MALDI-ToF protein profiling as a potential rapid diagnostic platform for COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Chivte P
PROVIDER: S-EPMC8426322 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The outbreak of coronavirus disease 2019 (COVID-19) caused by SARS CoV-2 is ongoing and a serious threat to global public health. It is essential to detect the disease quickly and immediately to isolate the infected individuals. Nevertheless, the current widely used PCR and immunoassay-based methods suffer from false negative results and delays in diagnosis. Herein, a high-throughput serum peptidome profiling method based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is developed for efficient detection of COVID-19. We analyzed the serum samples from 146 COVID-19 patients and 152 control cases (including 73 non-COVID-19 patients with similar clinical symptoms, 33 tuberculosis patients, and 46 healthy individuals). After MS data processing and feature selection, eight machine learning methods were used to build classification models. A logistic regression machine learning model with 25 feature peaks achieved the highest accuracy (99%), with sensitivity of 98% and specificity of 100%, for the detection of COVID-19. This result demonstrated a great potential of the method for screening, routine surveillance, and diagnosis of COVID-19 in large populations, which is an important part of the pandemic control.
| S-EPMC7945584 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, is rapidly spreading and severely straining the capacities of public health communities and systems around the world. Therefore, accurate, rapid, and robust diagnostic tests for COVID-19 are crucial to prevent further spread of the infection, alleviate the burden on healthcare and diagnostic facilities, and ensure timely therapeutic intervention. To date, several detection methods based on nucleic acid amplification have been developed for the rapid and accurate detection of SARS-CoV-2. Despite the myriad of advancements in the detection methods for SARS-CoV-2, rapid sample preparation methods for RNA extraction from viruses have rarely been explored. Here, we report a rapid COVID-19 molecular diagnostic system that combines a self-powered sample preparation assay and loop-mediated isothermal amplification (LAMP) based naked-eye detection method for the rapid and sensitive detection of SARS-CoV-2. The self-powered sample preparation assay with a hydrophilic polyvinylidene fluoride filter and dimethyl pimelimidate can be operated by hand, without the use of any sophisticated instrumentation, similar to the reverse transcription (RT)-LAMP-based lateral flow assay for the naked-eye detection of SARS-CoV-2. The COVID-19 molecular diagnostic system enriches the virus population, extracts and amplifies the target RNA, and detects SARS-CoV-2 within 60 min. We validated the accuracy of the system by using 23 clinical nasopharyngeal specimens. We envision that this proposed system will enable simple, facile, efficient, and inexpensive diagnosis of COVID-19 at home and the clinic as a pre-screening platform to reduce the burden on the medical staff in this pandemic era.
| S-EPMC8534047 | biostudies-literature
Project description:Although procyanidins constitute a unique class of polymeric plant secondary metabolites with a variety of biological properties including potent antioxidant activity, structure determination has been challenging, and structures of many complex procyanidins remain uncertain. To expedite the characterization of procyanidins, negative ion matrix-assisted laser desorption ionization high-energy collision-induced dissociation tandem time-of-flight (MALDI-ToF/ToF) mass spectra of 20 isolated procyanidins containing catechin and epicatechin subunits with degrees of polymerization up to five were obtained and evaluated. Structurally significant fragmentation pathways of singly charged, deprotonated molecules were identified representing quinone methide, heterocyclic ring fission, and retro-Diels-Alder fragmentation. The interpretation of the tandem mass spectra for sequencing A-type, B-type, mixed-type, linear, and branched procyanidins is explained using specific examples of each.
| S-EPMC6296472 | biostudies-literature
Project description:BackgroundThe identification of the cause of chronic low back pain (CLBP) represents a great challenge to orthopedists due to the controversy over the diagnosis of discogenic low back pain (DLBP) and the existence of a number of cases of CLBP of unknown origin. This study aimed to develop diagnostic models to distinguish DLBP from other forms of CLBP and to identify serum biomarkers for DLBP.MethodsSerum samples were collected from patients with DLBP, chronic lumbar disc herniation (LDH), or CLBP of unknown origin, and healthy controls (N), and randomly divided into a training set (n = 30) and a blind test set (n = 30). Matrix-assisted laser desorption ionization time-of-flight mass spectrometry was performed for protein profiling of these samples. After the discriminative ability of two most significantly differential peaks from each two groups was assessed using scatter plots, classification models were developed using differential peptide peaks to evaluate their diagnostic accuracy. The identity of peptides corresponding to three representative differential peaks was analyzed.ResultsThe fewest statistically significant differential peaks were identified between DLBP and CLBP (3), followed by CLBP vs. N (5), DLBP vs. N (9), LDH vs. CLBP (20), DLBP vs. LDH (23), and LDH vs. N (43). The discriminative ability of two most significantly differential peaks was poor in classifying DLBP vs. CLBP but good in classifying DLBP vs. LDH. The accuracy of models for classification of DLBP vs. CLBP was not very high in the blind test (forecasting ability, 67.24%; sensitivity, 70%), although a higher accuracy was observed for classification of DLBP vs. LDH and LDH vs. N (forecasting abilities, ~90%; sensitivities, >90%). A further investigation of three representative differential peaks led to the identification of two peaks as peptides of complement C3, and one peak as a human fibrinogen peptide.ConclusionsOur findings benefit not only the diagnosis of CLBP but also the understanding of the differences between different forms of DLBP. The ability to distinguish between different causes of CLBP and the identification of serum biomarkers may be of great value to diagnose different causes of DLBP and predict treatment efficacy.
| S-EPMC4061098 | biostudies-literature
Project description:Truffles are edible mushrooms with similar morphological characteristics, that make it difficult to distinguish between highly prized truffles (such as the Périgord black T. melanosporum) and inexpensive truffles (such as the Asian Black T. indicum). These biological and economic features have led to several misidentifications and/or fraudulent profit in the truffle markets. In this paper, we investigate Matrix-assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) biotyping to identify 34 commercial fresh truffles from Europe and Asia. The MALDI-TOF MS clustering rapidly distinguished seven Tuber species identified by ITS phylogenetic analysis. The tasty T. melanosporum was clearly differentiated from the Chinese and less expensive truffles. These cheaper mushrooms were marketed as T. indicum but corresponded to a mix of three species. In total, the method confirmed misidentifications in 26% of commercial specimens. Several unknown blind-coded truffles were rapidly identified, with scores >= 2, using the Bruker Biotyper algorithm against MS databases. This study demonstrates that MALDI-TOF MS is a reliable, rapid and cheaper new tool compared with molecular methods for the identification of truffle species and could be used to control frauds in the truffle markets. It could also be useful for the certification of truffle-inoculated seedlings and/or diversity in forest ecosystems.
| S-EPMC6881316 | biostudies-literature
Project description:SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that predict high (hospitalized) and low-risk (outpatients) cases of COVID-19 identified by a platform that combines machine learning with matrix-assisted laser desorption ionization mass spectrometry analysis. Sample preparation, MS, and data analysis parameters were optimized to achieve an overall accuracy of 92%, sensitivity of 93%, and specificity of 92% in dataset without feature selection. We identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of SDS-PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins, both already described as biomarkers for viral infections in the acute phase. Unbiased discrimination of high- and low-risk COVID-19 patients using a technology that is currently in clinical use may have a prompt application in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.
| S-EPMC8321665 | biostudies-literature
Project description:Ticks are vectors of infectious diseases of major importance in human and veterinary medicine. For epidemiological studies, accurate identification of ticks is crucial to define their potential role as vectors and to develop control and prevention strategies. Although morphological and molecular methods are widely used to identify ticks, an innovative approach using MALDI-TOF MS technology recently emerged as an alternative tool. Previous works showed that MALDI-TOF MS was highly effective in identifying ticks, but these works mainly tested tick specimens of different genera. To confirm the accuracy of this new tool for tick identification, nine closely related tick species belonging to the Ixodes genus were analysed, specimens of the Dermacentor reticulatus species were also included in the analysis as an outer group. Three of the species used for the present study belonged to the I. ricinus species complex, which are known to transmit Borrelia burgdorferi sensu lato, the causative agent of Lyme borreliosis. A total of 246 tick specimens were submitted to MALDI-TOF MS analysis, and two body parts (half-idiosoma and four legs) were individually investigated. For each body part, intraspecies reproducibility and interspecies specificity of the MS profiles were determined. The profile analysis revealed that the main determinant for spectra clustering was the tick species for both legs and half-idiosoma. For each body part, a reference database of spectra was set up including 2 to 5 specimens per species randomly selected, and genotyped using 16s rDNA and COI genes to confirm their morphological identification. Both created spectral databases were individually blind tested with their respective body part using the remaining specimens, which were correctly identified in 98.5% of the cases. MALDI-TOF MS is a reliable tool for tick identification, including specimens belonging to closely related species and hardly distinguishable using morphology. The 4-legs as well as the half-idiosoma of ticks can now be applied for specimen identification using two different databases. The combined use of these two body parts improves the rate of tick identification and their confidence level.
| S-EPMC6797106 | biostudies-literature
Project description:Lack of genomic sequence data and the relatively high cost of tandem mass spectrometry have hampered proteomic investigations into helminths, such as resolving the mechanism underpinning globally reported anthelmintic resistance. Whilst detailed mechanisms of resistance remain unknown for the majority of drug-parasite interactions, gene mutations and changes in gene and protein expression are proposed key aspects of resistance. Comparative proteomic analysis of drug-resistant and -susceptible nematodes may reveal protein profiles reflecting drug-related phenotypes. Using the gastro-intestinal nematode, Haemonchus contortus as case study, we report the application of freely available expressed sequence tag (EST) datasets to support proteomic studies in unsequenced nematodes. EST datasets were translated to theoretical protein sequences to generate a searchable database. In conjunction with matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF-MS), Peptide Mass Fingerprint (PMF) searching of databases enabled a cost-effective protein identification strategy. The effectiveness of this approach was verified in comparison with MS/MS de novo sequencing with searching of the same EST protein database and subsequent searches of the NCBInr protein database using the Basic Local Alignment Search Tool (BLAST) to provide protein annotation. Of 100 proteins from 2-DE gel spots, 62 were identified by MALDI-TOF-MS and PMF searching of the EST database. Twenty randomly selected spots were analysed by electrospray MS/MS and MASCOT Ion Searches of the same database. The resulting sequences were subjected to BLAST searches of the NCBI protein database to provide annotation of the proteins and confirm concordance in protein identity from both approaches. Further confirmation of protein identifications from the MS/MS data were obtained by de novo sequencing of peptides, followed by FASTS algorithm searches of the EST putative protein database. This study demonstrates the cost-effective use of available EST databases and inexpensive, accessible MALDI-TOF MS in conjunction with PMF for reliable protein identification in unsequenced organisms.
| S-EPMC3315570 | biostudies-literature
Project description:BackgroundThe accurate and rapid preliminarily identification of the types of methicillin-resistant Staphylococcus aureus (MRSA) is crucial for infection control. Currently, however, expensive, time-consuming, and labor-intensive methods are used for MRSA typing. By contrast, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a potential tool for preliminary lineage typing. The approach has not been standardized, and its performance has not been analyzed in some regions with geographic barriers (e.g., Taiwan Island).MethodsThe mass spectra of 306 MRSA isolates were obtained from multiple reference hospitals in Taiwan. The multilocus sequence types (MLST) of the isolates were determined. The spectra were analyzed for the selection of characteristic peaks by using the ClinProTools software. Furthermore, various machine learning (ML) algorithms were used to generate binary and multiclass models for classifying the major MLST types (ST5, ST59, and ST239) of MRSA.ResultsA total of 10 peaks with the highest discriminatory power (m/z range: 2,082-6,594) were identified and evaluated. All the single peaks revealed significant discriminatory power during MLST typing. Moreover, the binary and multiclass ML models achieved sufficient accuracy (82.80-94.40% for binary models and >81.00% for multiclass models) in classifying the major MLST types.ConclusionsA combination of MALDI-TOF MS analysis and ML models is a potentially accurate, objective, and efficient tool for infection control and outbreak investigation.
| S-EPMC6228551 | biostudies-literature
Project description:Protein glycosylation mediates a wide range of cellular processes, affecting development and disease in mammals. Deciphering the "glycocodes" requires rapid, sensitive and in-depth characterization of diverse glycan structures derived from biological samples. In this study, we described a two-step derivatization strategy termed linkage-specific sialic acid permethylation (SSAP) consisting of dimethylamination and permethylation for the improved profiling of glycosylation by matrix-assisted laser desorption/ionization (MALDI) time-of-fight (TOF) mass spectrometry (MS). High linkage-specificity (∼99%) of SSAP to both the two most common forms of sialic acid, N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc), permitted direct discrimination of α2,3- and α2,6-linked sialic acids in MALDI-TOF MS. The enhanced intensity (>10-fold) and increased detection limit (>10-fold) of derivatized glycans were valued for sensitive glycomics. Moreover, the good compatibility and reaction efficiency of the two steps of SSAP allowed rapid sample preparation (<2 h), benefiting robust analysis of glycans in a high-throughput manner. The SSAP strategy was further applied to investigate the protein glycosylation of human serum associated with rheumatoid arthritis (RA). It was demonstrated that the relative abundances of individual glycans were different in RA negative and RA positive samples, and meanwhile the RA patient/control ratios of both α2,3- and α2,6-sialylated glycans tended to elevate accompanied with the increase of sialylation. Those findings of the glycosylation changes occurred in human serum protein may contribute to the diagnosis of RA. Herein, SSAP derivatization combined with MALDI-TOF MS exhibits unique advantages for glycomic analysis and shows potential in glycosylation profiling of therapeutic proteins and clinical glycan biomarker discovery.
| S-EPMC5953179 | biostudies-literature