Machine Learning Approach for Candida albicans Fluconazole Resistance Detection Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Candida albicans causes life-threatening systemic infections in immunosuppressed patients. These infections are commonly treated with fluconazole, an antifungal agent targeting the ergosterol biosynthesis pathway. Current Antifungal Susceptibility Testing (AFST) methods are time-consuming and are often subjective. Moreover, they cannot reliably detect the tolerance phenomenon, a breeding ground for the resistance. An alternative to the classical AFST methods could use Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass spectrometry (MS). This tool, already used in clinical microbiology for microbial species identification, has already offered promising results to detect antifungal resistance on non-azole tolerant yeasts. Here, we propose a machine-learning approach, adapted to MALDI-TOF MS data, to qualitatively detect fluconazole resistance in the azole tolerant species C. albicans. MALDI-TOF MS spectra were acquired from 33 C. albicans clinical strains isolated from 15 patients. Those strains were exposed for 3 h to 3 fluconazole concentrations (256, 16, 0 μg/mL) and with (5 μg/mL) or without cyclosporin A, an azole tolerance inhibitor, leading to six different experimental conditions. We then optimized a protein extraction protocol allowing the acquisition of high-quality spectra, which were further filtered through two quality controls. The first one consisted of discarding not identified spectra and the second one selected only the most similar spectra among replicates. Quality-controlled spectra were divided into six sets, following the sample preparation's protocols. Each set was then processed through an R based script using pre-defined housekeeping peaks allowing peak spectra positioning. Finally, 32 machine-learning algorithms applied on the six sets of spectra were compared, leading to 192 different pipelines of analysis. We selected the most robust pipeline with the best accuracy. This LDA model applied to the samples prepared in presence of tolerance inhibitor but in absence of fluconazole reached a specificity of 88.89% and a sensitivity of 83.33%, leading to an overall accuracy of 85.71%. Overall, this work demonstrated that combining MALDI-TOF MS and machine-learning could represent an innovative mycology diagnostic tool

Investigating Antifungal Susceptibility in Candida Species With MALDI-TOF MS-Based Assays.

Half of invasive fungal infections lead to death. Amongst pathogenic fungi, the most widespread species belong to the Candida genus and vary in their susceptibility to antifungal drugs. The emergence of antifungal resistance has become a major clinical problem. Therefore, the definition of susceptibility patterns is crucial for the survival of patients and the monitoring of resistance epidemiology. Although, most routinely used methods of AntiFungal Susceptibility Testing (AFST) have reached their limits, the rediscovery of Matrix Associated Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) in the field of mycology provides a promising alternative for the study of antifungal resistance. MALDI-TOF MS is already used in mycology for fungal identification, which permits to highlight inherent antifungal resistance. However, the main concern of clinicians is the rise of acquired antifungal resistance and the time needed for their detection. For this purpose, MALDI-TOF MS has been shown to be an accurate tool for AFST, presenting numerous advantages in comparison to commonly used techniques. Finally, MALDI-TOF MS could be used directly to detect resistance mechanisms through typing. Consequently, MALDI-TOF MS offers new perspectives in the context of healthcare associated outbreaks of emerging multi-drug resistant fungi, such as C. auris. As a proof of concept, we will illustrate the current and future benefits in using and adapting MALDI-TOF MS-based assays to define the susceptibility pattern of C. auris, by species identification, AFST, and typing

Investigating Antifungal Susceptibility in Candida Species With MALDI-TOF MS-Based Assays

Half of invasive fungal infections lead to death. Amongst pathogenic fungi, the most widespread species belong to the Candida genus and vary in their susceptibility to antifungal drugs. The emergence of antifungal resistance has become a major clinical problem. Therefore, the definition of susceptibility patterns is crucial for the survival of patients and the monitoring of resistance epidemiology. Although, most routinely used methods of AntiFungal Susceptibility Testing (AFST) have reached their limits, the rediscovery of Matrix Associated Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) in the field of mycology provides a promising alternative for the study of antifungal resistance. MALDI-TOF MS is already used in mycology for fungal identification, which permits to highlight inherent antifungal resistance. However, the main concern of clinicians is the rise of acquired antifungal resistance and the time needed for their detection. For this purpose, MALDI-TOF MS has been shown to be an accurate tool for AFST, presenting numerous advantages in comparison to commonly used techniques. Finally, MALDI-TOF MS could be used directly to detect resistance mechanisms through typing. Consequently, MALDI-TOF MS offers new perspectives in the context of healthcare associated outbreaks of emerging multi-drug resistant fungi, such as C. auris. As a proof of concept, we will illustrate the current and future benefits in using and adapting MALDI-TOF MS-based assays to define the susceptibility pattern of C. auris, by species identification, AFST, and typing

The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives

This is the final version. Available on open access from Oxford University Press via the DOI in this recordCandida albicans is a major fungal pathogen of humans. It exists as a commensal in the oral cavity, gut or genital tract of most individuals, constrained by the local microbiota, epithelial barriers and immune defences. Their perturbation can lead to fungal outgrowth and the development of mucosal infections such as oropharyngeal or vulvovaginal candidiasis, and patients with compromised immunity are susceptible to life-threatening systemic infections. The importance of the interplay between fungus, host and microbiota in driving the transition from C. albicans commensalism to pathogenicity is widely appreciated. However, the complexity of these interactions, and the significant impact of fungal, host and microbiota variability upon disease severity and outcome, are less well understood. Therefore, we summarise the features of the fungus that promote infection, and how genetic variation between clinical isolates influences pathogenicity. We discuss antifungal immunity, how this differs between mucosae, and how individual variation influences a person's susceptibility to infection. Also, we describe factors that influence the composition of gut, oral and vaginal microbiotas, and how these affect fungal colonisation and antifungal immunity. We argue that a detailed understanding of these variables, which underlie fungal-host-microbiota interactions, will present opportunities for directed antifungal therapies that benefit vulnerable patients

La navigation pédestre dans l'espace public: évaluation des besoins et esquisses de solutions

Ce projet de recherche a été proposé lors de l’appel d’offre 2006 de l’institut Inter qui encourage un travail interdisciplinaire mettant en contact des chercheurs d’horizons divers autour d’un thème commun et au carrefour de quelques disciplines. Les chercheurs rassemblés dans ce projet ont choisi de réfléchir sur une thématique liée à la fois à l’espace public, à la mobilité des personnes et aux aspects technologiques de la navigation. Cette recherche vise donc à construire une approche interdisciplinaire sur les perspectives d’application de la navigation pédestre, en confrontant les points de vue des ingénieurs qui développent des solutions technologiques, ceux des sociologues des comportements de mobilité et ceux des architectes-urbanistes qui conçoivent les espaces publics et de circulation des personnes

Resources-Stratified Guidelines for Classical Hodgkin Lymphoma

Hodgkin lymphoma is a haematological malignancy predominantly affecting young adults. Hodgkin lymphoma is a highly curable disease by current treatment standards. Latest treatment guidelines for Hodgkin lymphoma however imply access to diagnostic and treatment modalities that may not be available in settings with restricted healthcare resources. Considerable discrepancies in Hodgkin lymphoma patient survival exist, with poorer outcomes reported in resources-constrained settings. Resources-stratified guidelines for diagnosis, staging and treatment of Hodgkin lymphoma were derived in an effort to optimize patient outcome provided a given setting of available resources. These guidelines were derived based on the framework of the Breast Health Global Initiative stratifying resource levels in basic, core, advanced and maximal categories