Volatile biomarkers of Gram‑positive bacteria of clinical relevance as a tool for infection diagnosis

Vol.:(0123456789) International Microbiology https://doi.org/10.1007/s10123-024-00511-z RESEARCH Volatile biomarkers ofGram‑positive bacteria ofclinical relevance asatool forinfection diagnosis RicardoRubio‑Sánchez1· EsperanzaLepe‑Balsalobre2· CristinaUbeda3· JoséAntonioLepe‑Jiménez4 Received: 26 September 2023 / Revised: 19 February 2024 / Accepted: 10 March 2024 © The Author(s) 2024 Abstract Aim Volatile organic compounds (VOCs) are being studied as potential biomarkers in many infections. Therefore, this study aimed to analyze the volatile profile of three Gram-positive bacteria of clinical relevance to identify potential volatile biomarkers that allow their differentiation. Methods and results L. monocytogenes, S. aureus, and E. faecalis clinical isolates were inoculated in a thioglycollate medium until grown. Then, VOCs were extracted by solid-phase microextraction, and the data obtained were subjected to multivariate analysis. According to our results, there was a high production of aldehydes in E. faecalis. In the case of alcohols, they only increased in L. monocytogenes, while ketones were produced significantly in all three bacteria, mainly due to acetoin. Acids were produced significantly in E. faecalis and L. monocytogenes. Conclusions Potential biomarkers of L. monocytogenes could be 1-butanol and 2-methylbutanoic acid. In the case of E. faecalis, the VOC most related to its presence was nonanal. Lastly, potential biomarkers of S. aureus could be isoamyl butanoate and methionol, although some pyrazines have also been associated with this bacterium. Significance and impact of the study The identification of potential biomarkers of these clinically relevant bacteria could open the way for the diagnosis of these infections through the analysis of volatile compounds. Keywords Biomarkers· Enterococcus faecalis· Listeria monocytogenes· Staphylococcus aureus· VOC Introduction Infections caused by Gram-positive bacteria are a public health problem due to the outbreaks of food poisoning that it can cause and the worrying increase of bacterial resistance to antibiotics that have been taking place in recent years. Among the Gram-positive bacteria involved in outbreaks of food poisoning, the most notable are Listeria monocytogenes, Bacillus cereus, Staphylococcus aureus, Clostridium perfringens, and Clostridium botulinum. L. monocytogenes causes listeriosis, an infection related to eating contaminated food that affects 1600 people and causes 260 deaths each year worldwide (CDC 2024). Listeriosis is the most severe human foodborne disease due to high hospitalization (99%) and mortality (15.6%) rates (Jiménez etal. 2022). In Spain, in 2019, an outbreak of food poisoning by L. monocytogenes was reported with 217 infected people and three deaths associated with the industrially produced larded meat with the CC388 clonal complex consumption (Ministerio de Sanidad, Consumo y Bienestar Social, 2019). In recent years, the upward trend in the number of outbreaks by Listeria spp., as in the number of hospitalized cases, is worrying (Jiménez etal. 2022). S. aureus also usually causes food poisoning outbreaks by a toxigenic mechanism, giving rise to the sudden appearance of vomiting and diarrhea since preformed enterotoxins are ingested in food (Vila etal. 2009 2008). Between 2019 * Cristina Ubeda [email protected] 1 Servicio de Análisis Clínicos, Hospital Universitario de Jerez de la Frontera, Cádiz, Spain 2 Servicio de Análisis Clínicos, Hospital de Riotinto, Huelva, Spain 3 Departamento de Nutrición y Bromatología, Toxicología y Medicina Legal, Facultad de Farmacia, Universidad de Sevilla, C/ Profesor García González, 2, 41012Seville, Spain 4 Clinical Unit ofInfectious Diseases, Microbiology andPreventive Medicine, Infectious Diseases Research Group, Institute ofBiomedicine ofSeville (IBIS), University ofSeville/CSIC/University Hospital Virgen del Rocío, Seville, Spain International Microbiology and 2020, 121 outbreaks of food poisoning by staphylococcal enterotoxins were reported in Europe, affecting almost 1900 people (Jiménez etal. 2022). In addition, methicillinresistant S. aureus (MRSA), as multiresistant Enterococcus spp., are increasingly causing nosocomial infections due to the appearance of new MRSA clones and mec gene variants that are not detected by the most common molecular systems (Cantón & Ruiz-Garbajosa 2013). The multiresistant bacteria appearance calls for better use of antimicrobials and the application of epidemiological measures, including the detection of carriers, that reduce their transmission. Detection of pathogens in samples from the environment (mainly foods) and patients usually involves time-consuming growth in selective media, isolation, and biochemical and molecular diagnostic analyses (Reichert-Schwillinsky etal. 2009). Thus, currently, the methodologies used to diagnose diseases have been diversified to a great extent. The search for specific disease biomarkers in non-invasive samples is a trend in several research areas. Specifically, volatile organic compounds (VOCs) are being studied as potential biomarkers in many diseases, such as cancer (Wen etal. 2020) and Alzheimer’s disease (Ubeda etal. 2022). Furthermore, microorganisms can produce species-specific VOCs as a product of their metabolism and could also be helpful for the diagnosis of infection as an odor fingerprinting (Tait etal. 2014). Thus, the VOCs produced by microorganisms have been employed successfully to identify their presence in biological samples with Helicobacter pylori (Ulanowska etal. 2011), Giardia lamblia (Ubeda etal. 2019), and SARS-CoV-2 (Lamote etal. 2020), among several others. Specifically, the volatilomic profile of L. monocytogenes has already been studied in thioglycolate broth (Lepe-Balsalobre etal. 2022), trypticase soy broth (Chen etal. 2017), and milk samples (Tait etal. 2014). Regarding S. aureus, the VOCs produced by this bacterium have also been studied in trypticase soy broth (Chen etal. 2017), blood agar media (Gómez-Mejia etal. 2022), and bronchoalveolar lavage fluid (Nasir etal. 2018). This bacterium, like E. faecalis, has also been studied in urine sample (Storer etal. 2011) and blood culture samples (Dolch etal. 2012).Therefore, this study aimed to analyze the volatile profile of the L. monocytogenes clonal complex responsible for the recent and severe outbreak in Spain (CC388) in comparison with that produced by other Gram-positive bacteria of clinical relevance, such as S. aureus and E. faecalis, to identify potential volatile biomarkers that allow their differentiation. Materials andmethods This study was not submitted for institutional review board approval because it did not include individual patient data. Bacterial strains andculture conditions The study included the clinical isolate of Listeria monocytogenes characterized by Multilocus Sequence typing (MLST) belonging to the CC388 clonal complex involved in the epidemic outbreak of 2019 and two clinical isolates of Staphylococcus aureus (ATCC 29213) and Enterococcus faecalis (ATCC 29212) obtained from the American Type Culture Collection (ATCC). A 0.5 McFarland dilution was prepared in sterile water from each isolate (plate count, 1.2 × 108CFU/mL). Then, a technical triplicate 100μl inoculum (1 × 106CFU/mL) was transferred to three fluid thioglycollate medium 20-mL tubes (Becton, Dickinson and Company, USA) and incubated at 37°C for 24h. The positivity was evaluated by bacterial count in Columbia Agar with 5% Sheep Blood (Becton, Dickinson and Company, USA). An uninoculated tube was used as a control. Tubes were stored at − 80°C until analysis. Extraction ofvolatile compounds Solid-phase microextraction (SPME) was employed for the VOC extraction. Tubes were defrosted, and 7.5mL of the media where microorganisms grew was placed in a 20-mL headspace vial joint to 1.5g of NaCl and 10 μL of internal standard (4-methyl-2-pentanol, 0.75mg/L). An MPS Autosampler (Gerstel, USA) incubated the vial for 10min at 45°C with agitation at 300rpm. Then, a 2-cm 50/30μm Carboxen/DVB/PDMS SPME fiber (Supelco, USA) was exposed to the headspace of the vial for 40min. Afterward, fiber was desorbed in the injector in a splitless mode for 3min with the transfer line at a temperature of 250°C. Analyses were performed in an Agilent 8890 GC system coupled to an Agilent 5977B Inert Plus quadrupole mass spectrometer with a Gerstel autosampler (Müllheim an der Ruhr, Germany). The capillary column and flow rate employed were the same as the analysis. The conditions were as follows: the oven temperature program started at 35°C held for 4min, followed by an increase to 220°C at 2.5°C/min held for 1min. For both analyses, electron ionization mass spectra data were recorded from m/z 29–300 in scan mode with an ionization voltage of 70eV. All data were recorded using an MS ChemStation (Agilent Technologies, USA). The VOC identification was done by comparing the mass spectra obtained from each molecule with the reference spectra of the NIST 98 software library and the literature data (Pherobase: www.pherobase.com; NIST Mass Spectrometry Data Center: https:// webbo ok. nist. gov; LRI and Odour database: http:// www. odour. org. uk/ International Microbiology lriin dex. html). When only the software identification was possible, it was treated as tentatively identified. The data showed in this work were expressed as the relative area concerning 4-methyl-2-pentanol (internal standard). The relative concentration was calculated by dividing the peak area of the target ion of each compound by the peak area of the target ion of the internal standard. Statistical analysis The data obtained from the SPME/GC/MS determination were subjected to multivariate analysis performing principal component analysis (PCA) with MetaboAnalyst (Canada). Results Volatile profile characterization ofL. monocytogenes (CC388), E. faecalis, andS. aureus The employment of the SPME technique allowed the identification of 78 VOCs present in thioglycollate media after the growth of the bacteria. It was found that the control medium, without bacteria, presented several volatile compounds (Table1). They were not subtracted from the bacterial culture samples because it is also interesting to observe the decrease in the amount of these compounds in the media since it could be due to volatilization but also to their consumption by these pathogens, which would provide interesting information to understand their metabolism. The metabolic pattern of each microorganism gave rise to different amounts of VOCs of each chemical family found. This first approach shows that the VOC pattern observed in L. monocytogenes is closer to that of E. faecalis than that of S. aureus. Thus, as can be observed in Fig.1, in the culture of S. aureus, the aldehydes had decreased slightly concerning the control. In contrast, the other two bacteria showed significant aldehyde production, with E. faecalis being the most productive. In this study, L. monocytogenes was characterized by the production of alcohols, unlike E. faecalis and S. aureus, which did not vary their total amount concerning the control. Our results showed that all bacteria produce ketones, mainly due to acetoin (Table1). Esters and compounds derived from pyrazine were also determined, detecting most of them in the control medium. Volatile acids were the only chemical group not present in the control medium determined with SPME–GC–MS. E. faecalis, followed by L. monocytogenes, exhibited a remarkable production of volatile acids (Fig.1). The production of volatile acids by S. aureus was significantly lower than the amounts detected in the other bacteria studied. The main difference relied on the short-chain fatty acid (SCFA) production. Thus, acetic, propanoic, and 2-methyl butanoic acids were not detected in the media of S. aureus. In addition, butanoic and hexanoic acids were determined in significantly lower amounts than in the E. faecalis and L. monocytogenes media. Multivariate analysis: principal component analysis A PCA including all the VOCs and the total sum of each chemical group was performed, as shown in Fig.2 (84 variables), to interpret the results obtained from the volatile profile comparison of L. monocytogenes, E. faecalis, and S. aureus. The analysis determined eight principal components (PCs) that explained 87.4% of the total variance, with PC1 and PC2 accounting for 48.8% of the accumulated variance (Fig.3) and permitting a significant separation of the samples. The location in the plane of the samples corroborates that the thioglycollate medium employed for the growth of these bacteria gives rise to similar volatile profiles for L. monocytogenes and E. faecalis, being different to the amounts and types of volatile metabolites resulting for S. aureus growth. Furthermore, it can be observed that acids were clearly correlated with E. faecalis and L. monocytogenes (Fig.2). Discussion Although both E. faecalis and L. monocytogenes produce aldehydes, it is interesting in the first bacterium since it has been little studied. Monedeiro etal. (2021) observed that the volatile profile pattern of E. faecalis was the most common, as it had few unique VOCs compared to Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis. It can be seen in this study that E. faecalis significantly produces benzaldehyde and nonanal, being the only bacterium that generates the latter aldehyde (Table1), so nonanal could be a potential biomarker of its presence in the media. The highest production of alcohols in L. monocytogenes was mainly due to 1-butanol (Table1), a short-chain alcohol that was significantly increased in all clonal complexes of L. monocytogenes (Lepe-Balsalobre etal. 2022). This result contrasts with the findings of Yu etal. (2015) who did not observe 1-butanol among the VOCs produced by L. monocytogenes cultured in TSB. This fact might be due to the culture medium, described as one of the main factors defining the VOCs produced by a microorganism (Tait etal. 2014; Sharma etal. 2017). Isoamyl alcohols (2-methyl- 1-butanol and 3-methyl-1-butanol) were only produced by L. monocytogenes and E. faecalis, again reflecting the proximity between their metabolic systems. This fact agrees with D’Angelo etal. (2020) on another bacterium of the same genus, Enterococcus faecium, where they observed that International Microbiology Table 1 Relative area ranges and linear retention index (LRI) of the volatile organic compounds (VOCs) identified in the thioglycollate media LRI ID Control L. monocytogenes E. faecalis S. aureus 1 ALDEHYDES 2 3-Methylbutanal 939 A 34.7 ± 10.1b 39.8 ± 8.7b 42.8 ± 3.1b 12.8 ± 3.1a 3 Nonanal 1382 A 1.32 ± 0.18a 1.66 ± 0.35a 14.2 ± 0.8b 1.45 ± 0.22a 4 3-(methylthio)propionaldehyde 1455 A 1.82 ± 0.34b 1.89 ± 0.46b 2.31 ± 0.34b NDa 5 Benzaldehyde 1510 A 14.2 ± 2.3a 46.2 ± 13.8b 77.6 ± 19.3c 11.2 ± 2.9a 6 5-Methyl-2-thiophenecarboxaldehyde 1742 A 2.44 ± 0.30a 15.7 ± 3.7b 26.4 ± 3.5c 6.53 ± 1.03a 7 2,5-thiophenedicarboxaldehyde 1798 A 20.7 ± 2.9a 40.2 ± 9.7bc 46.8 ± 1.3c 30.3 ± 5.9ab 8 2-Phenyl-2-butenal 1936 A 0.202 ± 0.029a 0.739 ± 0.222bc 1.15 ± 0.42c 0.286 ± 0.059ab 9 ALCOHOLS 10 Ethanol 958 A 221 ± 20ab 260 ± 17b 189 ± 20a 230 ± 20ab 11 1-Butanol 1151 A 11.9 ± 0.3a 120 ± 12b 22.6 ± 0.5a 14.2 ± 2.2a 12 2-Methyl-1-butanol 1195 A NDa 5.88 ± 0.45c 2.26 ± 0.26b NDa 13 3-Methyl-1-butanol 1198 A NDa 21.3 ± 1.4b 19.7 ± 1.9b NDa 14 5-Methyl-3-hexanol 1231 B 5.94 ± 0.82a 6.57 ± 0.28a 6.17 ± 0.45a 6.48 ± 0.63a 15 6-Methyl-2-heptanol 1380 A 0.525 ± 0.078a 0.578 ± 0.125a 0.915 ± 0.035b 0.581 ± 0.006a 16 3,6-Dimethyl-3-octanol 1434 B 0.753 ± 0.018a 0.788 ± 0.115a 0.778 ± 0.078a 0.748 ± 0.105a 17 1-Heptanol 1459 A 0.961 ± 0.161a 1.70 ± 0.23b 2.16 ± 0.13c 1.07 ± 0.09a 18 Dihydromyrcenol 1473 A 0.673 ± 0.122a 0.932 ± 0.269a 0.868 ± 0.174a 0.958 ± 0.160a 19 5-Methyl-1-heptanol 1535 B 0.382 ± 0.054a 0.405 ± 0.028a 0.435 ± 0.067a 0.348 ± 0.057a 20 1-Octanol 1566 A 2.29 ± 0.56a 3.16 ± 0.27bc 3.39 ± 0.31c 2.44 ± 0.32ab 21 2-Decanol 1586 A 0.554 ± 0.092a 0.742 ± 0.153b 0.973 ± 0.071c 0.535 ± 0.039a 22 Levomenthol 1638 A 0.290 ± 0.097b 0.346 ± 0.013b NDa 0.395 ± 0.121b 23 1-Nonanol 1660 A 1.57 ± 0.28a 3.79 ± 0.75b 4.69 ± 0.36b 1.43 ± 0.09a 24 2-Propyl-1-heptanol 1666 B 0.289 ± 0.043a 0.361 ± 0.067a 0.330 ± 0.014a 0.306 ± 0.023a 25 4-Butoxybutan-1-ol 1704 B 0.086 ± 0.012a 1.06 ± 0.34b 0.906 ± 0.283b 0.172 ± 0.046a 26 2-Undecanol 1725 A 0.316 ± 0.066a 0.535 ± 0.134b 1.55 ± 0.18c 0.277 ± 0.008a 27 Methionol 1728 A 1.08 ± 0.22a 0.821 ± 0.171a 0.733 ± 0.119a 2.80 ± 0.40b 28 1-Decanol 1772 A 1.07 ± 0.18a 1.42 ± 0.12ab 1.72 ± 0.42b 1.19 ± 0.10a 29 3-Acetyl-2.5-dimethylthiophene 1826 A 0.170 ± 0.038a 0.988 ± 0.255ab 1.26 ± 0.23b 0.496 ± 0.142ab 30 3-Methyl-4-(methylthio)phenol 1866 B 1.02 ± 0.09a 1.37 ± 0.40b 1.61 ± 0.13b 1.44 ± 0.24a 31 2-Phenylethanol 1826 A 1.30 ± 0.15a 3.99 ± 0.62c 2.50 ± 0.07b 1.58 ± 0.28a 32 1-Dodecanol 1980 A 2.05 ± 0.30b 1.61 ± 0.05a 1.14 ± 0.13a 1.62 ± 0.19a 33 3-Methylphenol 2080 A 0.203 ± 0.026b NDa NDa 0.223 ± 0.048b 34 1-Hexadecanol 2165 A 0.475 ± 0.071a 0.463 ± 0.116a 0.308 ± 0.051a 0.379 ± 0.118a 35 KETONES 36 Methyl isobutyl ketone 999 A 37.2 ± 3.6b 24.6 ± 2.7a 21.5 ± 2.6a 26.2 ± 4.8a 37 2,6-Dimethyl-4-heptanone 1168 A 11.7 ± 1.1a 13.7 ± 0.9a 13.1 ± 0.7a 11.5 ± 1.1a 38 Acetoin 1271 A 1.72 ± 0.41a 352 ± 13c 449 ± 32d 130 ± 12b 39 Hydroxyacetona 1284 A 3.72 ± 0.89a 5.93 ± 1.31b 5.76 ± 0.78b 5.72 ± 0.66b 40 2-Decanone 1487 A 0.618 ± 0.080b 0.558 ± 0.085b NDa 0.553 ± 0.041b 41 Acetophenone 1635 A 1.95 ± 0.62a 2.23 ± 0.51a 2.44 ± 0.38a 2.11 ± 0.44a 42 2,4,4-Trimethyl-3-(3-methylbutyl)cyclohex-2-enone 1733 A 22.4 ± 4.8a 34.6 ± 6.3b 32.8 ± 8.2ab 26.4 ± 5.9ab 43 Geranylacetone 1852 A 0.574 ± 0.136a 0.793 ± 0.119a 0.645 ± 0.028a 0.734 ± 0.133a 44 2-Acetylpyrrole 1969 A 0.700 ± 0.047a 0.857 ± 0.054ab 0.888 ± 0.024b 0.890 ± 0.026b 45 PYRAZINES 46 Pyrazine 1168 A 33.3 ± 8.7a 31.9 ± 9.3a 28.9 ± 3.5a 33.1 ± 4.6a 47 2-Methylpyrazine 1253 A 25.4 ± 5.5a 26.1 ± 5.8a 26.7 ± 1.6a 28.7 ± 8.2a 48 2,5-Dimethylpyrazine 1320 A 9.37 ± 2.47a 13.6 ± 4.1a 13.2 ± 2.2a 15.4 ± 2.4a 49 2-Ethylpyrazine 1328 A 16.6 ± 2.7a 16.7 ± 2.9a 16.4 ± 1.2a 21.4 ± 5.1a 50 2-Ethyl-6-methylpyrazine 1386 A 7.43 ± 1.02a 8.22 ± 0.77a 8.54 ± 0.61a 9.85 ± 2.26a International Microbiology leucine was converted to the corresponding keto acid before being decarboxylated to 3-methylbutanal, which could later be reduced to 3-methyl-1-butanol or oxidized to 3-meth- ylbutanoic acid. The amount of methionol found in the culture medium of S. aureus was significantly higher compared to the other microorganisms. This increase, together with the disappearance of 3-(methylthio)propionaldehyde (methional) in the case of S. aureus, points to a reduction of 3-(methylthio)propionaldehyde to methionol by the alcohol dehydrogenase activity of this bacteria to metabolize the amino acid methionine. This enzymatic activity has been previously described in other bacteria, such as Oenococcus oeni (Vallet etal. 2009). Table 1 (continued) LRI ID Control L. monocytogenes E. faecalis S. aureus 51 2,3,5-Trimethylpyrazine 1403 A 5.72 ± 1.07a 7.28 ± 2.13a 7.23 ± 0.75a 9.07 ± 1.61a 52 3-Ethyl-2,5-dimethylpyrazine 1444 A 21.3 ± 3.2a 21.1 ± 2.9ab 18.6 ± 3.5a 33.9 ± 8.5b 53 2,6-Diethylpyrazine 1463 A 2.26 ± 0.53a 2.81 ± 0.75a 2.75 ± 0.37a 3.43 ± 0.83a 54 2,3,5,6-Tetramethylpyrazine 1480 A 0.810 ± 0.247a 0.733 ± 0.104a 0.671 ± 0.044a 1.03 ± 0.24a 55 2,3,5-Trimethyl-6-ethylpyrazine 1518 A 2.29 ± 0.13b 1.89 ± 0.13ab 1.67 ± 0.12a 4.38 ± 0.34c 56 2,5-Dimethyl-3-isobutylpyrazine 1530 B 0.772 ± 0.103a 0.751 ± 0.123a 0.767 ± 0.073a 1.49 ± 0.08b 57 2,5-Dimethyl-3-butylpyrazine 1574 A 2.16 ± 0.26a 2.29 ± 0.34a 2.33 ± 0.09a 3.59 ± 0.26b 58 2-Isoamylpyrazine 1585 B 0.657 ± 0.197a 0.744 ± 0.205a 0.715 ± 0.078a 0.983 ± 0.235a 59 2,5-Dimethyl-3-isoamylpyrazine 1656 A 14.4 ± 2.4a 13.3 ± 2.5a 13.1 ± 1.6a 32.5 ± 2.7b 60 ESTERS 61 Isoamyl butyrate 1247 A 0.495 ± 0.042a 0.265 ± 0.073a 0.377 ± 0.037a 7.61 ± 2.51b 62 Isononyl acetate 1392 B 0.491 ± 0.122a 0.825 ± 0.377a 0.310 ± 0.069a 0.549 ± 0.027a 63 Ethyl octanoate 1422 A 0.821 ± 0.026a 1.29 ± 0.16c 1.09 ± 0.08bc 0.912 ± 0.061ab 64 Methyl decanoate 1588 A NDa NDa NDa 0.736 ± 0.173b 65 Furfuryl thioacetate 1759 A NDa 2.34 ± 0.79b 2.37 ± 0.50b NDa 66 Isopropyl dodecanoate 1818 A 0.186 ± 0.021c 0.120 ± 0.012ab 0.105 ± 0.016a 0.141 ± 0.022b 67 2,2-Dimethyl-1-(2-hydroxy-1-methylethyl)propyl 2-methylpropanoate 1881 A 47.9 ± 5.8b 34.7 ± 10.6a 26.1 ± 5.9a 55.1 ± 5.5b 68 ACIDS 69 Acetic acid 1450 A NDa 119 ± 6b 239 ± 12c NDa 70 Propanoic acid 1539 A NDa 5.38 ± 1.03b 6.20 ± 0.09b NDa 71 Butyric acid 1600 A NDa 129 ± 13b 133 ± 5b 1.41 ± 0.54a 72 2-Methylbutanoic acid 1676 B NDa 41.8 ± 3.7b NDa NDa 73 Isobutyric acid 1582 A NDa 25.5 ± 1.1b 24.3 ± 0.4b NDa 74 Hexanoic acid 1872 A NDa 78.1 ± 2.4b 94.7 ± 10.4b 1.57 ± 0.23a 75 Octanoic acid 2073 A NDa 3.09 ± 0.43a 2.35 ± 0.38a 2.26 ± 0.51a 76 Nonanoic acid 2190 A NDa 2.16 ± 0.57b NDa 2.06 ± 0.75a OTHER NITROGEN AND SULFUR COMPOUNDS 77 2,4-Dimethylthiazole 1277 A 1.35 ± 0.34b 1.06 ± 0.19ab 0.513 ± 0.102a 1.29 ± 0.17ab 78 Pyrrole 1501 A 0.942 ± 0.085b NDa NDa NDa 79 2-Propyltetrahydrothiophene 1592 A NDa 1.80 ± 0.49b NDa 4.52 ± 0.45c 80 2-Acetylthiazole 1629 A 3.84 ± 1.11a 11.8 ± 1.3b 13.7 ± 1.1c 3.88 ± 0.67a 81 2-Acetylthiophene 1776 B 2.48 ± 0.36a 2.61 ± 0.49a 2.75 ± 0.16a 3.15 ± 0.99a 82 3-Methyl-2-thiophenecarboxaldehyde 1807 A 2.82 ± 0.59a 4.48 ± 0.68b 5.55 ± 0.29c 4.69 ± 0.57bc 83 2-Methylthieno[2,3-b]thiophene 1897 B 13.1 ± 3.2a 13.2 ± 4.4a 14.7 ± 3.5a 19.8 ± 5.1a 84 Toluene-3,4-dithiol 1986 B 15.5 ± 2.8a 17.1 ± 1.3a 17.2 ± 3.8a 19.3 ± 6.3a Results (average ± SD) are expressed as peak area/100. ND not detected, LRI linear retention index. Values with different superscript letter indicate statistically significant differences by ANOVA Tukey test (p < 0.05). ID: reliability of identification. A: mass spectrum agreed with mass spectral data base and LRI agreed with the literature data (Pherobase: www.pherobase.com; NIST Mass Spectrometry Data Center: https:// webbo ok. nist. gov/; LRI and Odour database: http:// www. odour. org. uk/ lriin dex. html). B: mass spectrum agreed with mass spectral database, but there is no LRI in a polar column reported in the literature. C: mass spectrum agreed with mass spectral data base R.Match ˃ 800 but not with LRI in the literature. Numbers for each compound from the first column correspond to the numeration of Fig.2 International Microbiology As mentioned above, the increase of ketones was mainly due to acetoin. The production of this compound by some microorganisms has been widely described through the acid-mixed fermentation pathway of pyruvate. Chen etal. (2017) pointed out that this ketone production indicated the presence of L. monocytogenes and S. aureus compared to Gram-negative bacteria in the TSB medium. Specifically, Yu etal. (2015) stated that acetoin was the key-com- pound discriminating samples inoculated with L. monocytogenes with an electronic nose. In our study, the highest amount of acetoin in the culture medium was reached by E. faecalis, followed by L. monocytogenes and S. aureus. This fact does not agree with that published by Filipiak etal. (2012), who reported that acetoin meets all the requirements to be a perfect biomarker of S. aureus and shows the great need for more research in this field due to the strong dependence on media and comparison with other bacteria. The acetoin formation causes these bacteria to test positive in the Voges Proskauer test, determining their ability to produce this compound from glucose by butanediol fermentation. This biochemical test is important for the identification of L. monocytogenes and useful as an indicator of its aerobic growth since acetoin is not produced under anaerobic conditions (Romick etal. 1996). The amounts of pyrazine and compounds derived from it were very similar in L. monocytogenes and the control medium, unlike the results obtained by extracting with dichloromethane (Lepe-Balsalobre etal. 2022). This fact could be due to the different extraction methods since, in the study of the Listeria clonal complexes, the extraction was carried out with a polar solvent, which is a more aggressive technique and extracts volatile compounds, but also a lot of non-volatile molecules. Also, the extraction performed in the present study was at 45°C for 50min, while in Lepe etal. (2022) it was done at room temperature, and maybe the extraction and/or formation of these compounds could be favored by high temperatures. In contrast, these compounds were higher in the case of S. aureus, mainly due to the increase of 2,5-dimethyl- 3-isoamylpyrazine. This compound has been previously described in food matrices contaminated with S. aureus (Fang etal. 2021). Fig. 1 Total volatile amounts of the main chemical families determined in thioglycollate culture medium from L. monocytogenes CC388, E. faecalis, and S. aureus. Different letters in the bars indicate differences between the samples (p < 0.05) (Tukey test) International Microbiology Regarding the esters, due to their lability to acid hydrolysis and evaporation, the apparent consumption by L. monocytogenes and E. faecalis was probably not due to their metabolism (Fig.1). However, the data point to a production of esters by S. aureus, especially isoamyl butyrate and methyl decanoate (Table1). The production of esters by S. aureus has already been described (Filipiak etal. 2012), but not that of these VOCs in particular, which seem to be biomarkers of the presence of this pathogen in this medium. The excretion of volatile acids by E. faecalis has already been reported in milk (Delgado etal. 2002). However, the variety of acids determined in this study has not been described for L. monocytogenes. The volatile acid profile revealed that 2-methylbutanoic acid could be a potential biomarker of L. monocytogenes presence (Table1). SCFAs such as acetic, butanoic, and hexanoic acids are commonly associated with anaerobic metabolism. Thus, L. monocytogenes shows a fermentative metabolism due to its beta-d-glucosi- dase activity and generates acids and diacetyl groups from Fig. 2 Data scores and loading biplot on the plane of the first two principal components (PC1 against PC2) of the volatiles from L. monocytogenes CC388, E. faecalis, and S. aureus. Numeration of loadings correspond to each compound from the first column of Table1 Fig. 3 Principal components (PCs) determined by principal component analysis (PCA) that explain different percentages of the total variance International Microbiology sugars such as glucose. A large number of SCFAs have been described in various intestinal diseases, such as that caused by L. monocytogenes (Ishiguro etal. 2017; Di Cagno etal. 2009). However, it has also been reported that fatty acids in Listeria spp. have an important role in resistance against peptidoglycan hydrolases and regulation of virulence (Sun etal. 2012), so they could be involved in the strong pathogenicity and virulence that the CC388 clonal complex presented in the Spanish outbreak in 2019. Some studies have reported the intolerance of S. aureus to SCFAs because they delay and even suppress their growth (Fletcher etal. 2022), and, therefore, this could explain the low contents found in their media. However, 3-methylbuta- noic acid that has been previously reported as a unique volatile compound produced by S. aureus grown in TSB (Chen etal. 2017) and Brain Heart Infusion (BHI) broth (Tait etal. 2014) was not found in our experiments. Multiple growth experiments in defined minimal media have shown that most L. monocytogenes strains require supplementation of the sulfur amino acids methionine and cysteine for growth. This need is explained by the fact that most L. monocytogenes genomes do not express the genes responsible for the sulfate reduction to sulfide, which is subsequently condensed with O-acetylserine to form cysteine (Sauer etal. 2019). The thioglycollate medium contains l-cystine, a dimer of two cysteines linked at their thiol functional groups through a disulfide bond. Some nitrogen and sulfur compounds, such as pyrrole and 2,4-dimethylthi- azole, are probably consumed by bacteria. Others, such as 3 methyl-2-thiophenecarboxaldehyde, could be produced from sulfur sources through cysteine consumption (Walker and Schmitt-Kopplin 2021) or formed from the substrate through the Maillard reaction (cysteine + glucose) due to the heating process for 50min at 45°C during extraction (Umano etal. 1995). In conclusion, the volatile pattern in the thioglycollate medium observed in L. monocytogenes is more similar to that of E. faecalis than that of S. aureus. Potential biomarkers of L. monocytogenes in this medium could be 1-butanol and 2-methylbutanoic acid. In contrast, in the case of E. faecalis, the VOC most related to its presence and, therefore, a potential volatile biomarker could be nonanal. Lastly, potential biomarkers of S. aureus are isoamyl butanoate and methionol, although some pyrazines have also been associated with this bacterium. The detection of these volatile biomarkers reveals the possible presence of a specific microorganism and opens the path for future research in biological samples. However, this is a first approach because biological samples contain, in most cases, multiple bacteria that interact with each other, being able to modify the emission of VOCs that they produce when isolated. Therefore, the next research will be focused on the confirmation using biological samples. Acknowledgements The authors would like to thank the Virgen del Rocío University Hospital Microbiology Laboratory for supplying the samples used in this study, as the “VI Plan Propio de Investigación y Transferencia” of the University of Seville for the current contract of Dr. Cristina Ubeda (USE-18644-Z). Author contributions Ricardo Rubio Sánchez and Esperanza Lepe Balsalobre contributed to sample analysis and manuscript writing. Cristina Ubeda contributed to conception and design, data analysis and, interpretation and manuscript writing. José Antonio Lepe contributed to conception and design and sample collection. Funding Funding for open access publishing: Universidad de Sevilla/ CBUA. Data availability All data can be provided by the corresponding author upon request. Declarations Consent for publication All authors have read and approved the manuscript for publication. Competing interests The authors declare no competing interests. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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