Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.
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Bianconi, E. et al. An estimation of the number of cells in the human body. Ann. Hum. Biol. 40, 463–471 (2013).
Amann, A. et al. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J. Breath Res. 8, 034001 (2014).
de Lacy Costello, B. et al. A review of the volatiles from the healthy human body. J. Breath Res. 8, 014001 (2014).
Broza, Y. Y., Zuri, L. & Haick, H. Combined volatolomics for monitoring of human body chemistry. Sci. Rep. 4, 4611 (2014). This paper reviews the advantages and drawbacks of analysing VOCs for diagnosing and monitoring pathologies.
Giannoukos, S., Agapiou, A., Brkić, B. & Taylor, S. Volatolomics: a broad area of experimentation. J. Chromatogr. B 1105, 136–147 (2019).
Angle, C., Waggoner, L. P., Ferrando, A., Haney, P. & Passler, T. Canine detection of the volatilome: a review of implications for pathogen and disease detection. Front. Vet. Sci. 3, 47 (2016).
Cambau, E. & Poljak, M. Sniffing animals as a diagnostic tool in infectious diseases. Clin. Microbiol. Infect. 26, 431–435 (2020).
Pirrone, F. & Albertini, M. Olfactory detection of cancer by trained sniffer dogs: a systematic review of the literature. J. Vet. Behav. 19, 105–117 (2017).
Agapiou, A., Amann, A., Mochalski, P., Statheropoulos, M. & Thomas, C. L. P. Trace detection of endogenous human volatile organic compounds for search, rescue and emergency applications. Trends Anal. Chem. 66, 158–175 (2015).
Tipple, C. A. et al. Comprehensive characterization of commercially available canine training aids. Forensic Sci. Int. 242, 242–254 (2014).
Ubeda, C., Lepe-Balsalobre, E., Ariza-Astolfi, C. & Ubeda-Ontiveros, J. M. Identification of volatile biomarkers of Giardia duodenalis infection in children with persistent diarrhoea. Parasitol. Res. 118, 3139–3147 (2019).
Dormont, L., Bessière, J.-M. & Cohuet, A. Human skin volatiles: a review. J. Chem. Ecol. 39, 569–578 (2013).
Phillips, M. et al. Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study. Lancet 353, 1930–1933 (1999).
Penn, D. J. et al. Individual and gender fingerprints in human body odour. J. R. Soc. Interface 4, 331–340 (2007).
Al-Kateb, H., de Lacy Costello, B. & Ratcliffe, N. An investigation of volatile organic compounds from the saliva of healthy individuals using headspace-trap/GC-MS. J. Breath Res. 7, 036004 (2013).
Amann, A. et al. Applications of breath gas analysis in medicine. Int. J. Mass Spectrom. 239, 227–233 (2004).
Trefz, P. et al. Exhaled volatile substances in children suffering from type 1 diabetes mellitus: results from a cross-sectional study. Sci. Rep. 9, 15707 (2019).
Nelson, N., Lagesson, V., Nosratabadi, A. R., Ludvigsson, J. & Tagesson, C. Exhaled isoprene and acetone in newborn infants and in children with diabetes mellitus. Pediatr. Res. 44, 363–367 (1998).
Neupane, S. et al. Exhaled breath isoprene rises during hypoglycemia in type 1 diabetes. Diabetes Care 39, e97–e98 (2016).
Mochalski, P. et al. Blood and breath levels of selected volatile organic compounds in healthy volunteers. Analyst 138, 2134–2145 (2013).
Mochalski, P. et al. Blood and breath profiles of volatile organic compounds in patients with end-stage renal disease. BMC Nephrol. 15, 43 (2014).
Filipiak, W. et al. A compendium of volatile organic compounds (VOCs) released by human cell lines. Curr. Med. Chem. 23, 2112–2131 (2016).
Elmassry, M. M. & Piechulla, B. Volatilomes of bacterial infections in humans. Front. Neurosci. 14, 257 (2020).
Serasanambati, M., Broza, Y. Y., Marmur, A. & Haick, H. Profiling single cancer cells with volatolomics approach. iScience 11, 178–188 (2019).
Lawal, O. et al. Headspace volatile organic compounds from bacteria implicated in ventilator-associated pneumonia analysed by TD-GC/MS. J. Breath Res. 12, 026002 (2018).
Filipiak, W. et al. Comparative analyses of volatile organic compounds (VOCs) from patients, tumors and transformed cell lines for the validation of lung cancer-derived breath markers. J. Breath Res. 8, 027111 (2014).
He, J. et al. Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles. Sci. Rep. 4, 5196 (2014).
Martin, A. N., Farquar, G. R., Jones, A. D. & Frank, M. Human breath analysis: methods for sample collection and reduction of localized background effects. Anal. Bioanal. Chem. 396, 739–750 (2010).
Kim, K.-H., Jahan, S. A. & Kabir, E. A review of breath analysis for diagnosis of human health. Trends Anal. Chem. 33, 1–8 (2012).
Lubes, G. & Goodarzi, M. Analysis of volatile compounds by advanced analytical techniques and multivariate chemometrics. Chem. Rev. 117, 6399–6422 (2017).
Schmidt, K. & Podmore, I. Current challenges in volatile organic compounds analysis as potential biomarkers of cancer. J. Biomark. 2015, 981458 (2015).
Lan, H., Hartonen, K. & Riekkola, M.-L. Miniaturised air sampling techniques for analysis of volatile organic compounds in air. Trends Anal. Chem. 126, 115873 (2020).
Lawal, O., Ahmed, W. M., Nijsen, T. M. E., Goodacre, R. & Fowler, S. J. Exhaled breath analysis: a review of ‘breath-taking’ methods for off-line analysis. Metabolomics 13, 110 (2017).
Shende, P., Vaidya, J., Kulkarni, Y. A. & Gaud, R. S. Systematic approaches for biodiagnostics using exhaled air. J. Control. Rel. 268, 282–295 (2017).
Sandlund, J. et al. Development of colorimetric sensor array for diagnosis of tuberculosis through detection of urinary volatile organic compounds. Diagn. Microbiol. Infect. Dis. 92, 299–304 (2018).
Rakow, N. A. & Suslick, K. S. A colorimetric sensor array for odour visualization. Nature 406, 710–713 (2000).
Hu, W. et al. Electronic noses: from advanced materials to sensors aided with data processing. Adv. Mater. Technol. 4, 1800488 (2019).
Geng, Y., Peveler, W. J. & Rotello, V. M. Array-based “chemical nose” sensing in diagnostics and drug discovery. Angew. Chem. Int. Ed. 58, 5190–5200 (2019).
Askim, J. R., Mahmoudi, M. & Suslick, K. S. Optical sensor arrays for chemical sensing: the optoelectronic nose. Chem. Soc. Rev. 42, 8649–8682 (2013).
Iitani, K., Naisierding, M., Toma, K., Arakawa, T. & Mitsubayashi, K. Evaluation for regional difference of skin-gas ethanol and sweat rate using alcohol dehydrogenase-mediated fluorometric gas-imaging system (sniff-cam). Analyst 145, 2915–2924 (2020).
Martinez-Vernon, A. S. et al. An improved machine learning pipeline for urinary volatiles disease detection: diagnosing diabetes. PLoS ONE 13, e0204425 (2018).
Palma, S. I. C. J. et al. Machine learning for the meta-analyses of microbial pathogens’ volatile signatures. Sci. Rep. 8, 3360 (2018).
Tait, E., Perry, J. D., Stanforth, S. P. & Dean, J. R. Use of volatile compounds as a diagnostic tool for the detection of pathogenic bacteria. Trends Anal. Chem. 53, 117–125 (2014).
Turner, A. P. F. & Magan, N. Electronic noses and disease diagnostics. Nat. Rev. Microbiol. 2, 161–166 (2004).
Walzl, G. et al. Tuberculosis: advances and challenges in development of new diagnostics and biomarkers. Lancet Infect. Dis. 18, e199–e210 (2018).
Traxler, S. et al. Volatile scents of influenza A and S. pyogenes (co-)infected cells. Sci. Rep. 9, 18894 (2019).
Purcaro, G. et al. Volatile fingerprinting of human respiratory viruses from cell culture. J. Breath Res. 12, 026015 (2018).
Usman, F. et al. A review of biosensors for non-invasive diabetes monitoring and screening in human exhaled breath. IEEE Access 7, 5963–5974 (2019).
Zhou, J., Huang, Z.-A., Kumar, U. & Chen, D. D. Y. Review of recent developments in determining volatile organic compounds in exhaled breath as biomarkers for lung cancer diagnosis. Anal. Chim. Acta 996, 1–9 (2017).
Sun, X., Shao, K. & Wang, T. Detection of volatile organic compounds (VOCs) from exhaled breath as noninvasive methods for cancer diagnosis. Anal. Bioanal. Chem. 408, 2759–2780 (2016).
Krilaviciute, A. et al. Detection of cancer through exhaled breath: a systematic review. Oncotarget 6, 38643–38657 (2015).
Neerincx, A. H. et al. Breathomics from exhaled volatile organic compounds in pediatric asthma. Pediatr. Pulmonol. 52, 1616–1627 (2017).
Bos, L. D. J. Diagnosis of acute respiratory distress syndrome by exhaled breath analysis. Ann. Transl. Med. 6, 33 (2018).
Smolinska, A. et al. Volatile metabolites in breath strongly correlate with gut microbiome in CD patients. Anal. Chim. Acta 1025, 1–11 (2018).
Trivedi, D. K. et al. Discovery of volatile biomarkers of Parkinson’s disease from sebum. ACS Cent. Sci. 5, 599–606 (2019).
Lau H.-C., Y. J.-B., Lee H. W., Huh J. S. & Lim, J. O. Investigation of exhaled breath samples from patients with Alzheimer’s disease using gas chromatography–mass spectrometry and an exhaled breath sensor system. Sensors 17, 1783 (2017).
Tait, E., Stanforth, S. P., Reed, S., Perry, J. D. & Dean, J. R. Analysis of pathogenic bacteria using exogenous volatile organic compound metabolites and optical sensor detection. RSC Adv. 5, 15494–15499 (2015). First application of VOC-based probes to discriminate between enzyme-producing bacteria in biological samples.
Thompson, R. et al. Detection of β-alanyl aminopeptidase as a biomarker for Pseudomonas aeruginosa in the sputum of patients with cystic fibrosis using exogenous volatile organic compound evolution. RSC Adv. 10, 10634–10645 (2020).
Bahroun, N. H. O., Perry, J. D., Stanforth, S. P. & Dean, J. R. Use of exogenous volatile organic compounds to detect Salmonella in milk. Anal. Chim. Acta 1028, 121–130 (2018). This work describes the use of multiplexed VOC-based probes for biomedicine. This strategy enabled clear detection of a pathogenic strain in food.
Taylor, C. et al. Analysis of Listeria using exogenous volatile organic compound metabolites and their detection by static headspace–multi-capillary column–gas chromatography–ion mobility spectrometry (SHS–MCC–GC–IMS). Anal. Bioanal. Chem. 409, 4247–4256 (2017).
Watkins, P. B. et al. Erythromycin breath test as an assay of glucocorticoid-inducible liver cytochromes P-450. Studies in rats and patients. J. Clin. Invest. 83, 688–697 (1989). This study describes the use of 14C-erythromycin to investigate CYP demethylase activity by measuring breath 14CO2 production after medication. The approach was first tested on rats and then humans.
Chan, L. W. et al. Engineering synthetic breath biomarkers for respiratory disease. Nat. Nanotechnol. 15, 792–800 (2020). This work demonstrates the use of volatile-releasing activity-based nanosensors for assessing in vivo inflammatory response to respiratory bacterial infection.
Douard, V. & Ferraris, R. P. The role of fructose transporters in diseases linked to excessive fructose intake. J. Physiol. 591, 401–414 (2013).
Lange, J. et al. Volatile organic compound (VOC)-based probe for induced volatolomics of cancers. Angew. Chem. Int. Ed. 58, 17563–17566 (2019). This study describes a sugar probe used to diagnose cancers and monitor solid tumour responses to chemotherapy.
Bucci, M., Goodman, C. & Sheppard, T. L. A decade of chemical biology. Nat. Chem. Biol. 6, 847–854 (2010).
Lemke, E. A. & Schultz, C. Principles for designing fluorescent sensors and reporters. Nat. Chem. Biol. 7, 480–483 (2011).
Xu, W. et al. In vivo imaging of a novel strain of Bacteroides fragilis via metabolic labeling. Front. Microbiol. 9, 2298 (2018).
Yang, P. & Liu, K. Activity-based protein profiling: recent advances in probe development and applications. ChemBioChem 16, 712–724 (2015).
Sinharay, S., Randtke, E. A., Howison, C. M., Ignatenko, N. A. & Pagel, M. D. Detection of enzyme activity and inhibition during studies in solution, in vitro and in vivo with CatalyCEST MRI. Mol. Imaging Biol. 20, 240–248 (2018).
Galas, L. et al. “Probe, sample, and instrument (PSI)”: the hat-trick for fluorescence live cell imaging. Chemosensors 6, 40 (2018).
Volpe, A., Kurtys, E. & Fruhwirth, G. O. Cousins at work: how combining medical with optical imaging enhances in vivo cell tracking. Int. J. Biochem. Cell Biol. 102, 40–50 (2018).
Jayanthi, V. S. P. K. S. A., Das, A. B. & Saxena, U. Recent advances in biosensor development for the detection of cancer biomarkers. Biosens. Bioelectron. 91, 15–23 (2017).
Stoddard, E. G. et al. Multifunctional activity-based protein profiling of the developing lung. J. Proteome Res. 17, 2623–2634 (2018).
Hewings, D. S., Flygare, J. A., Wertz, I. E. & Bogyo, M. Activity-based probes for the multicatalytic proteasome. FEBS J. 284, 1540–1554 (2017).
Chang, L., He, X., Chen, L. & Zhang, Y. A novel fluorescent turn-on biosensor based on QDs@GSH–GO fluorescence resonance energy transfer for sensitive glutathione S-transferase sensing and cellular imaging. Nanoscale 9, 3881–3888 (2017).
Yoo, B. et al. Detection of in vivo enzyme activity with CatalyCEST MRI. Magn. Reson. Med. 71, 1221–1230 (2014).
Sabale, S. et al. Recent developments in the synthesis, properties, and biomedical applications of core/shell superparamagnetic iron oxide nanoparticles with gold. Biomater. Sci. 5, 2212–2225 (2017).
Huang, L. et al. Plasmonic silver nanoshells for drug and metabolite detection. Nat. Commun. 8, 220 (2017).
Devaraj, N. K. The future of bioorthogonal chemistry. ACS Cent. Sci. 4, 952–959 (2018).
Graham, D. Y. & Miftahussurur, M. Helicobacter pylori urease for diagnosis of Helicobacter pylori infection: a mini review. J. Adv. Res. 13, 51–57 (2018).
Gaude, E. et al. Targeted breath analysis: exogenous volatile organic compounds (EVOC) as metabolic pathway-specific probes. J. Breath Res. 13, 032001 (2019). This review is the first describing exogenous VOCs as probes for monitoring global metabolic processes.
Simrén, M. & Stotzer, P.-O. Use and abuse of hydrogen breath tests. Gut 55, 297–303 (2006).
Losurdo, G. et al. Breath tests for the non-invasive diagnosis of small intestinal bacterial overgrowth: a systematic review with meta-analysis. J. Neurogastroenterol. Motil. 26, 16–28 (2020).
Calloway, D. H., Murphy, E. L. & Bauer, D. Determination of lactose intolerance by breath analysis. Am. J. Dig. Dis. 14, 811–815 (1969). First clinical work describing an exogenous volatile-based probe for tracing gastrointestinal disorder. The assay highlighted the suitability of lactose as an H2-based probe sugar for diagnosing patients with lactose-intolerance.
Rao, S. S. C., Attaluri, A., Anderson, L. & Stumbo, P. Ability of the normal human small intestine to absorb fructose: evaluation by breath testing. Clin. Gastroenterol. Hepatol. 5, 959–963 (2007).
Ebert, K. & Witt, H. Fructose malabsorption. Mol. Cell. Pediatr. 3, 10 (2016).
Enattah, N. S. et al. Identification of a variant associated with adult-type hypolactasia. Nat. Genet. 30, 233–237 (2002).
Kanai, T. et al. Overproduction of the membrane-bound [NiFe]-hydrogenase in Thermococcus kodakarensis and its effect on hydrogen production. Front. Microbiol. 6, 847 (2015).
Vignais, P. M., Billoud, B. & Meyer, J. Classification and phylogeny of hydrogenases. FEMS Microbiol. Rev. 25, 455–501 (2001).
Gevorgyan, H., Trchounian, A. & Trchounian, K. Understanding the role of Escherichia coli hydrogenases and formate dehydrogenases in the FOF1-ATPase activity during the mixed acid fermentation of mixture of carbon sources. IUBMB Life 70, 1040–1047 (2018).
Huang, G., Wagner, T., Ermler, U. & Shima, S. Methanogenesis involves direct hydride transfer from H2 to an organic substrate. Nat. Rev. Chem. 4, 213–221 (2020).
Rhodes, J. M., Middleton, P. & Jewell, D. P. The lactulose hydrogen breath test as a diagnostic test for small-bowel bacterial overgrowth. Scand. J. Gastroenterol. 14, 333–336 (1979).
Panesar, P. S. & Kumari, S. Lactulose: production, purification and potential applications. Biotechnol. Adv. 29, 940–948 (2011).
Pimentel, M., Chow, E. J. & Lin, H. C. Eradication of small intestinal bacterial overgrowth reduces symptoms of irritable bowel syndrome. Am. J. Gastroenterol. 95, 3503–3506 (2000).
Ghoshal, U. C. How to interpret hydrogen breath tests. J. Neurogastroenterol. Motil. 17, 312–317 (2011).
Choi, Y. K., Johlin, F. C. Jr, Summers, R. W., Jackson, M. & Rao, S. S. C. Fructose intolerance: an under-recognized problem. Am. J. Gastroenterol 98, 1348–1353 (2003).
Erdogan, A., Coss-Adame, E., Yu, S., Rattanakovit, K. & Rao, S. S. C. Optimal testing for diagnosis of fructose intolerance: over-dosage leads to false positive intolerance test. J. Neurogastroenterol. Motil. 20, 560 (2014).
Szilagyi, A. et al. Comparison of a real-time polymerase chain reaction assay for lactase genetic polymorphism with standard indirect tests for lactose maldigestion. Clin. Gastroenterol. Hepatol. 5, 192–196 (2007).
Lin, E. C. & Massey, B. T. Scintigraphy demonstrates high rate of false-positive results from glucose breath tests for small bowel bacterial overgrowth. Clin. Gastroenterol. Hepatol. 14, 203–208 (2016).
Yu, D., Cheeseman, F. & Vanner, S. Combined oro-caecal scintigraphy and lactulose hydrogen breath testing demonstrate that breath testing detects oro-caecal transit, not small intestinal bacterial overgrowth in patients with IBS. Gut 60, 334–340 (2011).
Kerber, M. et al. Hydrogen breath testing versus LCT genotyping for the diagnosis of lactose intolerance: a matter of age? Clin. Chim. Acta 383, 91–96 (2007).
Amieva-Balmori, M., Coss-Adame, E., Rao, N. S., Dávalos-Pantoja, B. M. & Rao, S. S. C. Diagnostic utility of carbohydrate breath tests for SIBO, fructose, and lactose intolerance. Dig. Dis. Sci. 65, 1405–1413 (2020).
Rumessen, J. J., Nordgaard-Andersen, I. & Gudmand-Høyer, E. Carbohydrate malabsorption: quantification by methane and hydrogen breath tests. Scand. J. Gastroenterol. 29, 826–832 (1994).
Sahakian, A. B., Jee, S.-R. & Pimentel, M. Methane and the gastrointestinal tract. Dig. Dis. Sci. 55, 2135–2143 (2010).
Perelló, A. et al. M1249: Methane and hydrogen breath testing for carbohydrate malabsorption. Gastroenterology 138, S-363 (2010).
Materacki, L. et al. PWE-098 Is methane testing a useful adjunct to hydrogen breath testing? Gut 67, A167 (2018).
Harvie, R. M., Tuck, C. J. & Schultz, M. Evaluation of lactulose, lactose, and fructose breath testing in clinical practice: a focus on methane. JGH Open 4, 198–205 (2020).
Enko, D., Rezanka, E., Stolba, R. & Halwachs-Baumann, G. Lactose malabsorption testing in daily clinical practice: a critical retrospective analysis and comparison of the hydrogen/methane breath test and genetic test (C/T−13910 polymorphism) results. Gastroenterol. Res. Pract. 2014, 464382 (2014).
Sundin, O. H. et al. Does a glucose-based hydrogen and methane breath test detect bacterial overgrowth in the jejunum? Neurogastroenterol. Motil. 30, e13350 (2018).
Ghoshal, U. C., Kumar, S., Misra, A. & Mittal, B. Lactose malabsorption diagnosed by 50-g dose is inferior to assess clinical intolerance and to predict response to milk withdrawal than 25-g dose in an endemic area. J. Gastroenterol. Hepatol. 28, 1462–1468 (2013).
Strocchi, A., Corazza, G., Ellis, C. J., Gasbarrini, G. & Levitt, M. D. Detection of malabsorption of low doses of carbohydrate: accuracy of various breath H2 criteria. Gastroenterology 105, 1404–1410 (1993).
Ishibe, A. et al. Detection of gas components as a novel diagnostic method for colorectal cancer. Ann. Gastroenterol. Surg. 2, 147–153 (2018).
Wilder-Smith, C. H., Olesen, S. S., Materna, A. & Drewes, A. M. Breath methane concentrations and markers of obesity in patients with functional gastrointestinal disorders. United European Gastroenterol. J. 6, 595–603 (2017).
Gottlieb, K. et al. Selection of a cut-off for high- and low-methane producers using a spot-methane breath test: results from a large north American dataset of hydrogen, methane and carbon dioxide measurements in breath. Gastroenterol. Rep. 5, 193–199 (2017).
Rubio-Escudero, C. et al. Data mining techniques applied to hydrogen lactose breath test. PLoS ONE 12, e0170385 (2017).
Zhang, J., Cheng, P. & Pu, K. Recent advances of molecular optical probes in imaging of β-galactosidase. Bioconjug. Chem. 30, 2089–2101 (2019).
Begoyan, V. V. et al. Multicolor GLUT5-permeable fluorescent probes for fructose transport analysis. Chem. Commun. 54, 3855–3858 (2018).
Gao, F. et al. Simultaneous detection of hydrogen and methane in breath for the diagnosis of small intestinal bacterial overgrowth by fast gas chromatography. Anal. Methods 10, 4329–4338 (2018).
Newman, A. Breath-analysis tests in gastroenterology. Gut 15, 308–323 (1974).
King, C. E., Toskes, P. P., Spivey, J. C., Lorenz, E. & Welkos, S. Detection of small intestine bacterial overgrowth by means of a 14C-d-xylose breath test. Gastroenterology 77, 75–82 (1979).
Walters, B. & Vanner, S. J. Detection of bacterial overgrowth in IBS using the lactulose H2 breath test: comparison with 14C-d-xylose and healthy controls. Am. J. Gastroenterol. 100, 1566–1570 (2005).
King, C. E. & Toskes, P. P. Comparison of the 1-gram [14C]xylose, 10-gram lactulose-H2, and 80-gram glucose-H2 breath tests in patients with small intestine bacterial overgrowth. Gastroenterology 91, 1447–1451 (1986).
Gunnarsson, M. et al. Long-term biokinetics and radiation exposure of patients undergoing 14C-glycocholic acid and 14C-xylose breath tests. Cancer Biother. Radiopharm. 22, 762–771 (2007).
Wurst, F. M., Skipper, G. E. & Weinmann, W. Ethyl glucuronide — the direct ethanol metabolite on the threshold from science to routine use. Addiction 98, 51–61 (2003).
Bosslet, K. et al. Elucidation of the mechanism enabling tumor selective prodrug monotherapy. Cancer Res. 58, 1195–1201 (1998).
Bosslet, K., Czech, J. & Hoffmann, D. A novel one-step tumor-selective prodrug activation system. Tumor Target. 1, 45–50 (1995).
Fishman, W. H. & Anlyan, A. J. Comparison of the β-glucuronidase activity of normal, tumor, and lymph node tissues of surgical patients. Science 106, 66–67 (1947).
Albin, N. et al. Main drug-metabolizing enzyme systems in human breast tumors and peritumoral tissues. Cancer Res. 53, 3541–3546 (1993).
Sperker, B. et al. Expression and function of β-glucuronidase in pancreatic cancer: potential role in drug targeting. Naunyn-Schmiedeberg’s Arch. Pharmacol. 362, 110–115 (2000).
Renoux, B. et al. Targeting the tumour microenvironment with an enzyme-responsive drug delivery system for the efficient therapy of breast and pancreatic cancers. Chem. Sci. 8, 3427–3433 (2017).
Jin, Y. et al. Highly specific near-infrared fluorescent probe for the real-time detection of β-glucuronidase in various living cells and animals. Anal. Chem. 90, 3276–3283 (2018).
Awolade, P. et al. Therapeutic significance of β-glucuronidase activity and its inhibitors: a review. Eur. J. Med. Chem. 187, 111921 (2020).
Cortadellas, T. et al. Estimation of tumor size in breast cancer comparing clinical examination, mammography, ultrasound and MRI — correlation with the pathological analysis of the surgical specimen. Gland Surg. 6, 330–335 (2017).
Wu, M.-H. et al. Features of non-small cell lung carcinomas overlooked at digital chest radiography. Clin. Radiol. 63, 518–528 (2008).
Mitchell, D. G. et al. Early invasive cervical cancer: tumor delineation by magnetic resonance imaging, computed tomography, and clinical examination, verified by pathologic results, in the ACRIN 6651/GOG 183 intergroup study. J. Clin. Oncol. 24, 5687–5694 (2006).
Cabello, J. & Ziegler, S. I. Advances in PET/MR instrumentation and image reconstruction. Br. J. Radiol. 91, 20160363 (2016).
Marom, E. M., Sarvis, S., Herndon, J. E. & Patz, E. F. T1 lung cancers: sensitivity of diagnosis with fluorodeoxyglucose PET. Radiology 223, 453–459 (2002).
Peng, L. et al. Tissue and plasma proteomics for early stage cancer detection. Mol. Omics 14, 405–423 (2018).
Kałużna-Czaplińska, J. & Jóźwik, J. Current applications of chromatographic methods for diagnosis and identification of potential biomarkers in cancer. Trends Anal. Chem. 56, 1–12 (2014).
Lambin, P. et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat. Rev. Clin. Oncol. 14, 749–762 (2017).
Lee, D.-K. et al. In vitro tracking of intracellular metabolism-derived cancer volatiles via isotope labeling. ACS Cent. Sci. 4, 1037–1044 (2018).
Alahi, E. E. M. & Mukhopadhyay, C. S. Detection methodologies for pathogen and toxins: a review. Sensors 17, 1885 (2017).
Garnacho-Montero, J. et al. Timing of adequate antibiotic therapy is a greater determinant of outcome than are TNF and IL-10 polymorphisms in patients with sepsis. Crit. Care 10, R111 (2006).
Kralik, P. & Ricchi, M. A basic guide to real time PCR in microbial diagnostics: definitions, parameters, and everything. Front. Microbiol. 8, 108 (2017).
Law, J. W.-F., Ab Mutalib, N.-S., Chan, K.-G. & Lee, L.-H. Rapid methods for the detection of foodborne bacterial pathogens: principles, applications, advantages and limitations. Front. Microbiol. 5, 770 (2015).
Chu, Y. W., Wang, B. Y., Engebretson, D. A. & Carey, J. R. Single step, rapid identification of pathogenic microorganisms in a culture bottle. Analyst 138, 5879–5885 (2013).
Guillemot, L.-H., Vrignaud, M., Marcoux, P. R., Rivron, C. & Tran-Thi, T.-H. Facile and fast detection of bacteria via the detection of exogenous volatile metabolites released by enzymatic hydrolysis. Phys. Chem. Chem. Phys. 15, 15840–15844 (2013).
Bedernjak, A. F. et al. Synthesis and evaluation of novel 7- and 8-aminophenoxazinones for the detection of β-alanine aminopeptidase activity and the reliable identification of Pseudomonas aeruginosa in clinical samples. J. Med. Chem. 59, 4476–4487 (2016).
Jokerst, J. C. et al. Development of a paper-based analytical device for colorimetric detection of select foodborne pathogens. Anal. Chem. 84, 2900–2907 (2012).
Orenga, S., James, A. L., Manafi, M., Perry, J. D. & Pincus, D. H. Enzymatic substrates in microbiology. J. Microbiol. Methods 79, 139–155 (2009).
Ramírez-Guízar, S. et al. A chromatographic approach to distinguish Gram-positive from Gram-negative bacteria using exogenous volatile organic compound metabolites. J. Chromatogr. A 1501, 79–88 (2017).
Pham, C. T. N. Neutrophil serine proteases: specific regulators of inflammation. Nat. Rev. Immunol. 6, 541–550 (2006).
Bircher, J. & Preisig, R. Exhalation of isotopic CO2. Methods Enzymol. 77, 3–9 (1981).
Guengerich, F. P. Cytochrome P450 and chemical toxicology. Chem. Res. Toxicol. 21, 70–83 (2008).
Watkins, P. B. Erythromycin breath test and clinical transplantation. Ther. Drug Monit. 18, 368–371 (1996).
Michael, M. et al. Docetaxel pharmacokinetics and its correlation with two in vivo probes for cytochrome P450 enzymes: the C14-erythromycin breath test and the antipyrine clearance test. Cancer Chemother. Pharmacol. 69, 125–135 (2012).
Modak, A. S. Regulatory issues on breath tests and updates of recent advances on [13C]-breath tests. J. Breath Res. 7, 037103 (2013).
Charidemou, E., Ashmore, T. & Griffin, J. L. The use of stable isotopes in the study of human pathophysiology. Int. J. Biochem. Cell Biol. 93, 102–109 (2017).
Bonfrate, L., Grattagliano, I., Palasciano, G. & Portincasa, P. Dynamic carbon 13 breath tests for the study of liver function and gastric emptying. Gastroenterol. Rep. 3, 12–21 (2014).
Hepner, G. W. & Vesell, E. S. Quantitative assessment of hepatic function by breath analysis after oral administration of [14C]aminopyrine. Ann. Intern. Med. 83, 632–638 (1975).
Pijls, K. E. et al. Critical appraisal of 13C breath tests for microsomal liver function: aminopyrine revisited. Liver Int. 34, 487–494 (2014).
Armuzzi, A. et al. Breath testing for human liver function assessment. Aliment. Pharmacol. Ther. 16, 1977–1996 (2002).
Gorowska-Kowolik, K., Chobot, A. & Kwiecien, J. 13C Methacetin breath test for assessment of microsomal liver function: methodology and clinical application. Gastroenterol. Res. Pract. 2017, 7397840 (2017).
Buechter, M., Kersting, S., Gerken, G. & Kahraman, A. Enzymatic liver function measured by LiMAx — a reliable diagnostic and prognostic tool in chronic liver disease. Sci. Rep. 9, 13577 (2019). A thorough evaluation and comparison of the diagnostic and prognostic performance of different non-invasive tools for detecting chronic liver disease. This led to the LiMAx test, which relies on 13C-methacetin, being clinically approved in different countries.
Burke, P. A. et al. l-[1-13C]phenylalanine oxidation as a measure of hepatocyte functional capacity in end-stage liver disease. Am. J. Surg. 173, 270–273 (1997).
Ishii, Y. et al. l-[1-13C]phenylalanine breath test reflects phenylalanine hydroxylase activity of the whole liver. J. Surg. Res. 112, 38–42 (2003).
Saadeh, S. et al. The utility of the 13C-galactose breath test as a measure of liver function. Aliment. Pharmacol. Ther. 18, 995–1002 (2003).
Witschi, A., Mossi, S., Meyer, B., Junker, E. & Lauterburg, B. H. Mitochondrial function reflected by the decarboxylation of [13C]ketoisocaproate is impaired in alcoholics. Alcohol. Clin. Exp. Res. 18, 951–955 (1994).
Palmieri, V. O. et al. Liver function as assessed by breath tests in patients with hepatocellular carcinoma. J. Surg. Res. 157, 199–207 (2009).
Pessayre, D. et al. Central role of mitochondria in drug-induced liver injury. Drug Metab. Rev. 44, 34–87 (2012).
Banasch, M., Ellrichmann, M., Tannapfel, A., Schmidt, W. & Goetze, O. The non-invasive 13C-methionine breath test detects hepatic mitochondrial dysfunction as a marker of disease activity in non-alcoholic steatohepatitis. Eur. J. Med. Res. 16, 258–264 (2011).
Savage, D. B., Petersen, K. F. & Shulman, G. I. Disordered lipid metabolism and the pathogenesis of insulin resistance. Physiol. Rev. 87, 507–520 (2007).
Mizrahi, M., Lalazar, G., Adar, T., Raz, I. & Ilan, Y. Assessment of insulin resistance by a 13C glucose breath test: a new tool for early diagnosis and follow-up of high-risk patients. Nutr. J. 9, 25 (2010).
Hussain, M. et al. [13C]Glucose breath testing provides a noninvasive measure of insulin resistance: calibration analyses against clamp studies. Diabetes Technol. Ther. 16, 102–112 (2013).
Maldonado-Hernández, J., Martínez-Basila, A., Rendón-Macías, M. E. & López-Alarcón, M. Accuracy of the 13C-glucose breath test to identify insulin resistance in non-diabetic adults. Acta Diabetol. 56, 923–929 (2019).
Tanaka, K. et al. Noninvasive assessment of insulin resistance in the liver using the fasting 13C-glucose breath test. Transl. Res. 162, 191–200 (2013).
Graham, D. Y. et al. Campylobacter pylori detected noninvasively by the 13C-urea breath test. Lancet 329, 1174–1177 (1987). First description of the 13C-urea breath test to diagnose Helicobacter pylori infection. This breath test was approved in 2010 and is used clinically worldwide.
Covacci, A., Telford, J. L., Giudice, G. D., Parsonnet, J. & Rappuoli, R. Helicobacter pylori virulence and genetic geography. Science 284, 1328–1333 (1999).
Marshall, B. Helicobacter connections. ChemMedChem 1, 783–802 (2006).
El-Omar, E. M. et al. Interleukin-1 polymorphisms associated with increased risk of gastric cancer. Nature 404, 398–402 (2000).
Graham, D. Y. & Klein, P. D. Accurate diagnosis of Helicobacter pylori: 13C-urea breath test. Gastroenterol. Clin. North Am. 29, 885–893 (2000).
Li, Z.-X. et al. Cut-off optimization for 13C-urea breath test in a community-based trial by mathematic, histology and serology approach. Sci. Rep. 7, 2072 (2017).
Gomollón, F. et al. Breath test is very reliable for diagnosis of Helicobacter pylori infection in real clinical practice. Dig. Liver Dis. 35, 612–618 (2003).
Som, S. et al. Excretion kinetics of 13C-urea breath test: influences of endogenous CO2 production and dose recovery on the diagnostic accuracy of Helicobacter pylori infection. Anal. Bioanal. Chem. 406, 5405–5412 (2014).
Moayyedi, P. et al. Do patients need to fast for a 13C-urea breath test? Eur. J. Gastroenterol. Hepatol. 9, 275–277 (1997).
Eisdorfer, I., Shalev, V., Goren, S., Chodick, G. & Muhsen, K. Sex differences in urea breath test results for the diagnosis of Helicobacter pylori infection: a large cross-sectional study. Biol. Sex. Differ. 9, 1 (2018).
Peng, N.-J. et al. Clinical significance of oral urease in diagnosis of Helicobacter pylori infection by [13C]urea breath test. Dig. Dis. Sci. 46, 1772–1778 (2001).
Cummings, J. H. & Macfarlane, G. T. The control and consequences of bacterial fermentation in the human colon. J. Appl. Bacteriol. 70, 443–459 (1991).
Fenchel, T., King, G. M. & Blackburn, T. H. in Bacterial Biogeochemistry 3rd edn (eds Fenchel, T., King, G. M. & Blackburn, T. H.) 1–34 (Academic Press, 2012).
Houben, E., De Preter, V., Billen, J., Van Ranst, M. & Verbeke, K. Additional value of CH4 measurement in a combined 13C/H2 lactose malabsorption breath test: a retrospective analysis. Nutrients 7, 7469–7485 (2015).
The authors thank the Ligue Contre le Cancer (Comité de la Vienne), the Cancéropôle Grand Sud-Ouest and the Région Nouvelle-Aquitaine for their financial support. They also thank Claude Geffroy for her precious help. Finally, the authors gratefully thank Sébastien Papot for his very wise advice.
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
A chronic condition associated with abnormally high levels of sugar (glucose) in the blood. Insulin produced by the pancreas lowers blood glucose. Absence or insufficient production of insulin, or an inability of the body to properly use insulin, causes diabetes.
- Lactose intolerance
A disease found in approximately 70% of the adult world population that arises because of incomplete intestinal lactose absorption. Symptoms include colicky abdominal pain, flatulence and diarrhoea.
- Small intestinal bacterial overgrowth
(SIBO). SIBO is characterized by an increased concentration of bacteria (>105 colony-forming units per ml) in the upper small intestine. In addition to the absolute number of organisms, the type of microbial flora seems to play an important role in the appearance of signs and symptoms. Although the majority of microbiota in the small bowel are Gram-positive organisms, the flora of patients with SIBO mainly comprises coliform bacteria and anaerobes. These microorganisms can ferment carbohydrates and may produce toxins that damage the intestinal mucous membrane, affecting its absorptive function.
A diagnostic technique in which a 2D picture of internal body tissue is produced through the detection of radiation emitted by a radioactive substance administered into the body.
- Cytochrome P450
(CYP). A CYP is a monooxygenase enzyme with a conserved Phe-X(6−9)-Cys-X-Gly motif near its C terminus. The Cys thiolate binds a haem cofactor, the Fe site of which splits O2. One O atom is converted into H2O, while the other ends up on an organic substrate, with the oxidized product then being released from the enzymatic pocket. High interindividual variation in the activity profiles of these isoforms exist. If an individual is inherently deficient in a CYP or it is inhibited by another drug, toxicity may develop, particularly if drugs accumulate after multiple doses. Drug–drug interactions are a major cause of adverse drug reactions. CYPs themselves can have deleterious effects, converting some chemicals into toxic products that covalently bind enzymes, mitochondrial proteins, RNA, DNA and lipids.
- Insulin resistance
This occurs when a normal or elevated insulin level produces an attenuated biological response. Classically, this refers to impaired sensitivity to insulin-mediated glucose disposal.
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Djago, F., Lange, J. & Poinot, P. Induced volatolomics of pathologies. Nat Rev Chem 5, 183–196 (2021). https://doi.org/10.1038/s41570-020-00248-z