Dataset Information

Identification of a clonal population of Aspergillus flavus by MALDI-TOF mass spectrometry using deep learning.

ABSTRACT: The spread of fungal clones is hard to detect in the daily routines in clinical laboratories, and there is a need for new tools that can facilitate clone detection within a set of strains. Currently, Matrix Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry is extensively used to identify microbial isolates at the species level. Since most of clinical laboratories are equipped with this technology, there is a question of whether this equipment can sort a particular clone from a population of various isolates of the same species. We performed an experiment in which 19 clonal isolates of Aspergillus flavus initially collected on contaminated surgical masks were included in a set of 55 A. flavus isolates of various origins. A simple convolutional neural network (CNN) was trained to detect the isolates belonging to the clone. In this experiment, the training and testing sets were totally independent, and different MALDI-TOF devices (Microflex) were used for the training and testing phases. The CNN was used to correctly sort a large portion of the isolates, with excellent (> 93%) accuracy for two of the three devices used and with less accuracy for the third device (69%), which was older and needed to have the laser replaced.

SUBMITTER: Normand AC

PROVIDER: S-EPMC8799650 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Identification of a clonal population of Aspergillus flavus by MALDI-TOF mass spectrometry using deep learning.

Normand Anne-Cécile AC Chaline Aurélien A Mohammad Noshine N Godmer Alexandre A Acherar Aniss A Huguenin Antoine A Ranque Stéphane S Tannier Xavier X Piarroux Renaud R

Scientific reports 20220128 1

The spread of fungal clones is hard to detect in the daily routines in clinical laboratories, and there is a need for new tools that can facilitate clone detection within a set of strains. Currently, Matrix Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry is extensively used to identify microbial isolates at the species level. Since most of clinical laboratories are equipped with this technology, there is a question of whether this equipment can sort a particular clone from ...[more]

PMID: 35091651

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Project description:Dermatophytoses represent a major health burden in animals and man. Zoophilic dermatophytes usually show a high specificity to their original animal host but a zoonotic transmission is increasingly recorded. In humans, these infections elicit highly inflammatory skin lesions requiring prolonged therapy even in the immunocompetent patient. The correct identification of the causative agent is often crucial to initiate a targeted and effective therapy. To that end, matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) represents a promising tool. The objective of this study was to evaluate the reliability of species identification of zoophilic dermatophytes using MALDI-TOF MS. The investigation of isolates from veterinary clinical samples suspicious of dermatophytoses suggests a good MALDI-TOF MS based identification of the most common zoophilic dermatophyte Microsporum canis. Trichophyton (T.) spp. usually achieved scores only around the cutoff value for secure species identification because of a small number of reference spectra. Moreover, these results need to be interpreted with caution due to the close taxonomic relationship of dermatophytes being reflected in very similar spectra. In our study, the analysis of 50 clinical samples of hedgehogs revealed no correct identification using the provided databases, nor for zoophilic neither for geophilic causative agents. After DNA sequencing, adaptation of sample processing and an individual extension of the in-house database, acceptable identification scores were achieved (T. erinacei and Arthroderma spp., respectively). A score-oriented distance dendrogram revealed clustering of geophilic isolates of four different species of the genus Arthroderma and underlined the close relationship of the important zoophilic agents T. erinacei, T. verrucosum and T. benhamiae by forming a subclade within a larger cluster including different dermatophytes. Taken together, MALDI-TOF MS proofed suitable for the identification of zoophilic dermatophytes provided fresh cultures are used and the reference library was previously extended with spectra of laboratory-relevant species. Performing independent molecular methods, such as sequencing, is strongly recommended to substantiate the findings from morphologic and MALDI-TOF MS analyses, especially for uncommon causative agents.

Project description:A method of analysis is presented that utilizes matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) to monitor the kinetics and products of RNA cleavage, by use of a program designed to mass-match observed MS peaks with predicted RNA cleavage products. The method is illustrated through application to the study of targeted oxidation of RNA stem loops from HIV-1 Rev Response Element mRNA (RRE RNA) and ribosomal 16S A-site RNA (16S RNA) by metallonucleases. Following incubation of each RNA with catalysts and/or redox co-reactants, reaction mixtures were desalted, and MALDI-TOF MS was used to monitor both time-resolved formation of cleavage products and disappearance of full-length RNA. For each RNA, a unique list was generated that contained the predicted masses of both the full-length, and all of the possible RNA cleavage fragments that resulted from the combination of all possible cleavage sites and each of the six expected overhangs formed at nascent termini adjacent to the cleavage sites. The overhangs corresponded to 2',3'-cyclic phosphate, 3'-phosphate, 3'-phosphoglycolate, 5'- hydroxyl and 5'- phosphate, which corresponded to differing oxidative, hydrolytic, and/or 2'-OH-mediated-endonucleolytic modes of scission. Each mass spectrum was compared with a corresponding list of predicted masses, and peaks were rapidly assigned by use of a Perl script, with a mass-matching tolerance of 200 ppm. Both time-dependent cleavage mediated by metallonucleases and MALDI-TOF-induced fragmentation were observed, and these were distinguished by time-dependent experiments. The resulting data allowed a semi-quantitative assessment of the rate of formation of each overhang at each nucleotide position. Limitations included artifactual skewing of quantification by mass bias, a limited mass range for quantification, and a lack of detection of secondary cleavage products. Nevertheless, the method presented herein provides a rapid, accurate, highly-detailed and semi-quantitative analysis of RNA cleavage that should be widely applicable.

Dataset Information

Identification of a clonal population of Aspergillus flavus by MALDI-TOF mass spectrometry using deep learning.

Publications

Identification of a clonal population of Aspergillus flavus by MALDI-TOF mass spectrometry using deep learning.

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