetrakis(4-pyridylphenyl)ethylene-based Zinc Metal-Organic Framework with Aggregation-Induced Chemiluminescence Emission on a Paper Platform for Formaldehyde Detection in Breath. Anal Chem 2023; 95:1739-1746. [PMID: 36574337 DOI: 10.1021/acs.analchem.2c05048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Volatile formaldehyde (FA) in exhaled breath (EB) is considered as a biomarker for lung cancer (LC). On-the-spot selective and sensitive detection of gaseous FA is rather important for LC screening and diagnosis. Herein, a tetrakis(4-pyridylphenyl)ethylene (Py-TPE)-based zinc metal-organic framework (MOF) with excellent aggregation-induced emission (AIE) property was utilized for absorption and selective detection of FA in EB. The porous Zn-Py-TPE served as a gaseous confinement cavity for the adsorption of FA in EB. Interestingly, Zn-Py-TPE was aggregated on paper, and then aggregation-induced chemiluminescence (CL) emission can be triggered by only adding bis(2,4,6-trichlorophenyl)oxalate (TCPO). Though without H2O2, the CL of Zn-Py-TPE-TCPO was enhanced greatly by FA. FA promoted the aggregation of Zn-Py-TPE on paper by forming halogen bonding between FA and Zn-Py-TPE, which contributed to the better selectivity. FA can also stimulate the production of more singlet oxygen (1O2) in the Zn-Py-TPE-TCPO CL system. Hence, FA could be detected via the proposed Zn-Py-TPE-TCPO system with a quantification linear range of 1.0-100.0 ppb and detection limit of 0.3 ppb. This portable, low-cost, and sensitive paper-based platform can achieve trace FA detection in EB and is expected to provide an on-the-spot screening platform for lung cancer.
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Affiliation(s)
- Yanli Guo
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Yue Hou
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Congcong Lv
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Xiaohu Ma
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Min Yang
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Yan Jin
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Baoxin Li
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
| | - Wei Liu
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710062, China
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22
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VOCs from Exhaled Breath for the Diagnosis of Hepatocellular Carcinoma. Diagnostics (Basel) 2023; 13:diagnostics13020257. [PMID: 36673067 PMCID: PMC9858163 DOI: 10.3390/diagnostics13020257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/30/2022] [Accepted: 01/02/2023] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Volatile organic compound (VOC) profiles as biomarkers for hepatocellular carcinoma (HCC) are understudied. We aimed to identify VOCs from the exhaled breath for HCC diagnosis and compare the performance of VOCs to alpha-fetoprotein (AFP). The performance of VOCs for predicting treatment response and the association between VOCs level and survival of HCC patients were also determined. METHODS VOCs from 124 HCC patients and 219 controls were identified using the XGBoost algorithm. ROC analysis was used to determine VOCs performance in differentiating HCC patients from controls and in discriminating treatment responders from non-responders. The association between VOCs and the survival of HCC patients was analyzed using Cox proportional hazard analysis. RESULTS The combination of 9 VOCs yielded 70.0% sensitivity, 88.6% specificity, and 75.0% accuracy for HCC diagnosis. When differentiating early HCC from cirrhotic patients, acetone dimer had a significantly higher AUC than AFP, i.e., 0.775 vs. 0.714, respectively, p = 0.001. Acetone dimer classified HCC patients into treatment responders and non-responders, with 95.7% sensitivity, 73.3% specificity, and 86.8% accuracy. Isopropyl alcohol was independently associated with the survival of HCC patients, with an adjusted hazard ratio of 7.23 (95%CI: 1.36-38.54), p = 0.020. CONCLUSIONS Analysis of VOCs is a feasible noninvasive test for diagnosing and monitoring HCC treatment response.
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23
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Farnum A, Parnas M, Hoque Apu E, Cox E, Lefevre N, Contag CH, Saha D. Harnessing insect olfactory neural circuits for detecting and discriminating human cancers. Biosens Bioelectron 2023; 219:114814. [PMID: 36327558 DOI: 10.1016/j.bios.2022.114814] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.
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Affiliation(s)
- Alexander Farnum
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Michael Parnas
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Ehsanul Hoque Apu
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Division of Hematology and Oncology, Department of Internal Medicine, Michigan Medicine, University of Michigan, Ann Arbor, MI, 48108, USA
| | - Elyssa Cox
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Noël Lefevre
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Christopher H Contag
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Debajit Saha
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA.
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24
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Gouzerh F, Ganem G, Pichevin A, Dormont L, Thomas F. Ability of animals to detect cancer odors. Biochim Biophys Acta Rev Cancer 2023; 1878:188850. [PMID: 36528192 DOI: 10.1016/j.bbcan.2022.188850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/12/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
The olfactory capacity of animals has long been used by humans to help with various activities, e.g., hunting, detecting mines, locating people, and diagnosing diseases. Cancer is among the leading diseases causing death worldwide. Several recent studies have underscored the benefit of using scent to detect cancer, and this paper will review the studies using animals to detect tumor scents. A large variety of animals have been used for this purpose-dogs, rodents, insects, and nematodes-and have shown their capacity to detect cancer, with a success rate close to 90%. Here we discuss these studies, their methodologies, and the animal models used. Finally, we discuss the medical perspectives for cancer diagnosis using odors.
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Affiliation(s)
- Flora Gouzerh
- Centre de Recherches Écologiques et Évolutives sur le Cancer, Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle, UMR IRD 224- CNRS 5290- Université de Montpellier, 34394 Montpellier, France; Centre d'Ecologie Fonctionnelle et Evolutive, Université́ de Montpellier, CNRS, EPHE, IRD, Université Paul Valéry Montpellier 3, 34293 Montpellier, France.
| | - Guila Ganem
- Institut des Sciences de l'Evolution, ISEM, Université Montpellier, CNRS, IRD, 34095 Montpellier, France
| | - Anaïs Pichevin
- Centre d'Ecologie Fonctionnelle et Evolutive, Université́ de Montpellier, CNRS, EPHE, IRD, Université Paul Valéry Montpellier 3, 34293 Montpellier, France
| | - Laurent Dormont
- Centre d'Ecologie Fonctionnelle et Evolutive, Université́ de Montpellier, CNRS, EPHE, IRD, Université Paul Valéry Montpellier 3, 34293 Montpellier, France
| | - Frédéric Thomas
- Centre de Recherches Écologiques et Évolutives sur le Cancer, Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle, UMR IRD 224- CNRS 5290- Université de Montpellier, 34394 Montpellier, France
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25
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Hwang CH, Lee S, Lee S, Kim H, Kang T, Lee D, Jeong KH. Highly Adsorptive Au-TiO 2 Nanocomposites for the SERS Face Mask Allow the Machine-Learning-Based Quantitative Assay of SARS-CoV-2 in Artificial Breath Aerosols. ACS APPLIED MATERIALS & INTERFACES 2022; 14:54550-54557. [PMID: 36448483 PMCID: PMC9718102 DOI: 10.1021/acsami.2c16446] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
Human respiratory aerosols contain diverse potential biomarkers for early disease diagnosis. Here, we report the direct and label-free detection of SARS-CoV-2 in respiratory aerosols using a highly adsorptive Au-TiO2 nanocomposite SERS face mask and an ablation-assisted autoencoder. The Au-TiO2 SERS face mask continuously preconcentrates and efficiently captures the oronasal aerosols, which substantially enhances the SERS signal intensities by 47% compared to simple Au nanoislands. The ultrasensitive Au-TiO2 nanocomposites also demonstrate the successful detection of SARS-CoV-2 spike proteins in artificial respiratory aerosols at a 100 pM concentration level. The deep learning-based autoencoder, followed by the partial ablation of nondiscriminant SERS features of spike proteins, allows a quantitative assay of the 101-104 pfu/mL SARS-CoV-2 lysates (comparable to 19-29 PCR cyclic threshold from COVID-19 patients) in aerosols with an accuracy of over 98%. The Au-TiO2 SERS face mask provides a platform for breath biopsy for the detection of various biomarkers in respiratory aerosols.
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Affiliation(s)
- Charles
S. H. Hwang
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
- KAIST
Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro,
Yuseong-gu, Daejeon 34141, Korea
| | - Sangyeon Lee
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Sejin Lee
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
- KAIST
Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro,
Yuseong-gu, Daejeon 34141, Korea
| | - Hanjin Kim
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Taejoon Kang
- Bionanotechnology
Research Center, Korea Research Institute
of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon 34141, Korea
- School
of Pharmacy, Sungkyunkwan University, Suwon 16419, Korea
| | - Doheon Lee
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Ki-Hun Jeong
- Department
of Bio and Brain Engineering, Korea Advanced
Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
- KAIST
Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro,
Yuseong-gu, Daejeon 34141, Korea
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26
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Shahi F, Forrester S, Redeker K, Chong JP, Barlow G. Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year. Wellcome Open Res 2022; 7:50. [PMID: 36874581 PMCID: PMC9975432 DOI: 10.12688/wellcomeopenres.17450.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found. METHODS As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year. RESULTS We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites. CONCLUSIONS This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.
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Affiliation(s)
- Farah Shahi
- Department of Biology, University of York, UK, York, YO10 5DD, UK
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
| | - Sarah Forrester
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Kelly Redeker
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - James P.J. Chong
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Gavin Barlow
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
- Experimental Medicine and Biomedicine, Hull York Medical School, University of York, York, YO10 5DD, UK
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Volatilomics as an Emerging Strategy to Determine Potential Biomarkers of Female Infertility: A Pilot Study. Biomedicines 2022; 10:biomedicines10112852. [DOI: 10.3390/biomedicines10112852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/02/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022] Open
Abstract
Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.
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28
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Volatilomics: An Emerging and Promising Avenue for the Detection of Potential Prostate Cancer Biomarkers. Cancers (Basel) 2022; 14:cancers14163982. [PMID: 36010975 PMCID: PMC9406416 DOI: 10.3390/cancers14163982] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/09/2022] [Accepted: 08/16/2022] [Indexed: 12/20/2022] Open
Abstract
Simple Summary The lack of highly specific and sensitive biomarkers for the early detection of prostate cancer (PCa) is a major barrier to its management. Volatilomics emerged as a non-invasive, simple, inexpensive, and easy-to-use approach for cancer screening, characterization of disease progression, and follow-up of the treatment’s success. We provide a brief overview of the potential of volatile organic metabolites (VOMs) for the establishment of PCa biomarkers from non-invasive matrices. Endogenous VOMs have been investigated as potential biomarkers since changes in these VOMs can be characteristic of specific disease processes. Recent studies have shown that the conjugation of the prostate-specific antigen (PSA) screening with other methodologies, such as risk calculators, biomarkers, and imaging tests, can attenuate overdiagnosis and under-detection issues. This means that the combination of volatilomics with other methodologies could be extremely valuable for the differentiation of clinical phenotypes in a group of patients, providing more personalized treatments. Abstract Despite the spectacular advances in molecular medicine, including genomics, proteomics, transcriptomics, lipidomics, and personalized medicine, supported by the discovery of the human genome, prostate cancer (PCa) remains the most frequent malignant tumor and a leading cause of oncological death in men. New methods for prognostic, diagnostic, and therapy evaluation are mainly based on the combination of imaging techniques with other methodologies, such as gene or protein profiling, aimed at improving PCa management and surveillance. However, the lack of highly specific and sensitive biomarkers for its early detection is a major hurdle to this goal. Apart from classical biomarkers, the study of endogenous volatile organic metabolites (VOMs) biosynthesized by different metabolic pathways and found in several biofluids is emerging as an innovative, efficient, accessible, and non-invasive approach to establish the volatilomic biosignature of PCa patients, unravelling potential biomarkers. This review provides a brief overview of the challenges of PCa screening methods and emergent biomarkers. We also focus on the potential of volatilomics for the establishment of PCa biomarkers from non-invasive matrices.
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29
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Pham YL, Beauchamp J, Clement A, Wiegandt F, Holz O. 3D-printed mouthpiece adapter for sampling exhaled breath in medical applications. 3D Print Med 2022; 8:27. [PMID: 35943600 PMCID: PMC9364600 DOI: 10.1186/s41205-022-00150-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/07/2022] [Indexed: 11/10/2022] Open
Abstract
The growing use of 3D printing in the biomedical sciences demonstrates its utility for a wide range of research and healthcare applications, including its potential implementation in the discipline of breath analysis to overcome current limitations and substantial costs of commercial breath sampling interfaces. This technical note reports on the design and construction of a 3D-printed mouthpiece adapter for sampling exhaled breath using the commercial respiration collector for in-vitro analysis (ReCIVA) device. The paper presents the design and digital workflow transition of the adapter and its fabrication from three commercial resins (Surgical Guide, Tough v5, and BioMed Clear) using a Formlabs Form 3B stereolithography (SLA) printer. The use of the mouthpiece adapter in conjunction with a pulmonary function filter is appraised in comparison to the conventional commercial silicon facemask sampling interface. Besides its lower cost - investment cost of the printing equipment notwithstanding - the 3D-printed adapter has several benefits, including ensuring breath sampling via the mouth, reducing the likelihood of direct contact of the patient with the breath sampling tubes, and being autoclaveable to enable the repeated use of a single adapter, thereby reducing waste and associated environmental burden compared to current one-way disposable facemasks. The novel adapter for breath sampling presented in this technical note represents an additional field of application for 3D printing that further demonstrates its widespread applicability in biomedicine.
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Affiliation(s)
- Y Lan Pham
- Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Straße 35, 85354, Freising, Germany.,Department of Chemistry and Pharmacy, Chair of Aroma and Smell Research, Friedrich-Alexander-Universität Erlangen-Nürnberg, Henkestraße 9, 91054, Erlangen, Germany
| | - Jonathan Beauchamp
- Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Straße 35, 85354, Freising, Germany
| | - Alexander Clement
- Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Feodor-Lynen-Str. 15, 30625, Hannover, Germany
| | - Felix Wiegandt
- Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Feodor-Lynen-Str. 15, 30625, Hannover, Germany
| | - Olaf Holz
- Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Feodor-Lynen-Str. 15, 30625, Hannover, Germany. .,Member of the German Centre of Lung Research DZL (BREATH), Hannover, Germany.
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30
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Choueiry F, Barham A, Zhu J. Analyses of lung cancer-derived volatiles in exhaled breath and in vitro models. Exp Biol Med (Maywood) 2022; 247:1179-1190. [PMID: 35410512 PMCID: PMC9335511 DOI: 10.1177/15353702221082634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Lung cancer is one of the leading causes of cancer incidence and cancer-related deaths in the world. Early diagnosis of pulmonary tumors results in improved survival compared to diagnosis with more advanced disease, yet early disease is not reliably indicated by symptoms. Despite of the improved testing and monitoring techniques for lung cancer in the past decades, most diagnostic tests, such as sputum cytology or tissue biopsies, are invasive and risky, rendering them unfeasible for large population screening. The non-invasive analysis of exhaled breath has gained attentions as an innovative screening method to measure chemical alterations within the human volatilome profile as a result of oncogenesis. More importantly, volatile organic compounds (VOCs) have been correlated to the pathophysiology of disease since the source of volatile compounds relies mostly on endogenous metabolic processes that are altered as a result of disease onset. Therefore, studying VOCs emitted from human breath may assist lung cancer diagnosis, treatment monitoring, and other surveillance of this devastating disease. In this mini review, we evaluated recent human studies that have attempted to identify lung cancer-derived volatiles in exhaled breath of patients. We also examined reported volatiles in cell cultures of lung cancer to better understand the origins of cancer-associated VOCs. We highlight the metabolic processes of lung cancer that could be responsible for the endogenous synthesis of these VOCs and pinpoint the protein-encoding genes involved in these pathways. Finally, we highlight the potential value of a breath test in lung cancer and propose prominent areas for future research required for the incorporation of VOCs-based testing into clinical settings.
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Affiliation(s)
- Fouad Choueiry
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210-1132, USA
| | - Addison Barham
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210-1132, USA
| | - Jiangjiang Zhu
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210-1132, USA,James Comprehensive Cancer Center, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA,Jiangjiang Zhu.
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Janssens E, Schillebeeckx E, Zwijsen K, Raskin J, Van Cleemput J, Surmont VF, Nackaerts K, Marcq E, van Meerbeeck JP, Lamote K. External Validation of a Breath-Based Prediction Model for Malignant Pleural Mesothelioma. Cancers (Basel) 2022; 14:cancers14133182. [PMID: 35804954 PMCID: PMC9264774 DOI: 10.3390/cancers14133182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Malignant pleural mesothelioma (MPM) is an incurable asbestos-related thoracic cancer for which early-stage diagnosis remains a major challenge. Volatile organic compounds (VOCs), which are metabolites present in exhaled breath, have proven to be promising non-invasive biomarkers for MPM. However, without the necessary validation in an independent group of individuals, clinical implementation is hampered. Therefore, we performed external validation of a VOC-based prediction model for MPM, which initially revealed a poor performance and thus poor generalisability of the model. However, subsequent updating of the model improved its performance in the validation cohort, resulting in a more generalisable model with a screening potential, which could significantly impact MPM management. Abstract During the past decade, volatile organic compounds (VOCs) in exhaled breath have emerged as promising biomarkers for malignant pleural mesothelioma (MPM). However, as these biomarkers lack external validation, no breath test for MPM has been implemented in clinical practice. To address this issue, we performed the first external validation of a VOC-based prediction model for MPM. The external validation cohort was prospectively recruited, consisting of 47 MPM patients and 76 asbestos-exposed (AEx) controls. The predictive performance of the previously developed model was assessed by determining the degree of agreement between the predicted and actual outcome of the participants (patient/control). Additionally, to optimise the performance, the model was updated by refitting it to the validation cohort. External validation revealed a poor performance of the original model as the accuracy was estimated at only 41%, indicating poor generalisability. However, subsequent updating of the model improved the differentiation between MPM patients and AEx controls significantly (73% accuracy, 92% sensitivity, and 92% negative predictive value), substantiating the validity of the original predictors. This updated model will be more generalisable to the target population and exhibits key characteristics of a potential screening test for MPM, which could significantly impact MPM management.
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Affiliation(s)
- Eline Janssens
- Laboratory of Experimental Medicine and Pediatrics, Infla-Med Center of Excellence, University of Antwerp, 2610 Antwerp, Belgium; (E.J.); (E.S.); (K.Z.); (J.P.v.M.)
| | - Eline Schillebeeckx
- Laboratory of Experimental Medicine and Pediatrics, Infla-Med Center of Excellence, University of Antwerp, 2610 Antwerp, Belgium; (E.J.); (E.S.); (K.Z.); (J.P.v.M.)
- VIB-UGent Center for Medical Biotechnology, 9000 Ghent, Belgium
| | - Kathleen Zwijsen
- Laboratory of Experimental Medicine and Pediatrics, Infla-Med Center of Excellence, University of Antwerp, 2610 Antwerp, Belgium; (E.J.); (E.S.); (K.Z.); (J.P.v.M.)
| | - Jo Raskin
- Department of Pulmonology & Thoracic Oncology, Antwerp University Hospital, 2650 Edegem, Belgium;
| | - Joris Van Cleemput
- Occupational Health Service, Eternit N.V., 1880 Kapelle-op-den-Bos, Belgium;
| | - Veerle F. Surmont
- Department of Respiratory Medicine, Ghent University Hospital, 9000 Ghent, Belgium;
| | - Kristiaan Nackaerts
- Department of Respiratory Medicine, University Hospital Gasthuisberg, 3000 Leuven, Belgium;
| | - Elly Marcq
- Center for Oncological Research (CORE), Integrated Personalized and Precision Oncology Network (IPPON), University of Antwerp, 2610 Antwerp, Belgium;
| | - Jan P. van Meerbeeck
- Laboratory of Experimental Medicine and Pediatrics, Infla-Med Center of Excellence, University of Antwerp, 2610 Antwerp, Belgium; (E.J.); (E.S.); (K.Z.); (J.P.v.M.)
- Department of Pulmonology & Thoracic Oncology, Antwerp University Hospital, 2650 Edegem, Belgium;
- Department of Internal Medicine and Pediatrics, Ghent University, 9000 Ghent, Belgium
| | - Kevin Lamote
- Laboratory of Experimental Medicine and Pediatrics, Infla-Med Center of Excellence, University of Antwerp, 2610 Antwerp, Belgium; (E.J.); (E.S.); (K.Z.); (J.P.v.M.)
- Department of Internal Medicine and Pediatrics, Ghent University, 9000 Ghent, Belgium
- Correspondence: ; Tel.: +32-3-265-25-81
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32
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Rothbart N, Stanley V, Koczulla R, Jarosch I, Holz O, Schmalz K, Hübers HW. Millimeter-wave gas spectroscopy for breath analysis of COPD patients in comparison to GC-MS. J Breath Res 2022; 16. [PMID: 35688126 DOI: 10.1088/1752-7163/ac77aa] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/10/2022] [Indexed: 01/12/2023]
Abstract
The analysis of human breath is a very active area of research, driven by the vision of a fast, easy, and non-invasive tool for medical diagnoses at the point of care. Millimeter-wave gas spectroscopy (MMWGS) is a novel, well-suited technique for this application as it provides high sensitivity, specificity and selectivity. Most of all, it offers the perspective of compact low-cost systems to be used in doctors' offices or hospitals. In this work, we demonstrate the analysis of breath samples acquired in a medical environment using MMWGS and evaluate validity, reliability, as well as limitations and perspectives of the method. To this end, we investigated 28 duplicate samples from chronic obstructive lung disease patients and compared the results to gas chromatography-mass spectrometry (GC-MS). The quantification of the data was conducted using a calibration-free fit model, which describes the data precisely and delivers absolute quantities. For ethanol, acetone, and acetonitrile, the results agree well with the GC-MS measurements and are as reliable as GC-MS. The duplicate samples deviate from the mean values by only 6% to 18%. Detection limits of MMWGS depend strongly on the molecular species. For example, acetonitrile can be traced down to 1.8 × 10-12mol by the MMWGS system, which is comparable to the GC-MS system. We observed correlations of abundances between formaldehyde and acetaldehyde as well as between acetonitrile and acetaldehyde, which demonstrates the potential of MMWGS for breath research.
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Affiliation(s)
- Nick Rothbart
- Institute of Optical Sensor Systems, German Aerospace Center (DLR), Berlin, Germany.,Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Victoria Stanley
- Institute of Optical Sensor Systems, German Aerospace Center (DLR), Berlin, Germany.,Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Rembert Koczulla
- Schön Klinik Berchtesgadener Land, Research Institute for Pulmonary Rehabilitation, Schönau am Königssee, Germany.,Philipps-University of Marburg, Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Inga Jarosch
- Schön Klinik Berchtesgadener Land, Research Institute for Pulmonary Rehabilitation, Schönau am Königssee, Germany.,Philipps-University of Marburg, Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Olaf Holz
- Fraunhofer ITEM, German Center for Lung Research (BREATH, DZL), Clinical Airway Research, Hannover, Germany
| | - Klaus Schmalz
- IHP-Leibniz-Institut für Innovative Mikroelektronik, Frankfurt (Oder), Germany
| | - Heinz-Wilhelm Hübers
- Institute of Optical Sensor Systems, German Aerospace Center (DLR), Berlin, Germany.,Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
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33
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Zhang L, Li X, Chen H, Wu Z, Hu M, Yao M. Haze Air Pollution Health Impacts of Breath-Borne VOCs. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:8541-8551. [PMID: 35559607 DOI: 10.1021/acs.est.2c01778] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Here, we investigated the use of breath-borne volatile organic compounds (VOCs) for rapid monitoring of air pollution health effects on humans. Forty-seven healthy college students were recruited, and their exhaled breath samples (n = 235) were collected and analyzed for VOCs before, on, and after two separate haze pollution episodes using gas chromatography-ion mobility spectrometry (GC-IMS). Using a paired t-test and machine learning model (Gradient Boosting Machine, GBM), six exhaled VOC species including propanol and isoprene were revealed to differ significantly among pre-, on-, and post-exposure in both haze episodes, while none was found between clean control days. The GBM model was shown capable of differentiating between pre- and on-exposure to haze pollution with a precision of 90-100% for both haze episodes. However, poor performance was detected for the same model between two different clean days. In addition to gender and particular haze occurrence influences, correlation analysis revealed that NH4+, NO3-, acetic acid, mesylate, CO, NO2, PM2.5, and O3 played important roles in the changes in breath-borne VOC fingerprints following haze air pollution exposure. This work has demonstrated direct evidence of human health impacts of haze pollution while identifying potential breath-borne VOC biomarkers such as propanol and isoprene for haze air pollution exposure.
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Affiliation(s)
- Lu Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xinyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Haoxuan Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zhijun Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Maosheng Yao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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34
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Shahi F, Forrester S, Redeker K, Chong JP, Barlow G. Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year. Wellcome Open Res 2022; 7:50. [PMID: 36874581 PMCID: PMC9975432 DOI: 10.12688/wellcomeopenres.17450.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/06/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found. METHODS As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year. RESULTS We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites. CONCLUSIONS This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.
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Affiliation(s)
- Farah Shahi
- Department of Biology, University of York, UK, York, YO10 5DD, UK
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
| | - Sarah Forrester
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Kelly Redeker
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - James P.J. Chong
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Gavin Barlow
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
- Experimental Medicine and Biomedicine, Hull York Medical School, University of York, York, YO10 5DD, UK
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35
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Abstract
This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.
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Affiliation(s)
- Muhammad Khatib
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Hossam Haick
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 3200003, Israel
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36
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Sampaolo A, Patimisco P, Giglio M, Zifarelli A, Wu H, Dong L, Spagnolo V. Quartz-enhanced photoacoustic spectroscopy for multi-gas detection: A review. Anal Chim Acta 2022; 1202:338894. [PMID: 35341511 DOI: 10.1016/j.aca.2021.338894] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 07/02/2021] [Accepted: 07/26/2021] [Indexed: 11/29/2022]
Abstract
Multi-gas detection represents a suitable solution in many applications, such as environmental and atmospheric monitoring, chemical reaction and industrial process control, safety and security, oil&gas and biomedicine. Among optical techniques, Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) has been demonstrated to be a leading-edge technology for addressing multi-gas detection, thanks to the modularity, ruggedness, portability and real time operation of the QEPAS sensors. The detection module consists in a spectrophone, mounted in a vacuum-tight cell and detecting sound waves generated via photoacoustic excitation within the gas sample. As a result, the sound detection is wavelength-independent and the volume of the absorption cell is basically determined by the spectrophone dimensions, typically in the order of few cubic centimeters. In this review paper, the implementation of the QEPAS technique for multi-gas detection will be discussed for three main areas of applications: i) multi-gas trace sensing by exploiting non-interfering absorption features; ii) multi-gas detection dealing with overlapping absorption bands; iii) multi-gas detection in fluctuating backgrounds. The fundamental role of the analysis and statistical tools will be also discussed in detail in relation with the specific applications. This overview on QEPAS technique, highlighting merits and drawbacks, aims at providing ready-to-use guidelines for multi-gas detection in a wide range of applications and operating conditions.
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Affiliation(s)
- Angelo Sampaolo
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China; Polysense Lab, Dipartimento Interateneo di Fisica, University and Politecnico of Bari, CNR-IFN, Via Amendola 173, Bari, 70126, Italy
| | - Pietro Patimisco
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China; Polysense Lab, Dipartimento Interateneo di Fisica, University and Politecnico of Bari, CNR-IFN, Via Amendola 173, Bari, 70126, Italy
| | - Marilena Giglio
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China; Polysense Lab, Dipartimento Interateneo di Fisica, University and Politecnico of Bari, CNR-IFN, Via Amendola 173, Bari, 70126, Italy
| | - Andrea Zifarelli
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China; Polysense Lab, Dipartimento Interateneo di Fisica, University and Politecnico of Bari, CNR-IFN, Via Amendola 173, Bari, 70126, Italy
| | - Hongpeng Wu
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China
| | - Lei Dong
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China.
| | - Vincenzo Spagnolo
- State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy & Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China; Polysense Lab, Dipartimento Interateneo di Fisica, University and Politecnico of Bari, CNR-IFN, Via Amendola 173, Bari, 70126, Italy.
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Shahi F, Forrester S, Redeker K, Chong JP, Barlow G. Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year. Wellcome Open Res 2022; 7:50. [PMID: 36874581 PMCID: PMC9975432 DOI: 10.12688/wellcomeopenres.17450.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found. METHODS As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year. RESULTS We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites. CONCLUSIONS This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.
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Affiliation(s)
- Farah Shahi
- Department of Biology, University of York, UK, York, YO10 5DD, UK
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
| | - Sarah Forrester
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Kelly Redeker
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - James P.J. Chong
- Department of Biology, University of York, UK, York, YO10 5DD, UK
| | - Gavin Barlow
- Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, HU3 2JZ, UK
- Experimental Medicine and Biomedicine, Hull York Medical School, University of York, York, YO10 5DD, UK
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A pilot study for the prediction of liver function related scores using breath biomarkers and machine learning. Sci Rep 2022; 12:2032. [PMID: 35132067 PMCID: PMC8821604 DOI: 10.1038/s41598-022-05808-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 01/13/2022] [Indexed: 02/07/2023] Open
Abstract
Volatile organic compounds (VOCs) present in exhaled breath can help in analysing biochemical processes in the human body. Liver diseases can be traced using VOCs as biomarkers for physiological and pathophysiological conditions. In this work, we propose non-invasive and quick breath monitoring approach for early detection and progress monitoring of liver diseases using Isoprene, Limonene, and Dimethyl sulphide (DMS) as potential biomarkers. A pilot study is performed to design a dataset that includes the biomarkers concentration analysed from the breath sample before and after study subjects performed an exercise. A machine learning approach is applied for the prediction of scores for liver function diagnosis. Four regression methods are performed to predict the clinical scores using breath biomarkers data as features set by the machine learning techniques. A significant difference was observed for isoprene concentration (p < 0.01) and for DMS concentration (p < 0.0001) between liver patients and healthy subject's breath sample. The R-square value between actual clinical score and predicted clinical score is found to be 0.78, 0.82, and 0.85 for CTP score, APRI score, and MELD score, respectively. Our results have shown a promising result with significant different breath profiles between liver patients and healthy volunteers. The use of machine learning for the prediction of scores is found very promising for use of breath biomarkers for liver function diagnosis.
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Kaloumenou M, Skotadis E, Lagopati N, Efstathopoulos E, Tsoukalas D. Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors. SENSORS (BASEL, SWITZERLAND) 2022; 22:1238. [PMID: 35161984 PMCID: PMC8840008 DOI: 10.3390/s22031238] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 05/07/2023]
Abstract
Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.
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Affiliation(s)
- Maria Kaloumenou
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Evangelos Skotadis
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Nefeli Lagopati
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Efstathios Efstathopoulos
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Dimitris Tsoukalas
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
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Samira Kaghazkonani, Sadegh Afshari. Sensing C3–C10 Straight Chain Aldehydes Biomarker Gas Molecules: Density Functional Theory. RUSSIAN JOURNAL OF PHYSICAL CHEMISTRY B 2022. [DOI: 10.1134/s199079312106018x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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41
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Roquencourt C, Grassin-Delyle S, Thévenot EA. ptairMS: real-time processing and analysis of PTR-TOF-MS data for biomarker discovery in exhaled breath. Bioinformatics 2022; 38:1930-1937. [PMID: 35043937 PMCID: PMC8963316 DOI: 10.1093/bioinformatics/btac031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/24/2021] [Accepted: 01/16/2022] [Indexed: 11/14/2022] Open
Abstract
Motivation Analysis of volatile organic compounds (VOCs) in exhaled breath by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is of increasing interest for real-time, non-invasive diagnosis, phenotyping and therapeutic drug monitoring in the clinics. However, there is currently a lack of methods and software tools for the processing of PTR-TOF-MS data from cohorts and suited for biomarker discovery studies. Results We developed a comprehensive suite of algorithms that process raw data from patient acquisitions and generate the table of feature intensities. Notably, we included an innovative two-dimensional peak deconvolution model based on penalized splines signal regression for accurate estimation of the temporal profile and feature quantification, as well as a method to specifically select the VOCs from exhaled breath. The workflow was implemented as the ptairMS software, which contains a graphical interface to facilitate cohort management and data analysis. The approach was validated on both simulated and experimental datasets, and we showed that the sensitivity and specificity of the VOC detection reached 99% and 98.4%, respectively, and that the error of quantification was below 8.1% for concentrations down to 19 ppb. Availability and implementation The ptairMS software is publicly available as an R package on Bioconductor (doi: 10.18129/B9.bioc.ptairMS), as well as its companion experiment package ptairData (doi: 10.18129/B9.bioc.ptairData). Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Camille Roquencourt
- CEA, LIST, Laboratoire Sciences des Données et de la Décision, F-91191 Gif-Sur-Yvette, France
| | - Stanislas Grassin-Delyle
- Hôpital Foch, Exhalomics, Département des maladies des voies respiratoires, Suresnes, France
- Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation, Département de Biotechnologie de la Santé, Montigny le Bretonneux, France
- FHU SEPSIS (Saclay and Paris Seine Nord Endeavour to PerSonalize Interventions for Sepsis)
| | - Etienne A Thévenot
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), MetaboHUB, F-91191 Gif sur Yvette, France
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Faura G, Boix-Lemonche G, Holmeide AK, Verkauskiene R, Volke V, Sokolovska J, Petrovski G. Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning. SENSORS 2022; 22:s22030718. [PMID: 35161465 PMCID: PMC8839630 DOI: 10.3390/s22030718] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 12/20/2021] [Accepted: 12/26/2021] [Indexed: 12/13/2022]
Abstract
In this review, a selection of works on the sensing of biomarkers related to diabetes mellitus (DM) and diabetic retinopathy (DR) are presented, with the scope of helping and encouraging researchers to design sensor-array machine-learning (ML)-supported devices for robust, fast, and cost-effective early detection of these devastating diseases. First, we highlight the social relevance of developing systematic screening programs for such diseases and how sensor-arrays and ML approaches could ease their early diagnosis. Then, we present diverse works related to the colorimetric and electrochemical sensing of biomarkers related to DM and DR with non-invasive sampling (e.g., urine, saliva, breath, tears, and sweat samples), with a special mention to some already-existing sensor arrays and ML approaches. We finally highlight the great potential of the latter approaches for the fast and reliable early diagnosis of DM and DR.
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Affiliation(s)
- Georgina Faura
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
- Department of Medical Biochemistry, Institute of Clinical Medicine, University of Oslo, 0424 Oslo, Norway
| | - Gerard Boix-Lemonche
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
| | | | - Rasa Verkauskiene
- Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, LT-50009 Kaunas, Lithuania;
| | - Vallo Volke
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia;
- Institute of Biomedical and Transplant Medicine, Department of Medical Sciences, Tartu University Hospital, L. Puusepa Street, 51014 Tartu, Estonia
| | | | - Goran Petrovski
- Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway; (G.F.); (G.B.-L.)
- Department of Ophthalmology, Oslo University Hospital, 0450 Oslo, Norway
- Correspondence: ; Tel.: +47-9222-6158
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Gbaoui L, Fachet M, Lüno M, Meyer-Lotz G, Frodl T, Hoeschen C. Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations. Front Psychiatry 2022; 13:1061326. [PMID: 36590606 PMCID: PMC9795849 DOI: 10.3389/fpsyt.2022.1061326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/24/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD. METHODS Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis. RESULTS A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, pFDR=0.0006), 3-methylpyridine (p = 0.0002, pFDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, pFDR = 0.0174), valeric acid (p = 0.005, pFDR = 0.0162) and isoprene (p = 0.038, pFDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96). CONCLUSION According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.
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Affiliation(s)
- Laila Gbaoui
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
| | - Melanie Fachet
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
| | - Marian Lüno
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany
| | - Gabriele Meyer-Lotz
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany
| | - Thomas Frodl
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital, RWTH Aachen, Aachen, Germany
| | - Christoph Hoeschen
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
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Wu X, Wang H, Wang J, Wang D, Shi L, Tian X, Sun J. VOCs gas sensor based on MOFs derived porous Au@Cr2O3-In2O3 nanorods for breath analysis. Colloids Surf A Physicochem Eng Asp 2022. [DOI: 10.1016/j.colsurfa.2021.127752] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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45
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Salman D, Ibrahim W, Kanabar A, Joyce A, Zhao B, Singapuri A, Wilde M, Cordell RL, McNally T, Ruszkiewicz D, Hadjithekli A, Free R, Greening N, Gaillard EA, Beardsmore C, Monks P, Brightling C, Siddiqui S, Thomas CLP. The variability of volatile organic compounds in the indoor air of clinical environments. J Breath Res 2021; 16. [PMID: 34724656 DOI: 10.1088/1752-7163/ac3565] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Accepted: 11/01/2021] [Indexed: 11/11/2022]
Abstract
The development of clinical breath-analysis is confounded by the variability of background volatile organic compounds (VOCs). Reliable interpretation of clinical breath-analysis at individual, and cohort levels requires characterisation of clinical-VOC levels and exposures. Active-sampling with thermal-desorption/gas chromatography-mass spectrometry recorded and evaluated VOC concentrations in 245 samples of indoor air from three sites in a large National Health Service (NHS) provider trust in the UK over 27 months. Data deconvolution, alignment and clustering isolated 7344 features attributable to VOC and described the variability (composition and concentration) of respirable clinical VOC. 328 VOC were observed in more than 5% of the samples and 68 VOC appeared in more than 30% of samples. Common VOC were associated with exogenous and endogenous sources and 17 VOC were identified as seasonal differentiators. The presence of metabolites from the anaesthetic sevoflurane, and putative-disease biomarkers in room air, indicated that exhaled VOC were a source of background-pollution in clinical breath-testing activity. With the exception of solvents, and waxes associated with personal protective equipment (PPE), exhaled VOC concentrations above 3µg m-3are unlikely to arise from room air contamination, and in the absence of extensive survey-data, this level could be applied as a threshold for inclusion in studies, removing a potential environmental confounding-factor in developing breath-based diagnostics.
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Affiliation(s)
- Dahlia Salman
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Wadah Ibrahim
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Amisha Kanabar
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Abigail Joyce
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Bo Zhao
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Amisha Singapuri
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Michael Wilde
- Department of Chemistry, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Rebecca L Cordell
- Department of Chemistry, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Teresa McNally
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Dorota Ruszkiewicz
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Andria Hadjithekli
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Robert Free
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Neil Greening
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Erol A Gaillard
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Caroline Beardsmore
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Paul Monks
- Department of Chemistry, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom
| | - Chris Brightling
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - Salman Siddiqui
- College of Life Sciences, Department of Respiratory Sciences, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom.,Leicester NIHR Biomedical Research Centre (Respiratory theme), Glenfield Hospital, Groby Road, Leicester, LE3 9QP, United Kingdom
| | - C L Paul Thomas
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
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Ponurovsky YY, Nadezhdinsky AI, Stavrovsky DB, Shapovalov YP, Spiridonov MV, Kuzmichev AS, Karabinenko AA, Petrenko YM. Diode Laser Spectrometer for Diagnostic Assessment of Exhaled Air Components. Sovrem Tekhnologii Med 2021; 12:71-75. [PMID: 34796007 PMCID: PMC8596262 DOI: 10.17691/stm2020.12.5.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Indexed: 11/14/2022] Open
Abstract
The main requirements for a screening test are simplicity, non-invasiveness, safety of testing procedures, high processing speed, and ability to detect diseases at an early stage. A multichannel gas analyzer for assessment of exhaled air composition (diode laser spectrometer), non-invasive screening, and biomedical testing was developed on the basis of near-infrared diode lasers with fiber output. The device measures the following exhaled air components: 12CO2, 13CO2, CH4, NH3, H2O, and H2S. The concentration of molecules was measured in a multi-pass Herriot cell with a reference length of 40 cm, 1.8 L volume, and a total optical path length of 26 m. Three diode lasers manufactured by NTT Electronics (Japan) were used in the work. Detection of CH4 was carried out in the 1.65 μm wavelength range, 12CO2, 13CO2, and H2S levels were measured in the 1.60 μm range, NH3 and H2O in the 1.51 μm range. All measurements were taken in real time. Clinical testing of the spectrometer was carried out at V.M. Buyanov City Clinical Hospital of Moscow Department of Health. More than 150 patients were examined. The tests included analysis and measurement of these molecular components in the exhaled air of patients with various diseases. The content of these components was studied in conditions of various changes in the human physiological state (dosed physical activity, relaxation, psychoemotional stress, etc.). The studies have demonstrated efficacy of using the developed hardware system for assessment of exhaled air components in order to reveal functional disorders in various diseases of the digestive system, cardiorespiratory system, diseases caused by impaired nitrogen-excreting function of the kidneys, etc.
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Affiliation(s)
- Ya Ya Ponurovsky
- Head of the Department of Diode Laser Spectroscopy; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - A I Nadezhdinsky
- Professor, Chief Researcher; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - D B Stavrovsky
- Head of the Laboratory of Analytical Measurements; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - Yu P Shapovalov
- Researcher; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - M V Spiridonov
- Head of the Laboratory of Applied Diode Laser Spectroscopy; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - A S Kuzmichev
- Researcher; Federal Research Center, A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., Moscow, 119991, Russia
| | - A A Karabinenko
- Professor, Department of Hospital Therapy No.2; Pirogov Russian National Research Medical University, 1 Ostrovitianov St., Moscow, 117997, Russia
| | - Yu M Petrenko
- Professor, Department of General and Medical Biophysics Pirogov Russian National Research Medical University, 1 Ostrovitianov St., Moscow, 117997, Russia
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Zhou T, Dong W, Qiu Y, Chen S, Wang X, Xie C, Zeng D. Selectivity of a ZnO@ZIF-71@PDMS Nanorod Array Gas Sensor Enhanced by Coating a Polymer Selective Separation Membrane. ACS APPLIED MATERIALS & INTERFACES 2021; 13:54589-54596. [PMID: 34747600 DOI: 10.1021/acsami.1c16637] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
It is important for noninvasive diagnosis of diabetes to develop acetone gas sensors with high selectivity. ZnO@ZIF-71 has been reported as a highly sensitive and selective gas sensor on acetone detection. However, it is difficult to exclude the interference with similar molecular sizes gas in the gas-sensing process, like ethanol. To solve this problem, polydimethylsiloxane (PDMS) was synthesized on the surface of ZnO@ZIF-71 to form a ZnO@ZIF-71@PDMS sensor by vapor deposition. The new sensor shows inert response to ethanol and effective response to acetone simultaneously. The PDMS membrane acts as a molecular sieve, which shows the acetone selectivity performance and can totally eliminate the response to low concentration ethanol at low temperature. Theory calculations and solubility test are also employed to prove the role PDMS plays in this process. It demonstrated that the acetone selectivity performance comes from the hydrogen bond interaction between the ethanol gas molecules and PDMS, which increases difficulty for ethanol gas molecules to penetrate the PDMS membrane. Further, this work provides a new method for enhancing gas-sensing selectivity and promoting for miniaturization of gas sensors.
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Affiliation(s)
- Tingting Zhou
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Wenbo Dong
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Yue Qiu
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Shiyu Chen
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Xiaoxia Wang
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Changsheng Xie
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
| | - Dawen Zeng
- State Key Laboratory of Material Processing and Die & Mould Technology, Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China
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Liu L, Fei T, Guan X, Zhao H, Zhang T. Highly sensitive and chemically stable NH 3 sensors based on an organic acid-sensitized cross-linked hydrogel for exhaled breath analysis. Biosens Bioelectron 2021; 191:113459. [PMID: 34175649 DOI: 10.1016/j.bios.2021.113459] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/09/2021] [Accepted: 06/19/2021] [Indexed: 12/18/2022]
Abstract
Due to interference by the high moisture content and complicated compositions of human exhaled breath, the trace-level detection of ammonia (NH3) with desirable selectivity and stability is a large challenge for exhaled breath analysis. Carboxyl-sensitized hydrogels can be activated by moisture to exhibit a significant response and excellent selectivity to NH3. However, the high activity of carboxyl groups in hydrogels is a double-edged sword, resulting in poor chemical stability during NH3 detection. Herein, organic acids were embedded into a cross-linked poly(ethylene glycol) diacrylate (PEGDA) hydrogel via thiol-ene photochemistry to form stable hydrogels for NH3 detection in a humid atmosphere. As a result, under high humidity conditions (80% RH), the optimal sensors exhibited superior selectivity to NH3 among various interfering gas species, a remarkably high NH3 response (Za/Zg=6.20) towards 20 ppm NH3, and an extremely low actual detection limit (50 ppb) at room temperature. Moreover, the sensors exhibited excellent chemical stability due to the moderate equilibrium water content of the hydrogel composites and acid dissociation constant of the acid groups. The moisture-activated NH3 sensing mechanism was thoroughly investigated by complex impedance spectroscopy (CIS), quartz crystal microbalance (QCM) measurements, Fourier transform infrared (FT-IR) spectroscopy and X-ray photoelectron spectroscopy (XPS). To explore the application prospects of cross-linked hydrogel sensors for detecting NH3 in exhaled breath, a simulated exhaled breath test was also performed.
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Affiliation(s)
- Lichao Liu
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, PR China; State Key Laboratory of Transducer Technology, Shanghai, 200050, PR China
| | - Teng Fei
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, PR China; State Key Laboratory of Transducer Technology, Shanghai, 200050, PR China
| | - Xin Guan
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, PR China
| | - Hongran Zhao
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, PR China.
| | - Tong Zhang
- State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, PR China.
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Zhang J, Tian Y, Luo Z, Qian C, Li W, Duan Y. Breath volatile organic compound analysis: an emerging method for gastric cancer detection. J Breath Res 2021; 15. [PMID: 34610588 DOI: 10.1088/1752-7163/ac2cde] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 10/05/2021] [Indexed: 12/14/2022]
Abstract
Gastric cancer is a common malignancy, being the fifth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide. Diagnosis of gastric cancer at the early stage is critical to effectively improve the survival rate. However, a substantial proportion of patients with gastric cancer in the early stages lack specific symptoms or are asymptomatic. Moreover, the imaging techniques currently used for gastric cancer screening, such as computed tomography and barium examination, are usually radioactive and have low sensitivity and specificity. Even though endoscopy has high accuracy for gastric cancer screening, its application is limited by the invasiveness of the technique. Breath analysis is an economic, effective, easy to perform, non-invasive detection method, and has no undesirable side effects on subjects. Extensive worldwide research has been conducted on breath volatile organic compounds (VOCs), which reveals its prospect as a potential method for gastric cancer detection. Many interesting results have been obtained and innovative methods have been introduced in this subject; hence, an extensive review would be beneficial. By providing a comprehensive list of breath VOCs identified by gastric cancer would promote further research in this field. This review summarizes the commonly used technologies for exhaled breath analysis, focusing on the application of analytical instruments in the detection of breath VOCs in gastric cancers, and the alterations in the profile of breath biomarkers in gastric cancer patients are discussed as well.
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Affiliation(s)
- Jing Zhang
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Yonghui Tian
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Zewei Luo
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Cheng Qian
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, People's Republic of China
| | - Wenwen Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, People's Republic of China
| | - Yixiang Duan
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
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50
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Liver Impairment-The Potential Application of Volatile Organic Compounds in Hepatology. Metabolites 2021; 11:metabo11090618. [PMID: 34564434 PMCID: PMC8471934 DOI: 10.3390/metabo11090618] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/08/2021] [Accepted: 09/09/2021] [Indexed: 12/20/2022] Open
Abstract
Liver diseases are currently diagnosed through liver biopsy. Its invasiveness, costs, and relatively low diagnostic accuracy require new techniques to be sought. Analysis of volatile organic compounds (VOCs) in human bio-matrices has received a lot of attention. It is known that a musty odour characterises liver impairment, resulting in the elucidation of volatile chemicals in the breath and other body fluids such as urine and stool, which may serve as biomarkers of a disease. Aims: This study aims to review all the studies found in the literature regarding VOCs in liver diseases, and to summarise all the identified compounds that could be used as diagnostic or prognostic biomarkers. The literature search was conducted on ScienceDirect and PubMed, and each eligible publication was qualitatively assessed by two independent evaluators using the SANRA critical appraisal tool. Results: In the search, 58 publications were found, and 28 were kept for inclusion: 23 were about VOCs in the breath, one in the bile, three in urine, and one in faeces. Each publication was graded from zero to ten. A graphical summary of the metabolic pathways showcasing the known liver disease-related VOCs and suggestions on how VOC analysis on liver impairment could be applied in clinical practice are given.
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