Detection of Group B Streptococcus in pregnancy by vaginal volatile organic compound analysis: a prospective exploratory study

GC-IMS facilitates identification of carbapenem-resistant Klebsiella pneumoniae in simulated blood cultures

This study aimed to identify carbapenem-resistant Klebsiella pneumoniae (CRKP) based on changes in levels of its volatile organic compounds (VOCs) in simulated blood cultures (BCs) using the gas chromatography-ion mobility spectrometry (GC-IMS) technique. A comprehensive analysis of volatile metabolites produced by Klebsiella pneumoniae (K. pneumoniae) in BC bottles was conducted using GC-IMS. Subsequently, the released VOCs were analyzed to examine differences in VOC release between CRKP and carbapenem-susceptible Klebsiella pneumoniae (CSKP). A total of 54 VOCs were detected, of which 18 (6 VOCs found in both monomer and dimer forms) were successfully identified. The VOCs produced by K. pneumoniae in BC bottles (BacT/ALERT® SA) were primarily composed of organic acids, alcohols, esters, and ketones. The content of certain VOCs was significantly different between CRKP and CSKP after the addition of imipenem (IPM). Moreover, the inclusion of carbapenemase inhibitors facilitated the identification of carbapenemase-producing K. pneumoniae based on the variations in VOCs. This study demonstrates the utility of GC-IMS technology in identifying CRKP, and reveals that changes in VOCs are closely related to the growth and metabolism of K. pneumoniae, indicating that they can be leveraged to promote early identification of CRKP bacteremia. However, further in-depth studies and experiments are needed to validate our findings.

Modern approaches for detection of volatile organic compounds in metabolic studies focusing on pathogenic bacteria: Current state of the art

Pathogenic microorganisms produce numerous metabolites, including volatile organic compounds (VOCs). Monitoring these metabolites in biological matrices (e.g., urine, blood, or breath) can reveal the presence of specific microorganisms, enabling the early diagnosis of infections and the timely implementation of targeted therapy. However, complex matrices only contain trace levels of VOCs, and their constituent components can hinder determination of these compounds. Therefore, modern analytical techniques enabling the non-invasive identification and precise quantification of microbial VOCs are needed. In this paper, we discuss bacterial VOC analysis under in vitro conditions, in animal models and disease diagnosis in humans, including techniques for offline and online analysis in clinical settings. We also consider the advantages and limitations of novel microextraction techniques used to prepare biological samples for VOC analysis, in addition to reviewing current clinical studies on bacterial volatilomes that address inter-species interactions, the kinetics of VOC metabolism, and species- and drug-resistance specificity.

Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives

Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. KEY POINTS: • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future.

Screening of Chorioamnionitis Using Volatile Organic Compound Detection in Exhaled Breath: A Pre-clinical Proof of Concept Study

Chorioamnionitis is a major risk factor for preterm birth and an independent risk factor for postnatal morbidity for which currently successful therapies are lacking. Emerging evidence indicates that the timing and duration of intra-amniotic infections are crucial determinants for the stage of developmental injury at birth. Insight into the dynamical changes of organ injury after the onset of chorioamnionitis revealed novel therapeutic windows of opportunity. Importantly, successful development and implementation of therapies in clinical care is currently impeded by a lack of diagnostic tools for early (prenatal) detection and surveillance of intra-amniotic infections. In the current study we questioned whether an intra-amniotic infection could be accurately diagnosed by a specific volatile organic compound (VOC) profile in exhaled breath of pregnant sheep. For this purpose pregnant Texel ewes were inoculated intra-amniotically with Ureaplasma parvum and serial collections of exhaled breath were performed for 6 days. Ureaplasma parvum infection induced a distinct VOC-signature in expired breath of pregnant sheep that was significantly different between day 0 and 1 vs. day 5 and 6. Based on a profile of only 15 discriminatory volatiles, animals could correctly be classified as either infected (day 5 and 6) or not (day 0 and 1) with a sensitivity of 83% and a specificity of 71% and an area under the curve of 0.93. Chemical identification of these distinct VOCs revealed the presence of a lipid peroxidation marker nonanal and various hydrocarbons including n-undecane and n-dodecane. These data indicate that intra-amniotic infections can be detected by VOC analyses of exhaled breath and might provide insight into temporal dynamics of intra-amniotic infection and its underlying pathways. In particular, several of these volatiles are associated with enhanced oxidative stress and undecane and dodecane have been reported as predictive biomarker of spontaneous preterm birth in humans. Applying VOC analysis for the early detection of intra-amniotic infections will lead to appropriate surveillance of these high-risk pregnancies, thereby facilitating appropriate clinical course of action including early treatment of preventative measures for pre-maturity-associated morbidities.

Volatile organic compounds (VOCs) for the non-invasive detection of pancreatic cancer from urine

Pancreatic ductal adenocarcinoma (PDAC) is a particularly challenging cancer, with very low 5-year survival rates. This low survival rate is linked to late stage diagnosis, associated with the lack of approved biomarkers. One approach that is receiving considerable attention is the use of volatile organic compounds (VOCs) that emanate from biological waste as biomarkers for disease. In this study, we used urine as our biological matrix and two VOC analysis platforms: gas chromatography - ion mobility spectrometry (GC-IMS) and GC time-of-flight mass spectrometry (GC-TOF-MS). We measured the urinary headspace of samples from patients with PDAC, chronic pancreatitis (CP) and healthy controls. In total, 123 samples were tested from these groups. Results indicate that both GC-IMS and GC-TOF-MS were able to discriminate PDAC from healthy controls with high confidence and an AUC (area under the curve) in excess of 0.85. However, both methods struggled to separate CP from PDAC, with the best result of AUC 0.58. This indicates that both conditions produce similar biomarkers in the urinary headspace. Chemical identification suggests that 2,6-dimethyl-octane, nonanal, 4-ethyl-1,2-dimethyl-benzene and 2-pentanone play an important role in separating these groups. Therefore, both techniques validate this approach in identifying subjects for further investigation in a clinical setting.

Prostate cancer screening using chemometric processing of GC-MS profiles obtained in the headspace above urine samples

The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC-MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.

The Detection of Wound Infection by Ion Mobility Chemical Analysis

Surgical site infection represents a large burden of care in the National Health Service. Current methods for diagnosis include a subjective clinical assessment and wound swab culture that may take several days to return a result. Both techniques are potentially unreliable and result in delays in using targeted antibiotics. Volatile organic compounds (VOCs) are produced by micro-organisms such as those present in an infected wound. This study describes the use of a device to differentiate VOCs produced by an infected wound vs. colonised wound. Malodourous wound dressings were collected from patients, these were a mix of post-operative wounds and vascular leg ulcers. Wound microbiology swabs were taken and antibiotics commenced as clinically appropriate. A control group of soiled, but not malodorous wound dressings were collected from patients who had a split skin graft (SSG) donor site. The analyser used was a G.A.S. GC-IMS. The results from the samples had a sensitivity of 100% and a specificity of 88%, with a positive predictive value of 90%. An area under the curve (AUC) of 91% demonstrates an excellent ability to discriminate those with an infected wound from those without. VOC detection using GC-IMS has the potential to serve as a diagnostic tool for the differentiation of infected and non-infected wounds and facilitate the treatment of wound infections that is cost effective, non-invasive, acceptable to patients, portable, and reliable.