Volatile metabolites of pathogens: a systematic review

Lieuwe D J Bos, Peter J Sterk, Marcus J Schultz, Lieuwe D J Bos, Peter J Sterk, Marcus J Schultz

Abstract

Ideally, invading bacteria are detected as early as possible in critically ill patients: the strain of morbific pathogens is identified rapidly, and antimicrobial sensitivity is known well before the start of new antimicrobial therapy. Bacteria have a distinct metabolism, part of which results in the production of bacteria-specific volatile organic compounds (VOCs), which might be used for diagnostic purposes. Volatile metabolites can be investigated directly in exhaled air, allowing for noninvasive monitoring. The aim of this review is to provide an overview of VOCs produced by the six most abundant and pathogenic bacteria in sepsis, including Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli. Such VOCs could be used as biological markers in the diagnostic approach of critically ill patients. A systematic review of existing literature revealed 31 articles. All six bacteria of interest produce isopentanol, formaldehyde, methyl mercaptan, and trimethylamine. Since humans do not produce these VOCs, they could serve as biological markers for presence of these pathogens. The following volatile biomarkers were found for identification of specific strains: isovaleric acid and 2-methyl-butanal for Staphylococcus aureus; 1-undecene, 2,4-dimethyl-1-heptane, 2-butanone, 4-methyl-quinazoline, hydrogen cyanide, and methyl thiocyanide for Pseudomonas aeruginosa; and methanol, pentanol, ethyl acetate, and indole for Escherichia coli. Notably, several factors that may effect VOC production were not controlled for, including used culture media, bacterial growth phase, and genomic variation within bacterial strains. In conclusion, VOCs produced by bacteria may serve as biological markers for their presence. Goal-targeted studies should be performed to identify potential sets of volatile biological markers and evaluate the diagnostic accuracy of these markers in critically ill patients.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1. Inclusion flow diagram.
Figure 1. Inclusion flow diagram.
The initial search resulted in 837 hits. Fifty-nine were selected based on title and abstract. Full text was read and references were checked for additional hits. This resulted in ten additional hits. Thirty papers were included based on the full text.
Figure 2. Interaction plot.
Figure 2. Interaction plot.
The six investigated pathogenic bacteria are plotted on both sides, with gram-positive bacteria on the left and gram-negative on the right. All the metabolites for which convincing evidence on production by at least one of the bacteria was available (as indicated by a green cell in Tables S1 to S9 in Text S1) were included in the figure and connected with a line to all bacteria known to produce a particular metabolite. The stronger the available evidence for the production of a metabolite by one strain of bacteria, the closer the metabolite is situated to the pathogen. Four zones of interest are highlighted. The blue zone in the middle indicates metabolites that are (almost) always produced by all pathogens and are therefore candidate markers with a high sensitivity that might thus qualify for the exclusion of infection (high negative predictive value). The three red zones indicate metabolites that are produced by only or mainly one strain of bacteria; these are possibly volatile biomarkers specific for a pathogen with a very high positive predictive value.

References

    1. Martin GS, Mannino DM, Eaton S, Moss M (2003) The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 348: 1546–1554.
    1. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, et al. (2006) Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 34: 1589–1596.
    1. Retamar P, Portillo MM, Lopez-Prieto MD, Rodriguez-Lopez F, de Cueto M, et al. (2012) Impact of inadequate empirical therapy on the mortality of patients with bloodstream infections: a propensity score-based analysis. Antimicrob Agents Chemother 56: 472–478.
    1. Grace CJ, Lieberman J, Pierce K, Littenberg B (2001) Usefulness of blood culture for hospitalized patients who are receiving antibiotic therapy. Clin Infect Dis 32: 1651–1655.
    1. Bates DW, Goldman L, Lee TH (1991) Contaminant blood cultures and resource utilization. The true consequences of false-positive results. JAMA 265: 365–369.
    1. O'Horo JC, Thompson D, Safdar N (2012) Is the Gram stain useful in the microbiologic diagnosis of VAP? A Meta-analysis. Clin Infect Dis 55: 551–561.
    1. Veber B, Souweine B, Gachot B, Chevret S, Bedos J-P, et al. (2000) Comparison of direct examination of three types of bronchoscopy specimens used to diagnose nosocomial pneumonia. Crit Care Med 28: 962–968.
    1. Kibe S, Adams K, Barlow G (2011) Diagnostic and prognostic biomarkers of sepsis in critical care. J Antimicrob Chemother 66: ii33–ii40.
    1. Christ-Crain M, Morgenthaler N, Struck J, Harbarth S, Bergmann A, et al. (2005) Mid-regional pro-adrenomedullin as a prognostic marker in sepsis: an observational study. Critical Care 9: R816–R824.
    1. Pierrakos C, Vincent J-L (2011) Sepsis biomarkers: a review. Crit Care 14: R15.
    1. Pletz M, Wellinghausen N, Welte T (2011) Will polymerase chain reaction (PCR)-based diagnostics improve outcome in septic patients? A clinical view. Intensive Care Med 37: 1069–1076.
    1. Nicholson JK, Lindon JC (2008) Systems biology: metabonomics. Nature 455: 1054–1056.
    1. Thorn RM, Reynolds DM, Greenman J (2011) Multivariate analysis of bacterial volatile compound profiles for discrimination between selected species and strains in vitro. J Microbiol Methods 84: 258–264.
    1. Wilson AD, Baietto M (2012) Advances in electronic-nose technologies developed for biomedical applications. Sensors (Basel) 11: 1105–1176.
    1. Schulz S, Dickschat JS (2007) Bacterial volatiles: the smell of small organisms. Nat Prod Rep 24: 814–842.
    1. Röck F, Barsan N, Weimar U (2008) Electronic nose: current status and future trends. Chem Rev 108: 705–725.
    1. Friedrich MJ (2009) Scientists seek to sniff out diseases: electronic “noses” may someday be diagnostic tools. JAMA 301: 585–586.
    1. Smith D, Španěl P (2005) Selected ion flow tube mass spectrometry (SIFT-MS) for on-line trace gas analysis. Mass Spectrom Rev 24: 661–700.
    1. Dolch ME, Frey L, Hornuss C, Schmoelz M, Praun N, et al. (2008) Molecular breath-gas analysis by online mass spectrometry in mechanically ventilated patients: a new software-based method of CO2-controlled alveolar gas monitoring. J Breath Res 2: 037010.
    1. Lirk P, Bodrogi F, Raifer H, Greiner K, Ulmer H, et al. (2003) Elective haemodialysis increases exhaled isoprene. Nephrol Dial Transplant 18: 937–941.
    1. Boots AW, van Berkel JJ, Dallinga JW, Smolinska A, Wouters EF, et al. (2012) The versatile use of exhaled volatile organic compounds in human health and disease. J Breath Res 6: 027108.
    1. Vincent JL, Rello J, Marshall J, Silva E, Anzueto A, et al. (2009) International study of the prevalence and outcomes of infection in intensive care units. JAMA 302: 2323–2329.
    1. Wagner WP, Helmig D, Fall R (1999) Isoprene Biosynthesis in Bacillus subtilis via the methylerythritol phosphate pathway. J Nat Prod 63: 37–40.
    1. Kuzma J, Nemecek-Marshall M, Pollock WH, Fall R (1995) Bacteria produce the volatile hydrocarbon isoprene. Curr Microbiol 30: 97–103.
    1. Schubert JK, Muller WP, Benzing A, Geiger K (1998) Application of a new method for analysis of exhaled gas in critically ill patients. Intensive Care Med 24: 415–421.
    1. Ney P, Boland W (1987) Biosynthesis of 1-alkenes in higher plants. Eur J Biochem 162: 203–211.
    1. Kubo I, Muroi H, Kubo A (1995) Structural functions of antimicrobial long-chain alcohols and phenols. Bioorg Med Chem 3: 873–880.
    1. Zechman JM, Aldinger S, Labows JN Jr (1986) Characterization of pathogenic bacteria by automated headspace concentration–gas chromatography. J Chromatogr 377: 49–57.
    1. Watt B, Geddes PA, Greenan OA, Napier SK, Mitchell A (1982) Gas-liquid chromatography in the diagnosis of anaerobic infections: a three year experience. J Clin Pathol 35: 709–714.
    1. Watt B, Geddes PA, Greenan OA, Napier SK, Mitchell A (1982) Can direct gas-liquid chromatography of clinical samples detect specific organisms? J Clin Pathol 35: 706–708.
    1. Shaw BH (1924) On the production of formaldehyde by intestinal bacteria. BMJ 1: 461–463.
    1. Larsen AG, Knøchel S (1997) Antimicrobial activity of food-related Penicillium sp. against pathogenic bacteria in laboratory media and a cheese model system. J Appl Microbiol 83: 111–119.
    1. Xiao Z, Xu P (2007) Acetoin metabolism in bacteria. Crit Rev Microbiol 33: 127–140.
    1. Chambers ST, Bhandari S, Scott-Thomas A, Syhre M (2010) Novel diagnostics: progress toward a breath test for invasive Aspergillus fumigatus. Med Mycol 49 (Suppl 1) S54–61.
    1. Syhre M, Scotter JM, Chambers ST (2008) Investigation into the production of 2-Pentylfuran by Aspergillus fumigatus and other respiratory pathogens in vitro and human breath samples. Med Mycol 46: 209–215.
    1. Amann A, Miekisch W, Pleil J, Risby T, Schubert J (2010) Methodological issues of sample collection and analysis of exhaled breath. In: Horvath I, de Jongste JC, editors. European Respiratory Society monograph. pp. 96–114.
    1. Holland M, Rhodes G, DalleAve M, Wiesler D, Novotny M (1983) Urinary profiles of volatile and acid metabolites in germfree and conventional rats. Life Sci 32: 787–794.
    1. Yoshimura M, Nakano Y, Yamashita Y, Oho T, Saito T, et al. (2000) Formation of methyl mercaptan from L-methionine by Porphyromonas gingivalis. Infect Immun 68: 6912–6916.
    1. Labows JN, McGinley KJ, Webster GF, Leyden JJ (1980) Headspace analysis of volatile metabolites of Pseudomonas aeruginosa and related species by gas chromatography-mass spectrometry. J Clin Microbiol 12: 521–526.
    1. Scott-Thomas AJ, Syhre M, Pattemore PK, Epton M, Laing R, et al. (2010) 2-aminoacetophenone as a potential breath biomarker for Pseudomonas aeruginosa in the cystic fibrosis lung. BMC Pulm Med 10: 56.
    1. Scott-Thomas A, Pearson J, Chambers S (2011) Potential sources of 2-aminoacetophenone to confound the Pseudomonas aeruginosa breath test, including analysis of a food challenge study. J Breath Res 5: 046002.
    1. Di Martino P, Fursy R, Bret L, Sundararaju B, Phillips RS (2003) Indole can act as an extracellular signal to regulate biofilm formation of Escherichia coli and other indole-producing bacteria. Can J Microbiol 49: 443–449.
    1. Hu M, Zhang C, Mu Y, Shen Q, Feng Y (2010) Indole affects biofilm formation in bacteria. Indian J Microbiol 50: 362–368.
    1. Brooks JB (1977) Detection of bacterial metabolites in spent culture media and body fluids by electron capture gas-liquid chromatography. Adv Chromatogr 15: 1–31.
    1. Anema PJ, Kooiman WJ, Geers JM (1973) Volatile acid production by Clostridium sporogenes under controlled culture conditions. J Appl Bacteriol 36: 683–687.
    1. Hiele M, Ghoos Y, Rutgeerts P, Vantrappen G, Schoorens D (1991) Influence of nutritional substrates on the formation of volatiles by the fecal flora. Gastroenterology 100: 1597–1602.
    1. Scotter JM, Langford VS, Wilson PF, McEwan MJ, Chambers ST (2005) Real-time detection of common microbial volatile organic compounds from medically important fungi by selected ion flow tube-mass spectrometry (SIFT-MS). J Microbiol Methods 63: 127–134.
    1. Filipiak W, Sponring A, Bauer M, Filipiak A, Ager C, et al. (2012) Molecular analysis of volatile metabolites released specifically by Staphylococcus aureus and Pseudomonas aeruginosa. BMC Microbiol 12: 113.
    1. Dolch ME, Hornuss C, Klocke C, Praun S, Villinger J, et al. (2012) Volatile compound profiling for the identification of gram-negative bacteria by ion molecule reaction–mass spectrometry. J Appl Microbiol 113: 1097–1105.
    1. Dolch ME, Hornuss C, Klocke C, Praun S, Villinger J, et al. (2012) Volatile organic compound analysis by ion molecule reaction mass spectrometry for Gram-positive bacteria differentiation. Eur J Clin Microbiol Infect Dis 31: 3007–3013.
    1. Allardyce RA, Langford VS, Hill AL, Murdoch DR (2006) Detection of volatile metabolites produced by bacterial growth in blood culture media by selected ion flow tube mass spectrometry (SIFT-MS). J Microbiol Methods 65: 361–365.
    1. Julak J, Stranska E, Rosova V, Geppert H, Spanel P, et al. (2006) Bronchoalveolar lavage examined by solid phase microextraction, gas chromatography–mass spectrometry and selected ion flow tube mass spectrometry. J Microbiol Methods 65: 76–86.
    1. Julak J, Prochazkova-Francisci E, Stranska E, Rosova V (2003) Evaluation of exudates by solid phase microextraction–gas chromatography. J Microbiol Methods 52: 115–122.
    1. Preti G, Thaler E, Hanson CW, Troy M, Eades J, et al. (2009) Volatile compounds characteristic of sinus-related bacteria and infected sinus mucus: analysis by solid-phase microextraction and gas chromatography–mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 877: 2011–2018.
    1. Fend R, Kolk AH, Bessant C, Buijtels P, Klatser PR, et al. (2006) Prospects for clinical application of electronic-nose technology to early detection of Mycobacterium tuberculosis in culture and sputum. J Clin Microbiol 44: 2039–2045.
    1. Allardyce RA, Hill AL, Murdoch DR (2006) The rapid evaluation of bacterial growth and antibiotic susceptibility in blood cultures by selected ion flow tube mass spectrometry. Diagn Microbiol Infect Dis 55: 255–261.
    1. Dutta R, Hines EL, Gardner JW, Boilot P (2002) Bacteria classification using Cyranose 320 electronic nose. Biomed Eng Online 1: 4.
    1. Carey JR, Suslick KS, Hulkower KI, Imlay JA, Imlay KRC, et al. (2011) Rapid identification of bacteria with a disposable colorimetric sensing array. J Am Chem Soc 133: 7571–7576.
    1. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, et al. (2003) Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. BMJ 326: 41–44.
    1. Savelev SU, Perry JD, Bourke SJ, Jary H, Taylor R, et al. (2011) Volatile biomarkers of Pseudomonas aeruginosa in cystic fibrosis and noncystic fibrosis bronchiectasis. Lett Appl Microbiol 52: 610–613.
    1. Scholpp J, Schubert JK, Miekisch W, Geiger K (2002) Breath markers and soluble lipid peroxidation markers in critically ill patients. Clin Chem Lab Med 40: 587–594.
    1. Human Microbiome Project Consortium (2012) Structure, function and diversity of the healthy human microbiome. Nature 486: 207–214.
    1. Hilty M, Burke C, Pedro H, Cardenas P, Bush A, et al. (2010) Disordered microbial communities in asthmatic airways. PLoS ONE 5: e8578 doi:.
    1. Hakim M, Broza YY, Barash O, Peled N, Phillips M, et al. (2012) Volatile organic compounds of lung cancer and possible biochemical pathways. Chem Rev 112: 5949–5966.
    1. Hayward NJ, Jeavons TH, Nicholson AJ, Thornton AG (1977) Development of specific tests for rapid detection of Escherichia coli and all species of Proteus in urine. J Clin Microbiol 6: 195–201.
    1. Cox CD, Parker J (1979) Use of 2-aminoacetophenone production in identification of Pseudomonas aeruginosa. J Clin Microbiol 9: 479–484.
    1. Davies T, Hayward NJ (1984) Volatile products from acetylcholine as markers in the rapid urine test using head-space gas-liquid chromatography. J Chromatogr 307: 11–21.
    1. Scholler C, Molin S, Wilkins K (1997) Volatile metabolites from some gram-negative bacteria. Chemosphere 35: 1487–1495.
    1. Julak J, Stranska E, Prochazkova-Francisci E, Rosova V (2000) Blood cultures evaluation by gas chromatography of volatile fatty acids. Med Sci Monit 6: 605–610.
    1. Carroll W, Lenney W, Wang T, Spanel P, Alcock A, et al. (2005) Detection of volatile compounds emitted by Pseudomonas aeruginosa using selected ion flow tube mass spectrometry. Pediatr Pulmonol 39: 452–456.
    1. Hamilton-Kemp T, Newman M, Collins R, Elgaali H, Yu K, et al. (2005) Production of the long-chain alcohols octanol, decanol, and dodecanol by Escherichia coli. Curr Microbiol 51: 82–86.
    1. Scotter JM, Allardyce RA, Langford VS, Hill A, Murdoch DR (2006) The rapid evaluation of bacterial growth in blood cultures by selected ion flow tube–mass spectrometry (SIFT-MS) and comparison with the BacT/ALERT automated blood culture system. J Microbiol Methods 65: 628–631.
    1. Bunge M, Araghipour N, Mikoviny T, Dunkl J, Schnitzhofer R, et al. (2008) On-line monitoring of microbial volatile metabolites by proton transfer reaction-mass spectrometry. Appl Environ Microbiol 74: 2179–2186.
    1. Maddula S, Blank LM, Schmid A, Baumbach JI (2009) Detection of volatile metabolites of Escherichia coli by multi capillary column coupled ion mobility spectrometry. Anal Bioanal Chem 394: 791–800.
    1. Zhu J, Bean HD, Kuo YM, Hill JE (2010) Fast detection of volatile organic compounds from bacterial cultures by secondary electrospray ionization-mass spectrometry. J Clin Microbiol 48: 4426–4431.
    1. Shestivska V, Nemec A, Drevinek P, Sovova K, Dryahina K, et al. (2011) Quantification of methyl thiocyanate in the headspace of Pseudomonas aeruginosa cultures and in the breath of cystic fibrosis patients by selected ion flow tube mass spectrometry. Rapid Commun Mass Spectrom 25: 2459–2467.
    1. Storer MK, Hibbard-Melles K, Davis B, Scotter J (2011) Detection of volatile compounds produced by microbial growth in urine by selected ion flow tube mass spectrometry (SIFT-MS). J Microbiol Methods 87: 111–113.
    1. Bean HD, Dimandja JM, Hill JE (2012) Bacterial volatile discovery using solid phase microextraction and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 901: 41–46.
    1. Junger M, Vautz W, Kuhns M, Hofmann L, Ulbricht S, et al. (2012) Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria. Appl Microbiol Biotechnol 93: 2603–2614.

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren