Development of novel mass spectrometric methods for point-of-care mucosal diagnostics

Human mucosal surfaces act as key interfaces between microbiota and host. As such, mucosal sampling using medical swabs is performed for diagnostic purposes that most commonly rely upon subsequent microscopy, culture or molecular-based assays. These approaches are limited in providing information on host response, which is a critical facet of pathology. In this thesis, I sought to test the hypothesis that both presence of specific microbes as well as their interactions with the human host are reflected in the mucosal metabolome and that this information could be exploited for mucosal diagnostic applications. The study aimed to develop a method for rapid, direct metabolic profiling from swabs using desorption electrospray ionisation mass spectrometry (DESI-MS). Method optimisation was conducted to elucidate optimal instrumental and geometrical conditions essential for the swab analysis. The application of the method for mucosal diagnostics was then assessed by characterising the metabolic profile of multiple bodysites (oral, nasal and vaginal mucosa), vaginal mucosa during two different physiological states (non-pregnant vs pregnant) and to detect a pathological state (bacterial vaginosis). Correlation of DESI-MS vaginal metabolic profiles with matched vaginal microbiota composition (VMC) characterised by 16S rRNA-based metataxonomics during pregnancy enabled to robustly predict a Lactobacillus dominant from depleted state but also major vaginal community states types (CST). The predictive performance of DESI-MS based models was comparable to “gold standard” LC-MS based models. Additionally, bacterial metabolite markers predictive of specific microbial genera were identified through matching to a spectral database constructed using pure cultures of commensal and pathogenic microbes often observed in the vaginal microbiome. In summary, DESI-MS has the potential to revolutionise the current way of mucosal based diagnostic by reducing significantly the time-demand needed for the characterisation of VMC, drug or inflammatory response to only few minutes and therefore could enable a faster decision making on patient’s treatment.Open Acces

Intraoperative tissue identification by mass spectrometric technologies

AbstractMass spectrometric (MS) approaches developed for tissue identification in surgical environments are reviewed. MS Imaging (MSI) techniques enable the direct analysis of human tissue and can be used as an alternative means for margin assessment. While MSI-based approaches were demonstrated to improve the examiner-related variance of the data, the time demand and the cost of these analyses remained high. Furthermore, the necessity of MS expertise for the clinical deployment of these techniques has hindered large-scale clinical testing. The advent of ‘ambient’ MS methods contributed to the application of MSI techniques in this field, however alternative methods have been developed for the direct analysis of tissue samples without sample preparation. One group of methods employs surgical tissue manipulation for ionization while the other one uses minimally invasive probes for sampling prior to ionization. The methods are summarised and compared with regard to the information delivered, turnaround time and tissue identification performance

Direct on-swab metabolic profiling of vaginal microbiome host interactions during pregnancy and preterm birth

The pregnancy vaginal microbiome contributes to risk of preterm birth, the primary cause of death in children under 5 years of age. Here we describe direct on-swab metabolic profiling by Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) for sample preparation-free characterisation of the cervicovaginal metabolome in two independent pregnancy cohorts (VMET, n = 160; 455 swabs; VMET II, n = 205; 573 swabs). By integrating metataxonomics and immune profiling data from matched samples, we show that specific metabolome signatures can be used to robustly predict simultaneously both the composition of the vaginal microbiome and host inflammatory status. In these patients, vaginal microbiota instability and innate immune activation, as predicted using DESI-MS, associated with preterm birth, including in women receiving cervical cerclage for preterm birth prevention. These findings highlight direct on-swab metabolic profiling by DESI-MS as an innovative approach for preterm birth risk stratification through rapid assessment of vaginal microbiota-host dynamics

Colocalization Features for Classification of Tumors Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

Supervised modeling of mass spectrometry imaging (MSI) data is a crucial component for the detection of the distinct molecular characteristics of cancerous tissues. Currently, two types of supervised analyses are mainly used on MSI data: pixel-wise segmentation of sample images and whole-sample-based classification. A large number of mass spectra associated with each MSI sample can represent a challenge for designing models that simultaneously preserve the overall molecular content while capturing valuable information contained in the MSI data. Furthermore, intensity-related batch effects can introduce biases in the statistical models. Here we introduce a method based on ion colocalization features that allows the classification of whole tissue specimens using MSI data, which naturally preserves the spatial information associated the with the mass spectra and is less sensitive to possible batch effects. Finally, we propose data visualization strategies for the inspection of the derived networks, which can be used to assess whether the correlation differences are related to coexpression/suppression or disjoint spatial localization patterns and can suggest hypotheses based on the underlying mechanisms associated with the different classes of analyzed samples

Medical Swab Analysis Using Desorption Electrospray Ionization Mass Spectrometry: A Noninvasive Approach for Mucosal Diagnostics

Medical swabs are routinely used worldwide to sample human mucosa for microbiological screening with culture methods. These are usually time-consuming and have a narrow focus on screening for particular microorganism species. As an alternative, direct mass spectrometric profiling of the mucosal metabolome provides a broader window into the mucosal ecosystem. We present for the first time a minimal effort/minimal-disruption technique for augmenting the information obtained from clinical swab analysis with mucosal metabolome profiling using desorption electrospray ionization mass spectrometry (DESI-MS) analysis. Ionization of mucosal biomass occurs directly from a standard rayon swab mounted on a rotating device and analyzed by DESI MS using an optimized protocol considering swab–inlet geometry, tip–sample angles and distances, rotation speeds, and reproducibility. Multivariate modeling of mass spectral fingerprints obtained in this way readily discriminate between different mucosal surfaces and display the ability to characterize biochemical alterations induced by pregnancy and bacterial vaginosis (BV). The method was also applied directly to bacterial biomass to confirm the ability to detect intact bacterial species from a swab. These results highlight the potential of direct swab analysis by DESI-MS for a wide range of clinical applications including rapid mucosal diagnostics for microbiology, immune responses, and biochemistry