scholarly journals Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

2020 ◽  
Vol 16 ◽  
pp. 3038-3051
Author(s):  
Steffen Lippold ◽  
Arnoud H de Ru ◽  
Jan Nouta ◽  
Peter A van Veelen ◽  
Magnus Palmblad ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Data Analysis ◽  
Structural Diversity ◽  
Reversed Phase ◽  
Mass Analyzer ◽  
Data Quality Control ◽  
Cysteine Oxidation ◽  
Research Areas ◽  
Peptide Modification

Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography–tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.

scholarly journals Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: A case study of an urothelial cancer cohort analyzed in the Galaxy framework

2021 ◽  
Author(s):  
Melanie Christine Föll ◽  
Veronika Volkmann ◽  
Kathrin Enderle-Ammour ◽  
Konrad Wilhelm ◽  
Dan Guo ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Data Analysis ◽  
Mass Spectrometry Imaging ◽  
Urothelial Cancer ◽  
Type I ◽  
Raw Data ◽  
The Galaxy ◽  
Muscle Invasive ◽  
Reproducible Manner

Background: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens. This allows for spatial characterization of molecular compositions of different tissue types and tumor subtypes, which bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of an urothelial carcinoma dataset. Methods: Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle invasive urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. Results: Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle invasive tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: Stromal tissue was characterized by collagen type I peptides and tumor tissue by histone and heat shock protein beta-1 peptides. Intermediate filaments such as cytokeratins and vimentin were discriminative between the tumors with different muscle-infiltration status. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. Conclusion: Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.

scholarly journals Human Tear Metabolomics Using Liquid Chromatography-Q Exactive-HF Mass Spectrometry

2021 ◽  
Author(s):  
Gauri Shankar Shrestha ◽  
Ajay Kumar Vijay ◽  
Fiona Stapleton ◽  
Russell Pickford ◽  
Nicole Carnt
Keyword(s):  
Mass Spectrometry ◽  
Amino Acids ◽  
Liquid Chromatography ◽  
Data Analysis ◽  
Mass Spectra ◽  
Reversed Phase ◽  
Charged Surface ◽  
Hydrophilic Interaction ◽  
Q Exactive ◽  
Chromatography Columns

AbstractAimTo putatively identify and characterise human tear metabolites in a normal subject on an untargeted platform of liquid chromatography-Q exactive-HF mass spectrometry.MethodsFour samples of unstimulated tears were collected from both eyes on four consecutive days between 1 – 2 pm using a microcapillary tube and pooled from both eyes each day. Untargeted analysis of the tears was performed by chromatographic separation of constituent metabolites in both CSH-C18RP (Charged Surface Hybrid-C18 Reversed Phase) and SeQuant ZIC-pHILIC (Zwitterionic-polymeric Hydrophilic Interaction Liquid Chromatography) columns, followed by heated electrospray ionization (HESI) and the acquisition of mass spectra using QExactive-HF mass spectrometer. Compound Discoverer software (v2.0) was used for data analysis.ResultEighty-two metabolites were tentatively identified. Seventy compounds (85.4 %) were observed in all four samples with a coefficient of variation (CV) less than 25 %. Fifty-nine metabolites (71.9 %) were novel in the healthy tears. Amino acids were the most frequently detected metabolites in the tears (28 %), followed by carbohydrates (12.2 %), carboxylic acids (8.5 %), carnitines (6.1 %) and glycerophospholipids (4.9 %), respectively.ConclusionThe current untargeted platform is capable of detecting a range of tear metabolites across several biological categories. This study provides a baseline for further ocular surface studies.

scholarly journals Mass Spectrometry and Its Importance for the Analysis and Discovery of Active Molecules in Natural Products

2021 ◽  
Author(s):  
Paco Noriega ◽  
Gabriela Gortaire ◽  
Edison Osorio
Keyword(s):  
Mass Spectrometry ◽  
Molecular Weight ◽  
Quality Control ◽  
Natural Products ◽  
Atomic Mass ◽  
Mass Analyzer ◽  
Chromatographic Techniques ◽  
Positive Ions ◽  
Ionization Processes ◽  
Ion Analysis

Mass spectrometry is one of the best techniques for analyzing the structure of a molecule. It usually provides information about the molecular weight of a substance, and it can present atomic mass units and up to ten thousandths of atomic mass units depending on the accuracy of the mass analyzer. In addition, it provides information on the positive ions formed in the ionization process, which is linked to the chemical structure of the molecule and the nature of the bonds. This technique is widely used for analyzing compounds from natural products. The development of the technique combined with the use of software and databases has been remarkable in recent years, improving the ionization processes and the ion analysis. Since natural products generally constitute a mixture of a complex quantity of components, mechanisms have been developed for coupling to chromatographic techniques of various kinds. This review aims to show how mass spectrometry has contributed to the qualitative quality control in natural products, as well as in the finding of new metabolites of industrial interest.

scholarly journals Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA sequencing data quality control

2020 ◽  
Author(s):  
Daniel Osorio ◽  
James J. Cai
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Single Cell ◽  
Cell Types ◽  
Supplementary Information ◽  
Human Tissues ◽  
Data Quality Control ◽  
Sequencing Data ◽  
Mouse Tissues ◽  
Systematic Determination

AbstractMotivationQuality control (QC) is a critical step in single-cell RNA-seq (scRNA-seq) data analysis. Low-quality cells are removed from the analysis during the QC process to avoid misinterpretation of the data. One of the important QC metrics is the mitochondrial proportion (mtDNA%), which is used as a threshold to filter out low-quality cells. Early publications in the field established a threshold of 5% and since then, it has been used as a default in several software packages for scRNA-seq data analysis and adopted as a standard in many scRNA-seq studies. However, the validity of using a uniform threshold across different species, single-cell technologies, tissues, and cell types has not been adequately assessed.ResultsWe systematically analyzed 5,530,106 cells reported in 1,349 annotated datasets available in the PanglaoDB database and found that the average mtDNA% in scRNA-seq data across human tissues is significantly higher than in mouse tissues. This difference is not confounded by the platform used to generate the data. Based on this finding, we propose new reference values of the mtDNA% for 121 tissues of mice and 44 tissues of humans. In general, for mouse tissues, the 5% threshold performs well to distinguish between healthy and low-quality cells. However, for human tissues, the 5% threshold should be reconsidered as it fails to accurately discriminate between healthy and low-quality cells in 29.5% (13 of 44) tissues analyzed. We conclude that omitting the mtDNA% QC filter or adopting a suboptimal mtDNA% threshold may lead to erroneous biological interpretations of scRNA-seq data.AvailabilityThe code used to download datasets, perform the analyzes, and produce the figures is available at https://github.com/dosorio/[email protected] informationSupplementary data are available at Bioinformatics online.

Penerapan model kendali mutu data hidrologi dalam rangka peningkatan kualitas data

2018 ◽  
Vol 13 (2) ◽  
pp. 131-146
Author(s):  
Mirwan Rofiq Ginanjar ◽  
Sri Mulat Yuningsih
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Water Resources ◽  
Data Quality ◽  
Control Model ◽  
Rainfall Data ◽  
Data Quality Control ◽  
Discharge Data ◽  
Hydrological Data

Planning and management of water resources are dependent on the quality of hydrological data. Hydrological data plays an important role in hydrological analysis. The availability of good and qualified hydrological data is one of the determinants of the results of hydrological analysis. However, the facts indicate that many of the available data do not fit their ideal state. To solve this problem, a hydrological data quality control model should be established in order to improve the quality of national hydrological data. The scope includes quality control of rainfall and discharge data. Analysis of the quality control of rainfall data was conducted on 58 rainfall stations spread on the island of Java. The analysis shows that 41 stations are good categorized, 14 stations are in moderate category and 3 stations are badly categorized. Based on these results, a light improvement scenario was performed, good category Station increased to 46 stations, moderate category decreased to 11 stations and bad category reduced to 1 Stations. Quality control of discharge data analysis was conducted on 14 discharge stations spread on Java Island. Analyzes were performed for QC1, QC2 and QC3 then got final QC value. The results on the final QC show no stations for good category, 2 stations for moderate categories and 12 stations for bad category. Based on the results of the analysis, a light improvement scenario was performed with the result of bad category increased to good category 5 stations, bad category increased to moderate 7 stations, and moderate category 1 stations.

scholarly journals Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control

2020 ◽  
Author(s):  
Daniel Osorio ◽  
James J Cai
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Single Cell ◽  
Cell Types ◽  
Supplementary Information ◽  
Human Tissues ◽  
Data Quality Control ◽  
Sequencing Data ◽  
Mouse Tissues ◽  
Systematic Determination

Abstract Motivation Quality control (QC) is a critical step in single-cell RNA-seq (scRNA-seq) data analysis. Low-quality cells are removed from the analysis during the QC process to avoid misinterpretation of the data. An important QC metric is the mitochondrial proportion (mtDNA%), which is used as a threshold to filter out low-quality cells. Early publications in the field established a threshold of 5% and since then, it has been used as a default in several software packages for scRNA-seq data analysis, and adopted as a standard in many scRNA-seq studies. However, the validity of using a uniform threshold across different species, single-cell technologies, tissues and cell types has not been adequately assessed. Results We systematically analyzed 5 530 106 cells reported in 1349 annotated datasets available in the PanglaoDB database and found that the average mtDNA% in scRNA-seq data across human tissues is significantly higher than in mouse tissues. This difference is not confounded by the platform used to generate the data. Based on this finding, we propose new reference values of the mtDNA% for 121 tissues of mouse and 44 tissues of humans. In general, for mouse tissues, the 5% threshold performs well to distinguish between healthy and low-quality cells. However, for human tissues, the 5% threshold should be reconsidered as it fails to accurately discriminate between healthy and low-quality cells in 29.5% (13 of 44) tissues analyzed. We conclude that omitting the mtDNA% QC filter or adopting a suboptimal mtDNA% threshold may lead to erroneous biological interpretations of scRNA-seq data. Availabilityand implementation The code used to download datasets, perform the analyzes and produce the figures is available at https://github.com/dosorio/mtProportion. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Simultaneous isotope dilution quantification and metabolic tracing of deoxyribonucleotides by liquid chromatography high resolution mass spectrometry

2018 ◽  
Author(s):  
Rostislav Kuskovsky ◽  
Raquel Buj ◽  
Peining Xu ◽  
Samuel Hofbauer ◽  
Mary T Doan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Stable Isotope ◽  
Isotope Dilution ◽  
High Resolution Mass Spectrometry ◽  
Reversed Phase ◽  
Pentose Phosphate ◽  
High Mass ◽  
Mass Analyzer ◽  
Isotope Tracing ◽  
Metabolic Tracing

AbstractQuantification of cellular deoxyribonucleoside mono-(dNMP), di-(dNDP), triphosphates (dNTPs) and related nucleoside metabolites are difficult due to their physiochemical properties and widely varying abundance. Involvement of dNTP metabolism in cellular processes including senescence and pathophysiological processes including cancer and viral infection make dNTP metabolism an important bioanalytical target. We modified a previously developed ion pairing reversed phase chromatography-mass spectrometry method for the simultaneous quantification and 13C isotope tracing of dNTP metabolites. dNMPs, dNDPs, and dNTPs were chromatographically resolved to avoid mis-annotation of in-source fragmentation. We used commercially available 13C15N-stable isotope labeled analogs as internal standards and show that this isotope dilution approach improves analytical figures of merit. At sufficiently high mass resolution achievable on an Orbitrap mass analyzer, stable isotope resolved metabolomics allows simultaneous isotope dilution quantification and 13C isotope tracing from major substrates including 13C-glucose. As a proof of principle, we quantified dNMP, dNDP and dNTP pools from multiple cell lines. We also identified isotopologue enrichment from glucose corresponding to ribose from the pentose-phosphate pathway in dNTP metabolites.

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