Comprehensive volatile metabolic fingerprinting of bacterial and fungal pathogen groups

Abstract

The identification of pathogen-specific volatile metabolic 'fingerprints' could lead to the rapid identification of disease-causing organisms either directly from ex vivo patient bio-specimens or from in vitro cultures. In the present study, we have evaluated the volatile metabolites produced by 100 clinical isolates belonging to ten distinct pathogen groups that, in aggregate, account for 90% of bloodstream infections, 90% of urinary tract infections, and 80% of infections encountered in the intensive care unit setting. Headspace volatile metabolites produced in vitro were concentrated using headspace solid-phase microextraction and analyzed via two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). A total of 811 volatile metabolites were detected across all samples, of which 203 were: (1) detected in 9 or 10 (of 10) isolates belonging to one or more pathogen groups, and (2) significantly more abundant in cultures relative to sterile media. Network analysis revealed a distinct metabolic fingerprint associated with each pathogen group, and analysis via Random Forest using leave-one-out cross-validation resulted in a 95% accuracy for the differentiation between groups. The present findings support the results of prior studies that have reported on the differential production of volatile metabolites across pathogenic bacteria and fungi, and provide additional insight through the inclusion of pathogen groups that have seldom been studied previously, including Acinetobacter spp., coagulase-negative Staphylococcus, and Proteus mirabilis, as well as the utilization of HS-SPME-GC×GC-TOFMS for improved sensitivity and resolution relative to traditional gas chromatography-based techniques.

Sniffing Out Urinary Tract Infection—Diagnosis Based on Volatile Organic Compounds and Smell Profile

“…Recently, GCxGC-TOF-MS methods were used to discover 28 new P. aeruginosa VOCs as well as confirming 28 former VOCs [86]. This area of research seemed to gain further interest between 2017-2019, since a number of works relating to this topic were published [87][88][89][90][91][92][93]. Most research groups used a metabolite detection approach: GC-MS [87,88], GCxGC-TOF-MS [93], and TD-GC-MS (GC-MS coupled with a thermal desorption, TD, system) [91].…”

“…This area of research seemed to gain further interest between 2017–2019, since a number of works relating to this topic were published [ 87 , 88 , 89 , 90 , 91 , 92 , 93 ]. Most research groups used a metabolite detection approach: GC-MS [ 87 , 88 ], GCxGC-TOF-MS [ 93 ], and TD-GC-MS (GC-MS coupled with a thermal desorption, TD, system) [ 91 ]. DeJong et al identified E. coli in human urine (simulated infection samples) using surface enhanced Raman spectroscopy [ 92 ].…”

Host and Pathogen Communication in the Respiratory Tract: Mechanisms and Models of a Complex Signaling Microenvironment

“…Whereas there exists a substantial amount of information regarding soluble factor signaling and juxtacrine signaling mechanisms, much less is known regarding volatile signaling. Principally regarded as a potential diagnostic for identifying bacterial species in vivo (174)(175)(176), volatile chemicals secreted by microbial species perform multiple functions as both symbiotic and antagonistic factors in complex signaling environments (177)(178)(179)(180); indeed, microbial volatile organic compounds (mVOCs) have been described to play an important role in both intra-and inter-kingdom interactions (180). Additionally, these factors can originate from various microbes and kingdoms, and vary based on the microbial makeup of colonies, as well as the morphological form of microbe (i.e., spore vs. filamentous).…”

“…This beneficial effect on growth and resistance is important for infections where there are multiple distal sites of pathogen colonies, as communication between these locations is not limited by the soluble diffusion-or contact-based signaling required for paracrine and juxtacrine signaling, making it more difficult for the host to intercept or impede these signals. However, much is still unknown regarding the detrimental and antagonistic effects of pathogen-derived volatiles on other pathogens in the lungs, as much of the research has focused on either the positive effects of microbial volatile signaling for pathogen survival, or the use of these volatile signals as diagnostics for bacterial colonization and infection (174,175,187).…”

Influence of the lung microbiome on antibiotic susceptibility of cystic fibrosis pathogens

“…Finally, other non-culture based omics approaches such as metabolomics and metatranscriptomics are receiving increasing attention in the CF microbiome field [100][101][102][103], and may represent interesting tools to monitor microbial community composition and viability in vitro as well. To this end, in-depth comparative studies between these non-culture based and culture-based approaches will be essential to determine their suitability to accurately reflect microbial community content and viability before and after antibiotic treatment.…”