scholarly journals Optimization and Standardization of Human Saliva Collection for MALDI-TOF MS

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1304
Author(s):  
Monique Melo Costa ◽  
Nicolas Benoit ◽  
Florian Saby ◽  
Bruno Pradines ◽  
Samuel Granjeaud ◽  
...  
Keyword(s):  
Low Cost ◽  
Storage Conditions ◽  
Human Saliva ◽  
Learning Approaches ◽  
Sample Collection ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Key Factor ◽  
Diagnosis Method ◽  
Tof Ms

SARS-CoV-2 outbreak led to unprecedented innovative scientific research to preclude the virus dissemination and limit its impact on life expectancy. Waiting for the collective immunity by vaccination, mass-testing, and isolation of positive cases remain essential. The development of a diagnosis method requiring a simple and non-invasive sampling with a quick and low-cost approach is on demand. We hypothesized that the combination of saliva specimens with MALDI-TOF MS profiling analyses could be the winning duo. Before characterizing MS saliva signatures associated with SARS-CoV-2 infection, optimization and standardization of sample collection, preparation and storage up to MS analyses appeared compulsory. In this view, successive experiments were performed on saliva from healthy healthcare workers. Specimen sampling with a roll cotton of Salivette® devices appeared the most appropriate collection mode. Saliva protein precipitation with organic buffers did not improved MS spectra profiles compared to a direct loading of samples mixed with acetonitrile/formic acid buffer onto MS plate. The assessment of sample storage conditions and duration revealed that saliva should be stored on ice until MS analysis, which should occur on the day of sampling. Kinetic collection of saliva highlighted reproducibility of saliva MS profiles over four successive days and also at two-week intervals. The intra-individual stability of saliva MS profiles should be a key factor in the future investigation for biomarkers associated with SARS-CoV-2 infection. However, the singularity of MS profiles between individuals will require the development of sophisticated bio-statistical analyses such as machine learning approaches. MALDI-TOF MS profiling of saliva could be a promising PCR-free tool for SARS-CoV-2 screening.

scholarly journals Spectral Grouping of Nominally Aspergillus versicolor Microbial-Collection Deposits by MALDI-TOF MS

2019 ◽  
Vol 7 (8) ◽  
pp. 235
Author(s):  
Reeve ◽  
Caine ◽  
Buddie
Keyword(s):  
Low Cost ◽  
Resolving Power ◽  
Indoor Environments ◽  
Aspergillus Versicolor ◽  
Taxonomic Assignment ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Resource Collection ◽  
Tof Ms

Historical microbial collections often contain samples that have been deposited over extended time periods, during which accepted taxonomic classification (and also available methods for taxonomic assignment) may have changed considerably. Deposited samples can, therefore, have historical taxonomic assignments (HTAs) that may now be in need of revision, and subdivisions of previously-accepted taxa may also be possible with the aid of current methodologies. One such methodology is matrix-assisted laser-desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS). Motivated by the high discriminating power of MALDI-TOF MS coupled with the speed and low cost of the method, we have investigated the use of MALDI-TOF MS for spectral grouping of past deposits made to the Centre for Agriculture and Bioscience International (CABI) Genetic Resource Collection under the HTA Aspergillus versicolor, a common ascomycete fungus frequently associated with soil and plant material, food spoilage, and damp indoor environments. Despite their common HTA, the 40 deposits analyzed in this study fall into six clear spectral-linkage groups (containing nine, four, four, four, four, and two members, respectively), along with a group of ten spectrally-unique samples. This study demonstrates the clear resolving power of MALDI-TOF MS when applied to samples deposited in historical microbial collections.

scholarly journals Rapid classification and prediction of COVID-19 severity by MALDI-TOF mass spectrometry analysis of serum peptidome

2020 ◽  
Author(s):  
Rosa M. Gomila ◽  
Gabriel Martorell ◽  
Pablo A. Fraile-Ribot ◽  
Antonio Doménech-Sánchez ◽  
Antonio Oliver ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Favourable Outcome ◽  
Mass Spectrometry Analysis ◽  
Learning Approaches ◽  
Maldi Tof Ms ◽  
Spectrometry Analysis ◽  
Maldi Tof ◽  
Critical Patients ◽  
Tof Ms

ABSTRACTClassification and early detection of severe COVID-19 patients is urgently required to establish an effective treatment. Here, we tested the utility of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to classify and predict the severity of COVID-19 in a clinical setting. We used this technology to analyse the mass spectra profiles of the sera from 80 COVID-19 patients, clinically classified as mild (33), severe (26) and critical (21), and 20 healthy controls. We found a clear variability of the serum peptidome profile depending on COVID-19 severity. Seventy-eight peaks were significantly different and 12 at least four fold more intense in the set of critical patients than in the mild ones. Analysis of the resulting matrix of peak intensities by machine learning approaches classified severe (severe and critical) and non-severe (mild) patients with a 90% of accuracy. Furthermore, machine learning predicted correctly the favourable outcome of the severe patients in 85% of the cases and the unfavourable in 38% of the cases. Finally, liquid chromatography mass spectrometry analysis of sera identified five proteins that were significantly upregulated in the critical patients. They included serum amyloid proteins A1 and A2, which probably yielded the most intense peaks with m/z 11,530 and 11,686 detected by MALDI-TOF MS.In summary, we demonstrated the potential of the MALDI-TOF MS as a bench to bedside technology to aid clinicians in their decisions to classify COVID-19 patients and predict their evolution.

A brief identification of lactic acid bacteria isolated from Algerian goat’s Jben by MALDI-TOF MS

2018 ◽  
Vol 7 (4) ◽  
pp. 157-165
Author(s):  
Naïma L. Meghoufel ◽  
Abdelkader Homrani ◽  
Saïd Nemmiche ◽  
Nawel Benkrizi ◽  
Abdelkader E. Dahou ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Low Cost ◽  
Raw Milk ◽  
Ionization Time ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Sub Saharan ◽  
Tof Ms

In this paper, we investigated the lactic acid bacteria’s community of the Algerian goat’s Jben in order to define and preserve it. This cheese variety is only handmade with raw milk, and a dried flower of Cynara cardunculus is used instead of the animal rennet, it is also restricted in sub-Saharan prov-inces in Algeria, and no previous studies on its lactic acid bacteria composi-tion have been performed before. Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) procedure was used to identify 36 lactic acid bacteria isolated from artisanal Jben made from Arabia goat’s raw milk in Naâma (Algeria). The results showed the domination of the Enterococcus genus presents with four species: E. durans, E. faecalis, E. hirae and E. faecium. Lactococcus lactis and Leuconostoc mesenteroïdes were also detected. The species identified were favoured by the composition of goat’s raw milk microflora used and the artisanal manufacturing process of the cheese. The use of MALDI-TOF MS method provided us with a rapid diagnosis of the Jben lactic acid bacteria’s community. This method based on microbial abundant proteins fingerprint diagnosis was chosen for its fast, precise, low cost and less complicated analyse.

scholarly journals Exploratory Study on Application of MALDI-TOF-MS to Detect SARS-CoV-2 Infection in Human Saliva

2022 ◽  
Vol 11 (2) ◽  
pp. 295
Author(s):  
Monique Melo Costa ◽  
Hugo Martin ◽  
Bertrand Estellon ◽  
François-Xavier Dupé ◽  
Florian Saby ◽  
...  
Keyword(s):  
Human Saliva ◽  
Classification Performance ◽  
Training Dataset ◽  
Support Vector ◽  
Nasopharyngeal Swab ◽  
Correct Classification ◽  
Specific Test ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Tof Ms

SARS-CoV-2 has caused a large outbreak since its emergence in December 2019. COVID-19 diagnosis became a priority so as to isolate and treat infected individuals in order to break the contamination chain. Currently, the reference test for COVID-19 diagnosis is the molecular detection (RT-qPCR) of the virus from nasopharyngeal swab (NPS) samples. Although this sensitive and specific test remains the gold standard, it has several limitations, such as the invasive collection method, the relative high cost and the duration of the test. Moreover, the material shortage to perform tests due to the discrepancy between the high demand for tests and the production capacities puts additional constraints on RT-qPCR. Here, we propose a PCR-free method for diagnosing SARS-CoV-2 based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling and machine learning (ML) models from salivary samples. Kinetic saliva samples were collected at enrollment and ten and thirty days later (D0, D10 and D30), to assess the classification performance of the ML models compared to the molecular tests performed on NPS specimens. Spectra were generated using an optimized protocol of saliva collection and successive quality control steps were developed to ensure the reliability of spectra. A total of 360 averaged spectra were included in the study. At D0, the comparison of MS spectra from SARS-CoV-2 positive patients (n = 105) with healthy healthcare controls (n = 51) revealed nine peaks that significantly distinguished the two groups. Among the five ML models tested, support vector machine with linear kernel (SVM-LK) provided the best performance on the training dataset (accuracy = 85.2%, sensitivity = 85.1%, specificity = 85.3%, F1-Score = 85.1%). The application of the SVM-LK model on independent datasets confirmed its performances with 88.9% and 80.8% of correct classification for samples collected at D0 and D30, respectively. Conversely, at D10, the proportion of correct classification had fallen to 64.3%. The analysis of saliva samples by MALDI-TOF MS and ML appears as an interesting supplementary tool for COVID-19 diagnosis, despite the mitigated results obtained for convalescent patients (D10).

scholarly journals Exploratory Study on Application of MALDI-TOF-MS to Detect SARS-CoV-2 Infection in Human Saliva

2021 ◽  
Author(s):  
Monique Melo Costa ◽  
Hugo Martin ◽  
Bertrand Estellon ◽  
François-Xavier Dupé ◽  
Floriant Saby ◽  
...  
Keyword(s):  
Human Saliva ◽  
Classification Performance ◽  
Training Dataset ◽  
Support Vector ◽  
Nasopharyngeal Swab ◽  
Correct Classification ◽  
Specific Test ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Tof Ms

SARS-CoV-2 caused a large outbreak since its emergence in December 2019. The COVID-19 diagnosis became a priority to isolate and treat infected individuals in order to break the contamination chain. Currently, the reference test for COVID-19 diagnosis is the molecular detection (RT-qPCR) of the virus from nasopharyngeal swab (NPS) samples. Although this sensitive and specific test remains the gold standard, it has several limitations, such as the invasive collection method, the relative high cost and the duration of the test. Moreover, the material shortage to perform tests due to the discrepancy between the high demand for tests and the production capacities puts additional constraints on RT-qPCR. Here, we propose a PCR-free method for diagnosing SARS-CoV-2 based on Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling and machine learning (ML) models from salivary samples. Kinetic saliva samples were collected at enrollment and ten and thirty days later (D0, D10 and D30), to assess the classification performance of the ML models compared to the molecular tests performed on NPS specimens. Spectra were generated using an optimized protocol of saliva collection and successive quality control steps were developed to ensure the reliability of spectra. A total of 360 averaged spectra were included in the study. At D0, the comparison of MS spectra from SARS-CoV-2 positive patients (n=105) with healthy healthcare controls (n=51) revealed nine peaks that significantly distinguished the two groups. Among the five ML models tested, Support Vector Machine with Linear Kernel (SVM-LK) provided the best performance on the training dataset (accuracy = 85.2 %, sensitivity = 85.1 %, specificity = 85.3 %, F1-Score = 85.1 %). The application of the SVM-LK model on independent datasets confirmed it performances with 88.9% and 80.8% of correct classification for samples collected at D0 and D30, respectively. Conversely, at D10, the proportion of correct classification fallen to 64.3%. The analysis of saliva samples by MALDI-TOF MS and ML appears as an interesting supplementary tool for COVID-19 diagnosis, despite the mitigated results obtained for convalescent patients (D10).

Influence of storage conditions on MALDI-TOF MS profiling of gingival crevicular fluid: Implications on the role of S100A8 and S100A9 for clinical and proteomic based diagnostic investigations

PROTEOMICS ◽  
2016 ◽  
Vol 16 (6) ◽  
pp. 1033-1045 ◽  
Author(s):  
Mariaimmacolata Preianò ◽  
Giuseppina Maggisano ◽  
Nicola Lombardo ◽  
Tiziana Montalcini ◽  
Sergio Paduano ◽  
...  
Keyword(s):  
Gingival Crevicular Fluid ◽  
Storage Conditions ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Crevicular Fluid ◽  
Tof Ms ◽  
Diagnostic Investigations

Comparative analysis of storage conditions and homogenization methods for tick and flea species for identification by MALDI-TOF MS

2017 ◽  
Vol 31 (4) ◽  
pp. 438-448 ◽  
Author(s):  
A. NEBBAK ◽  
B. EL HAMZAOUI ◽  
J.-M. BERENGER ◽  
I. BITAM ◽  
D. RAOULT ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Storage Conditions ◽  
Flea Species ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Homogenization Methods ◽  
Tof Ms

scholarly journals MALDI-TOF MS as a method for rapid identification of Phytophthora de Bary, 1876

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11662
Author(s):  
Matěj Božik ◽  
Marcela Mrázková ◽  
Karolína Novotná ◽  
Markéta Hrabětová ◽  
Petr Maršik ◽  
...  
Keyword(s):  
Low Cost ◽  
Rapid Identification ◽  
Genetic Identification ◽  
Anthropogenic Habitats ◽  
Ionization Time ◽  
Maldi Tof Ms ◽  
Complementary Method ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Tof Ms

The number of described species of the oomycete genus Phytophthora is growing rapidly, highlighting the need for low-cost, rapid tools for species identification. Here, a collection of 24 Phytophthora species (42 samples) from natural as well as anthropogenic habitats were genetically identified using the internal transcribed spacer (ITS) and cytochrome c oxidase subunit I (COI) regions. Because genetic identification is time consuming, we have created a complementary method based on by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Both methods were compared and hypothesis that the MALDI-TOF MS method can be a fast and reliable method for the identification of oomycetes was confirmed. Over 3500 mass spectra were acquired, manually reviewed for quality control, and consolidated into a single reference library using the Bruker MALDI Biotyper platform. Finally, a database containing 144 main spectra (MSPs) was created and published in repository. The method presented in this study will facilitate the use of MALDI-TOF MS as a complement to existing approaches for fast, reliable identification of Phytophthora isolates.

scholarly journals MALDI-TOF Mass Spectrometry Technology as a Tool for the Rapid Diagnosis of Antimicrobial Resistance in Bacteria

Antibiotics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 982
Author(s):  
Eun-Jeong Yoon ◽  
Seok Hoon Jeong
Keyword(s):  
Mass Spectrometry ◽  
Antimicrobial Resistance ◽  
Low Cost ◽  
Rapid Identification ◽  
Diagnostic Process ◽  
Antimicrobial Drugs ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Mass Spectrometry Technology ◽  
Tof Ms

Species identification by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a routine diagnostic process for infectious diseases in current clinical settings. The rapid, low-cost, and simple to conduct methodology is expanding its application in clinical microbiology laboratories to diagnose the antimicrobial resistance (AMR) in microorganisms. Primarily, antimicrobial susceptibility testing is able to be carried out either by comparing the area under curve of MALDI spectra of bacteria grown in media with antimicrobial drugs or by identifying the shift peaks of bacteria grown in media including 13C isotope with antimicrobial drugs. Secondly, the antimicrobial resistance is able to be determined through identifying (i) the antimicrobial-resistant clonal groups based on the fingerprints of the clone, (ii) the shift peak of the modified antimicrobial drug, which is inactivated by the resistance determinant, (iii) the shift peak of the modified antimicrobial target, (iv) the peak specific for the antimicrobial determinant, and (v) the biomarkers that are coproduced proteins with AMR determinants. This review aims to present the current usage of the MALDI-TOF MS technique for diagnosing antimicrobial resistance in bacteria, varied approaches for AMR diagnostics using the methodology, and the future applications of the methods for the accurate and rapid identification of AMR in infection-causing bacterial pathogens.

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