MALDI-TOF Mass Spectrometry Data Research Articles

SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS.

Zooarchaeology by Mass Spectrometry (ZooMS) is a palaeoproteomics method for the taxonomic determination of collagen, which traditionally involves challenging manual spectra analysis with limitations in quantitative results. As the ZooMS reference database expands, a faster and reproducible identification tool is necessary. Here we present SpecieScan, an open-access algorithm for automating taxa identification from raw MALDI-ToF mass spectrometry (MS) data. SpecieScan was developed using R (pre-processing) and Python (automation). The algorithm's output includes identified peptide markers, closest matching taxonomic group (taxon, family, order), correlation scores with the reference databases, and contaminant peaks present in the spectra. Testing on original MS data from bones discovered at Palaeothic archaeological sites, including Denisova Cave in Russia, as well as using publicly-available, externally produced data, we achieved >90% accuracy at the genus-level and ∼92% accuracy at the family-level for mammalian bone collagen previously analysed manually. The SpecieScan algorithm, along with the raw data used in testing, results, reference database, and common contaminants lists are freely available on Github (https://github.com/mesve/SpecieScan).

A clinical case of posttraumatic osteomyelitis associated with <i>kytococcus schroeteri</i> and <i>enterococcus faecalis</i>

Introduction. In most cases, osteomyelitis is the monomicrobial disease caused by various Gram-positive bacteria. However, previous injury may contribute to formation of a microbial association. Presence of two or more pathogens in the infectious focus can markedly complicate the disease clinical picture.Kytococcus schroeteriis one of the rarest pathogens found in clinical samples. Slightly more than twenty described cases related to such infection have been recorded globally. The aim of the research was to analyse the first identified clinical case of post-traumatic osteomyelitis associated withKytococcus schroeteriandEnterococcus faecalis.Materials and methods.The bacterial cultures were obtained from the wound discharge of the patient’s shin by the cultural method. Identification of the bacterial cultures was performed using a VITEK MS mass spectrometer followed by 16S rRNA gene sequencing. The morphological, tinctorial and biochemical features of the cultures obtained were established, and their antibacterial resistance was also determined.Results. The clinical case was associated with the diagnosis “Chronic post-traumatic osteomyelitis of the left shin”. Two types of microorganisms were isolated from the wound discharge, and identified asKytococcus schroeteriandEnterococcus faecalisusing the MALDI-ToF mass spectrometry method. 16S rRNA gene sequencing from the isolated bacterial cultures confirmed the MALDI-ToF mass spectrometry data. Antimicrobial susceptibility for this microorganism was determined according to the criteria for the staphylococcal group according to the clinical guide “Determination of sensitivity to antimicrobial drugs (rev. 2021)”.Conclusion. For the first time, the mixed infection caused by two Gram-positive bacteriaK. schroeteriandE. faecalishas been described. Such associations can enhance the pathogenic effects of each other bacterium, which may contribute to transition of the infection to a chronic form with a low probability of positive cultural test.K. schroeteriis a representative of the normal skin microbiota, but this microorganism is able to cause various infections. TheK. schroeterispecies should be differentiated from other representatives of the orderMicrococcales. At cultural examination, resistance to oxacillin is a suspicious sign indicating that the bacterial culture might be potentially assigned toK. schroeterispecies. Due to the unavailability of current biochemical tests for differentiationK. schroeterifrom related taxa, reliable identification of this species is recommended using MALDI-ToF mass spectrometry or 16S rRNA gene sequencing.

Semi-supervised learning for MALDI–TOF mass spectrometry data classification: an application in the salmon industry

Semi-supervised learning for MALDI–TOF mass spectrometry data classification: an application in the salmon industry

N-glycosylation modulates enzymatic activity of Trypanosoma congolense trans-sialidase

Trypanosomes cause the devastating disease trypanosomiasis, in which the action of trans-sialidase (TS) enzymes harbored on their surface is a key virulence factor. TS enzymes are N-glycosylated, but the biological functions of their glycans have remained elusive. In this study, we investigated the influence of N-glycans on the enzymatic activity and structural stability of TconTS1, a recombinant TS from the African parasite Trypanosoma congolense. We expressed the enzyme in Chinese hamster ovary Lec1 cells, which produce high-mannose type N-glycans similar to the TS N-glycosylation pattern in vivo. Our MALDI-TOF mass spectrometry data revealed that up to eight putative N-glycosylation sites were glycosylated. In addition, we determined that N-glycan removal via endoglycosidase Hf treatment of TconTS1 led to a decrease in substrate affinity relative to the untreated enzyme but had no impact on the conversion rate. Furthermore, we observed no changes in secondary structure elements of hypoglycosylated TconTS1 in CD experiments. Finally, our molecular dynamics simulations provided evidence for interactions between monosaccharide units of the highly flexible N-glycans and some conserved amino acids located at the catalytic site. These interactions led to conformational changes, possibly enhancing substrate accessibility and enzyme–substrate complex stability. The here-observed modulation of catalytic activity via N-glycans represents a so-far-unknown structure–function relationship potentially inherent in several members of the TS enzyme family.

Machine Learning Algorithms for Classification of MALDI-TOF MS Spectra from Phylogenetically Closely Related Species Brucella melitensis, Brucella abortus and Brucella suis.

(1) Background: MALDI-TOF mass spectrometry (MS) is the gold standard for microbial fingerprinting, however, for phylogenetically closely related species, the resolution power drops down to the genus level. In this study, we analyzed MALDI-TOF spectra from 44 strains of B. melitensis, B. suis and B. abortus to identify the optimal classification method within popular supervised and unsupervised machine learning (ML) algorithms. (2) Methods: A consensus feature selection strategy was applied to pinpoint from among the 500 MS features those that yielded the best ML model and that may play a role in species differentiation. Unsupervised k-means and hierarchical agglomerative clustering were evaluated using the silhouette coefficient, while the supervised classifiers Random Forest, Support Vector Machine, Neural Network, and Multinomial Logistic Regression were explored in a fine-tuning manner using nested k-fold cross validation (CV) with a feature reduction step between the two CV loops. (3) Results: Sixteen differentially expressed peaks were identified and used to feed ML classifiers. Unsupervised and optimized supervised models displayed excellent predictive performances with 100% accuracy. The suitability of the consensus feature selection strategy for learning system accuracy was shown. (4) Conclusion: A meaningful ML approach is here introduced, to enhance Brucella spp. classification using MALDI-TOF MS data.

Label-free cell assays to determine compound uptake or drug action using MALDI-TOF mass spectrometry.

Cell-based assays for compound screening and profiling are fundamentally important in life sciences, chemical biology and pharmaceutical research. Most cell assays measure the amount of a single reporter molecule or cellular endpoint, and require the use of fluorescence or other labeled materials. Consequently, there is high demand for label-free technologies that enable multiple biomolecules or endpoints to be measured simultaneously. Here, we describe how to develop, optimize and validate MALDI-TOF mass spectrometry (MS) cell assays that can be used to measure cellular uptake of transporter substrates, to monitor cellular drug target engagement or to discover cellular drug-response markers. In uptake assays, intracellular accumulation of a transporter substrate and its inhibition by test compounds is measured. In drug response assays, changes to multiple cellular metabolites or to abundant posttranslational protein modifications are monitored as reporters of drug activity. We detail a ten-part optimization protocol with every part taking 1-2 d that leads to a final 2 d optimized procedure, which includes cell treatment, transfer, MALDI MS-specific sample preparation, quantification using stable-isotope-labeled standards, MALDI-TOF MS data acquisition, data processing and analysis. Key considerations for validation and automation of MALDI-TOF MS cell assays are outlined. Overall, label-free MS cell-based assays offer speed, sensitivity, accuracy and versatility in drug research.

Klebsiella MALDI TypeR: a web-based tool for Klebsiella identification based on MALDI-TOF mass spectrometry

Klebsiella pathogens affect human and animal health and are widely distributed in the environment. Among these, the Klebsiella pneumoniae species complex, which includes seven phylogroups, is an important cause of community and hospital infections. The Klebsiella oxytoca species complex also causes hospital infections and antibiotic-associated haemorrhagic colitis. The unsuitability of currently used clinical microbiology methods to distinguish species within each of these species complexes leads to high rates of misidentifications that are masking the true clinical significance and potential epidemiological specificities of individual species.We developed a web-based tool, Klebsiella MALDI TypeR, a platform-independent and user-friendly application that enables uploading MALDI-TOF mass spectrometry data in order to identify Klebsiella isolates at the species complex and phylogroup levels. The tool, available at https://maldityper.pasteur.fr/, leverages a database of previously identified biomarkers that are specific for species complexes, individual phylogroups, or related phylogroups. We obtained 84%–100% identification accuracy depending on phylogroup. Identification results are obtained in a few seconds from batches of uploaded spectral data.Klebsiella MALDI TypeR enables fast and reliable identification of Klebsiella strains that are often misidentified with standard microbiological methods. This web-based identification tool may be extended in the future to other human bacterial pathogens.

Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study.

Today machine learning methods are commonly deployed for bacterial species identification using MALDI-TOF mass spectrometry data. However, most of the studies reported in literature only consider very traditional machine learning methods on small datasets that contain a limited number of species. In this paper we present benchmarking results on an unprecedented scale for a wide range of machine learning methods, using datasets that contain almost 100,000 spectra and more than 1000 different species. The size and the diversity of the data allow to compare three important identification scenarios that are often not distinguished in literature, i.e., identification for novel biological replicates, novel strains and novel species that are not present in the training data. The results demonstrate that in all three scenarios acceptable identification rates are obtained, but the numbers are typically lower than those reported in studies with a more limited analysis. Using hierarchical classification methods, we also demonstrate that taxonomic information is in general not well preserved in MALDI-TOF mass spectrometry data. For the novel species scenario, we apply for the first time neural networks with Monte Carlo dropout, which have shown to be successful in other domains, such as computer vision, for the detection of novel species.

Intact-Cell MALDI-ToF Mass Spectrometry for the Authentication of Drug-Adapted Cancer Cell Lines.

The use of cell lines in research can be affected by cell line misidentification. Short tandem repeat (STR) analysis is an effective method, and the gold standard, for the identification of the genetic origin of a cell line, but methods that allow the discrimination between cell lines of the same genetic origin are lacking. Here, we use intact cell MALDI-ToF mass spectrometry analysis, routinely used for the identification of bacteria in clinical diagnostic procedures, for the authentication of a set of cell lines consisting of three parental neuroblastoma cell lines (IMR-5, IMR-32 and UKF-NB-3) and eleven drug-adapted sublines. Principal component analysis (PCA) of intact-cell MALDI-ToF mass spectrometry data revealed clear differences between most, but not all, of the investigated cell lines. Mass spectrometry whole-cell fingerprints enabled the separation of IMR-32 and its clonal subline IMR-5. Sublines that had been adapted to closely related drugs, for example, the cisplatin- and oxaliplatin-resistant UKF-NB-3 sublines and the vincristine- and vinblastine-adapted IMR-5 sublines, also displayed clearly distinctive patterns. In conclusion, intact whole-cell MALDI-ToF mass spectrometry has the potential to be further developed into an authentication method for mammalian cells of a common genetic origin.

LICIC: Less Important Components for Imbalanced Multiclass Classification

Multiclass classification in cancer diagnostics, using DNA or Gene Expression Signatures, but also classification of bacteria species fingerprints in MALDI-TOF mass spectrometry data, is challenging because of imbalanced data and the high number of dimensions with respect to the number of instances. In this study, a new oversampling technique called LICIC will be presented as a valuable instrument in countering both class imbalance, and the famous “curse of dimensionality” problem. The method enables preservation of non-linearities within the dataset, while creating new instances without adding noise. The method will be compared with other oversampling methods, such as Random Oversampling, SMOTE, Borderline-SMOTE, and ADASYN. F1 scores show the validity of this new technique when used with imbalanced, multiclass, and high-dimensional datasets.

Corrigendum: Probing the Surface of a Laccase for Clues towards the Design of Chemo-Enzymatic Catalysts.

The authors of this Full Paper wish to correct the acknowledgements as below, and apologize for this oversight. “L.S. was the recipient of a Ministre de l'Education Nationale fellowship. This study was supported by grants from the Agence Nationale de la Recherche (ANR-09-BLANC-0176 and ANR-15-CE07-0021-01) and from the Ministerio de Economa, Industria y Competitividad (CTQ2016-79138-R). We thank Elise Courvoisier–Dezord from the Plateforme AVB (AMU): Analyse et Valorisation de la Biodiversit and Yolande Charmasson for help in the production of the recombinant enzymes, as well as Pascal Mansuelle and Régine Lebrun from the Plateforme Protéomique, MaP IBiSA Labelled, Institut de Microbiologie de la Méditerranée, CNRS, Aix-Marseille Univ, for performing N-Terminal sequencing and for help in acquiring MALDI-TOF mass spectrometry data.”

MALDI-TOF Mass Spectrometric Analysis of Brain Tumor Cyst Fluid Reveals a Protein Peak Corresponding to ApoC1 and LuzP6

Objectives: SELDI-TOF and MALDI-TOF mass spectrometry (MS) are laser desorption technologies that allow for proteomic examination of molecular masses in small amounts of samples. In a precedent study, the feasibility of SELDI-TOF MS assessment of proteins in cerebrospinal fluid and tumor cyst fluid had been shown. In the present study, we analyzed whether MALDI-TOF MS examination of these fluids leads to comparable results. Methods: During neurosurgical intervention, cyst fluids from 24 glioblastomas and 15 metastases were collected. As control, cerebrospinal fluid samples from 23 patients were obtained. The samples were prepared using a protocol optimized for MALDI-TOF MS. Mass spectra were recorded and peaks were extracted, characterized by masses and relative intensities. These peaks were analyzed for statistically significant differences between the diagnosis groups and compared to SELDI-TOF MS data. Results: 41 protein peaks known from the SELDI-TOF MS analysis could be confirmed by MALDI-TOF MS, and the cellular expression of the proteins LuzP6 and ApoC1, corresponding to the protein peaks 6433 and 6632, was shown immunohistochemically in glioblas-toma tissue. The MALDI-TOF spectrometry extends the range of analysis down to 1.4 kDa, whereas the upper detection limit lies below 23 kDa. Discussion: The presented proteomic approach yields an inventory of protein masses, found in the tumor cyst at the time of puncture. It does not reveal pathophysiologic, metabolic or secretory pathways that lead to the presence of proteins in the cyst. These have to be assessed immunohistochemically or on mRNA level in the surrounding tumor cells. Conclusion: MALDI-TOF MS of tumor cyst fluid discloses protein sizes, overexpressed or lost in tumor tissue. A thorough proteomic work-up is needed to identify the underlying proteins and metabolic pathways.

Efficient heterologous expression, functional characterization and molecular modeling of annular seabream digestive phospholipase A2

Here we report the cDNA cloning of a phospholipase A2 (PLA2) from five Sparidae species. The deduced amino acid sequences show high similarity with pancreatic PLA2. In addition, a phylogenetic tree derived from alignment of various available sequences revealed that Sparidae PLA2 are closer to avian PLA2 group IB than to mammals’ ones. In order to understand the structure-function relationships of these enzymes, we report here the recombinant expression in E.coli, the refolding and characterization of His-tagged annular seabream PLA2 (AsPLA2). A single Ni-affinity chromatography step was used to obtain a highly purified recombinant AsPLA2 with a molecular mass of 15kDa as attested by gel electrophoresis and MALDI-TOF mass spectrometry data. The enzyme has a specific activity of 400U.mg−1 measured on phosphatidylcholine at pH 8.5 and 50°C. The enzyme high thermo-activity and thermo-stability make it a potential candidate in various biological applications. The 3D structure models of these enzymes were compared with structures of phylogenetically related pancreatic PLA2. By following these models and utilizing molecular dynamics simulations, the resistance of the AsPLA2 at high temperatures was explained. Using the monomolecular film technique, AsPLA2 was found to be active on various phospholipids spread at the air/water interface at a surface pressure between 12 and 25dyncm−1. Interestingly, this enzyme was shown to be mostly active on dilauroyl-phosphatidylglycerol monolayers and this behavior was confirmed by molecular docking and dynamics simulations analysis. The discovery of a thermo-active new member of Sparidae PLA2, provides new insights on structure-activity relationships of fish PLA2.

Subunit NDUFV3 is present in two distinct isoforms in mammalian complex I

Complex I (NADH:ubiquinone oxidoreductase) is the first enzyme of the electron transport chain in mammalian mitochondria. Extensive proteomic and structural analyses of complex I from Bos taurus heart mitochondria have shown it comprises 45 subunits encoded on both the nuclear and mitochondrial genomes; 44 of them are different and one is present in two copies. The bovine heart enzyme has provided a model for studying the composition of complex I in other mammalian species, including humans, but the possibility of additional subunits or isoforms in other species or tissues has not been explored. Here, we describe characterization of the complexes I purified from five rat tissues and from a rat hepatoma cell line. We identify a~50kDa isoform of subunit NDUFV3, for which the canonical isoform is only ~10kDa in size. We combine LC-MS and MALDI-TOF mass spectrometry data from two different purification methods (chromatography and immuno-purification) with information from blue native PAGE analyses to show the long isoform is present in the mature complex, but at substoichiometric levels. It is also present in complex I in cultured human cells. We describe evidence that the long isoform is more abundant in both the mitochondria and purified complexes from brain (relative to in heart, liver, kidney and skeletal muscle) and more abundant still in complex I in cultured cells. We propose that the long 50kDa isoform competes with its canonical 10kDa counterpart for a common binding site on the flavoprotein domain of complex I.

The first synthesis of sandwich-type complex based on tetradiazepinoporphyrazine ligand

Sandwich-type complex based on tetradiazepinoporphyrazine ligand — bis{tetrakis(5,7-di(4-tert-butylphenyl)-6H-1,4-diazepino)[2,3-b,g,l,q]porphyrazinato}lutetium — was synthesized for the first time. The structure of the compound has been confirmed by UV-vis/NIR, 1 H NMR spectroscopy, and MALDI-TOF mass spectrometry data. The introduction of annulated diazepine heterocycles to porphyrazine molecule significantly changes macrocycle reactivity and results in sandwich-type complex under conditions used for the selective synthesis of lanthanide(III) monophthalocyanines.

N-Glycosylation patterns in two α-l-arabinofuranosidases from Penicillium canescens belonging to the glycoside hydrolase families 51 and 54

Using MALDI-TOF mass spectrometry (MS) peptide fingerprinting procedure followed by the analysis of MS data with the GlycoMod tool from the ExPASy proteomic site, N-glycosylation of two GH51 and GH54 family α-l-arabinofuranosidases (Abf51A and Abf54A) from Penicillium canescens was studied. Variable N-linked glycans were identified at five out of eight potential N-glycosylation sites in the Abf51A and one out of three potential N-glycosylation sites in the Abf54A. The discriminated glycans represented high-mannose oligosaccharides (Man)x(GlcNAc)2 with a number of Man residues up to 7 or the products of sequential enzymatic trimming of a high-mannose glycan with α-mannosidases and β-N-acetylhexosaminidases. The Abf54A peptide, containing the Asn254 glycosylation site, and one peptide from the Abf51A, containing the Asn163 glycosylation site, were found to exist not only in glycosylated, but also in a native non-modified form.

Delineation of Stenotrophomonas spp. by multi-locus sequence analysis and MALDI-TOF mass spectrometry

The genus Stenotrophomonas is genetically and phenotypically heterogeneous. Of the nine species now accepted, only S. maltophilia is of clinical importance. Based on DNA-sequences of seven house keeping genes, it encompasses genogroups of DNA-similarity below 97% that predominantly comprise strains of environmental origin. Therefore, in order to unravel the uneven distribution of environmental isolates within genogroups and reveal genetic relationships within the genus, there is need for an easy and reliable approach for the identification and delineation of Stenotrophomonas spp. In this first study, a multi-locus sequence analysis (MLSA) with seven housekeeping genes ( atpD, gapA, guaA, mutM, nuoD, ppsA and recA) was applied for analysis of 21 S. maltophilia of environmental origin, Stenotrophomonas spp. and related genera. The genotypic findings were compared with the results of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analyses. Our MLSA provided reliable inter- and intra-species discrimination of all tested isolates that correlated with the MALDI-TOF mass spectrometry data. One distantly related genogroup of environmental S. maltophilia strains needs to be reclassified as S. rhizophila. However, there are still remaining delineated S. maltophilia genogroups of predominantly environmental origin. Our data provide further evidence that ‘ Pseudomonas’ beteli is a heterotypic synonym of S. maltophilia. Based on MLSA and MALDI-TOF data, Stenotrophomonas sp. (DSM 2408) belongs to S. koreensis.

A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples

Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data. MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf.

BioSunMS: a plug-in-based software for the management of patients information and the analysis of peptide profiles from mass spectrometry

BackgroundWith wide applications of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), statistical comparison of serum peptide profiles and management of patients information play an important role in clinical studies, such as early diagnosis, personalized medicine and biomarker discovery. However, current available software tools mainly focused on data analysis rather than providing a flexible platform for both the management of patients information and mass spectrometry (MS) data analysis.ResultsHere we presented a plug-in-based software, BioSunMS, for both the management of patients information and serum peptide profiles-based statistical analysis. By integrating all functions into a user-friendly desktop application, BioSunMS provided a comprehensive solution for clinical researchers without any knowledge in programming, as well as a plug-in architecture platform with the possibility for developers to add or modify functions without need to recompile the entire application.ConclusionBioSunMS provides a plug-in-based solution for managing, analyzing, and sharing high volumes of MALDI-TOF or SELDI-TOF MS data. The software is freely distributed under GNU General Public License (GPL) and can be downloaded from http://sourceforge.net/projects/biosunms/.

Analysis of MALDI-TOF Mass Spectrometry Data for Discovery of Peptide and Glycan Biomarkers of Hepatocellular Carcinoma

This paper presents computational methods to analyze MALDI-TOF mass spectrometry data for quantitative comparison of peptides and glycans in serum. The methods are applied to identify candidate biomarkers in serum samples of 203 participants from Egypt; 73 hepatocellular carcinoma (HCC) cases, 52 patients with chronic liver disease (CLD) consisting of cirrhosis and fibrosis cases, and 78 population controls. Two complementary sample preparation methods were applied prior to generating mass spectra: (1) low molecular weight (LMW) enrichment of each serum sample was carried out for MALDI-TOF quantification of peptides, and (2) glycans were enzymatically released from proteins in each serum sample and permethylated for MALDI-TOF quantification of glycans. A peak selection algorithm was applied to identify the most useful peptide and glycan peaks for accurate detection of HCC cases from high-risk population of patients with CLD. In addition to global peaks selected by the whole population based approach, where identically labeled patients are treated as a single group, subgroup-specific peaks were identified by searching for peaks that are differentially abundant in a subgroup of patients only. The peak selection process was preceded by peak screening, where we eliminated peaks that have significant association with covariates such as age, gender, and viral infection based on the peptide and glycan spectra from population controls. The performance of the selected peptide and glycan peaks was evaluated in terms of their ability in detecting HCC cases from patients with CLD in a blinded validation set and through the cross-validation method. Finally, we investigated the possibility of using both peptides and glycans in a panel to enhance the diagnostic capability of these candidate markers. Further evaluation is needed to examine the potential clinical utility of the candidate peptide and glycan markers identified in this study.