Accelerating tandem MS protein database searches using OpenCL

ZusammenfassungMit der Einführung neuer Technologien in das Spektrum der Labordiagnostik auf angeborene Stoffwechselerkrankungen im Neugeborenenalter wurde eine Reihe von organisatorischen Änderungen erforderlich, die zusammenfassend dargestellt werden. Der Beitrag beschreibt methodische Grundlagen der Tandem-Massenspektrometrie (Tandem-MS) und deren Anwendung in der präsymptomatischen Diagnostik entsprechend dem von der Deutschen Gesellschaft für Neugeborenenscreening (DGNS) geforderten Qualitätsmanagement. Die Hintergrundinformationen sind vor allem für die Probeneinsender (Ärzte, Hebammen, Schwestern), Laborpersonal und selbstverständlich auch für junge Eltern bestimmt, die mit den Neuerungen im Ablauf des Neugeborenenscreenings (NGS) konfrontiert sind bzw. die Argumente zur Teilnahme an dieser freiwilligen Präventionsmaßnahme suchen. Es werden exemplarisch das derzeit gültige Struktur- und Prozessmanagement für das Leipziger Screeningzentrum einschließlich der Qualitätssicherung und der Ergebnisse basierend auf 199 914 Trockenblutuntersuchungen vorgestellt.

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Determination of extractable perfluorooctanesulphonate (PFOS) in coated and impregnated solid articles, liquids and fire fighting foams. Method for sampling, extraction and analysis by LCqMS or LC-tandem/MS

10.3403/30297120u ◽

2015 ◽

Keyword(s):

Fire Fighting ◽

Tandem Ms ◽

Lc Tandem Ms

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Mass Spectrometry-Based Identification of Urinary Antimicrobial Peptides in Dairy Cows

Protein and Peptide Letters ◽

10.2174/0929866526666191025105038 ◽

2020 ◽

Vol 27 (3) ◽

pp. 225-235

Author(s):

Ambika Sharma ◽

Rajesh Nigam ◽

Ashish Kumar ◽

Simmi Singh

Keyword(s):

Mass Spectrometry ◽

Antimicrobial Peptides ◽

Polyacrylamide Gel Electrophoresis ◽

Radial Diffusion ◽

Protein Database ◽

Antimicrobial Effects ◽

Cow Urine ◽

Radial Diffusion Assay ◽

Promising Source ◽

Diffusion Assay

Background:: Urine is considered one of the biological fluids in which antimicrobial peptides are secreted or expressed. Cow urine has not been investigated for the presence of these peptides using MALDI-TOF-MS. Objective:: The aim of this study is to isolate, identify and assess the antimicrobial activity of urinary antimicrobial peptides from healthy normal cycling cows. Method:: We analyzed the urine sample using diafiltration, ion exchange chromatography, Reverse Phase High-Performance Liquid Chromatography (RP-HPLC), acid urea polyacrylamide gel electrophoresis (AU-PAGE) coupled with identification through Peptide Mass Fingerprinting (PMF) by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDITOF- MS). The in vitro antimicrobial effects of purified fractions were assessed using Radial Diffusion Assay (RDA) and microtitre broth dilution assay against Gram-positive and Gramnegative bacteria. Results: : Proteins corresponding to the peaks were identified using SWISSPROT protein database. This study revealed constitutive expression of β-Defensin-1 (DEFB1), β-Defensin-4A (DFB4A), Neutrophil Defensin-1 (DEF1), Neutrophil Defensin-3 (DEF3) in cow urine. The identified peptides are cationic antimicrobial peptides of the defensin family. The purified fractions exhibited antimicrobial effects in radial diffusion assay and MIC values in the range of 2.93-29.3 &*#181;M/L. Conclusion:: This study concludes that cow urine, previously unexplored with regard to antimicrobial peptides, would be a promising source of highly potent AMPs and an effective alternative to the resistant antibiotics.

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Label-Free Mass Spectrometry-Based Plasma Proteomics Identified LY6D, DSC3, CDSN, SERPINB12, and SLURP1,as Novel Protein Biomarkers For Pulmonary Tuberculosis

Current Proteomics ◽

10.2174/1570164617666191210105122 ◽

2019 ◽

Vol 17 ◽

Author(s):

Xiaoli Yu ◽

Lu Zhang ◽

Na Li ◽

Peng Hu ◽

Zhaoqin Zhu ◽

...

Keyword(s):

Pulmonary Tuberculosis ◽

Search Algorithm ◽

Differentially Expressed ◽

P Value ◽

Plasma Samples ◽

Label Free ◽

Protein Biomarkers ◽

Protein Database ◽

Leave One Out ◽

Potential Biomarkers

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary tuberculosis. Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of Pulmonary tuberculosis were still lacked. Objective: This study focused on construct a label-free LC-MS/MS based comparative proteomics between six tuberculosis patients and six healthy controls to identify differentially expressed proteins (DEPs) in plasma. Method: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by general discriminant analysis (GDA), with leave-one-out cross-validation. Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for differentially expressed protein was set as adjusted p-value < 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for pulmonary tuberculosis, and be worthy of further validation.

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Proteomic Analysis of Medicinal Plant Calotropis Gigantea by insilico Peptide Mass Fingerprinting

Current Computer - Aided Drug Design ◽

10.2174/1573409916666200219114531 ◽

2020 ◽

Vol 16 ◽

Author(s):

Saad Ur Rehman ◽

Muhammad Rizwan ◽

Sajid Khan ◽

Azhar Mehmood ◽

Anum Munir

Keyword(s):

Medicinal Plant ◽

Structure Prediction ◽

3D Structure ◽

Peptide Mass Fingerprinting ◽

Protein Docking ◽

Receptor Protein ◽

Human Leukemia ◽

Protein Database ◽

Calotropis Gigantea ◽

Peptide Mass

: Medicinal plants are the basic source of medicinal compounds traditionally used for the treatment of human diseases. Calotropis gigantea a medicinal plant belonging to the family of Apocynaceae in the plant kingdom and subfamily Asclepiadaceae usually bearing multiple medicinal properties to cure a variety of diseases. Background: The Peptide Mass Fingerprinting (PMF) identifies the proteins from a reference protein database by comparing the amino acid sequence that is previously stored in a database and identified. Method: The calculation of insilico peptide masses is done through the ExPASy PeptideMass and these masses are used to identify the peptides from MASCOT online server. Anticancer probability is calculated from the iACP server, docking of active peptides is done by CABS-dock the server. Objective: The purpose of the study is to identify the peptides having anti-cancerous properties by in-silico peptide mass fingerprinting. Results : The anti-cancerous peptides are identified with the MASCOT peptide mass fingerprinting server, the identified peptides are screened and only the anti-cancer are selected. De novo peptide structure prediction is used for 3D structure prediction by PEP-FOLD 3 server. The docking results confirm strong bonding with the interacting amino acids of the receptor protein of breast cancer BRCA1 which shows the best peptide binding to the Active chain, the human leukemia protein docking with peptides shows the accurate binding. Conclusion : These peptides are stable and functional and are the best way for the treatment of cancer and many other deadly diseases.

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Aggregation prone regions in antibody sequences raised against Vibrio cholerae: A bioinformatic approach

Current Bioinformatics ◽

10.2174/1574893615666200106120504 ◽

2020 ◽

Vol 15 ◽

Author(s):

Zakia Akter ◽

Anamul Haque ◽

Md. Sabir Hossain ◽

Firoz Ahmed ◽

Md Asiful Islam

Keyword(s):

Vibrio Cholerae ◽

Binding Sites ◽

Bioinformatic Analysis ◽

Antigen Binding ◽

Short Term ◽

Protein Database ◽

The Stability ◽

Bioinformatic Approach ◽

Self Aggregation ◽

Complementarity Determining Region

Background: Cholera, a diarrheal illness causes millions of deaths worldwide due to large outbreaks. Monoclonal antibody used as therapeutic purposes of cholera are prone to be unstable due to various factors including self-aggregation. Objectives: In this bioinformatic analysis, we identified the aggregation prone regions (APRs) of different immunogens of antibody sequences (i.e., CTB, ZnM-CTB, ZnP-CTB, TcpA-CT-CTB, ZnM-TcpA-CT-CTB, ZnP-TcpA-CT-CTB, ZnM-TcpA, ZnP-TcpA, TcpA-CT-TcpA, ZnM-TcpA-CT-TcpA, ZnP-TcpA-CT-TcpA, Ogawa, Inaba and ZnM-Inaba) raised against Vibrio cholerae. Methods: To determine APRs in antibody sequences that were generated after immunizing Vibrio cholerae immunogens on Mus musculus, a total of 94 sequences were downloaded as FASTA format from a protein database and the algorithms such as Tango, Waltz, PASTA 2.0, and AGGRESCAN were followed to analyze probable APRs in all of the sequences. Results: A remarkably high number of regions in the monoclonal antibodies were identified to be APRs which could explain a cause of instability/short term protection of anticholera vaccine. Conclusion: To increase the stability, it would be interesting to eliminate the APR residues from the therapeutic antibodies in a such way that the antigen binding sites or the complementarity determining region loops involved in antigen recognition are not disrupted.

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Identification of C ‐glycosyl flavones and O ‐glycosyl flavones in five Dendrobium species by HPLC coupled with electrospray ionization multi‐stage tandem MS

Rapid Communications in Mass Spectrometry ◽

10.1002/rcm.9158 ◽

2021 ◽

Author(s):

Li Hu ◽

Zhiyun Liang ◽

Yawen Wang ◽

Gang Wei ◽

Yuechun Huang

Keyword(s):

Electrospray Ionization ◽

Tandem Ms ◽

Multi Stage

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Chimera Spectrum Diagnostics for Peptides Using Two-Dimensional Partial Covariance Mass Spectrometry

Molecules ◽

10.3390/molecules26123728 ◽

2021 ◽

Vol 26 (12) ◽

pp. 3728

Author(s):

Taran Driver ◽

Nikhil Bachhawat ◽

Leszek J. Frasinski ◽

Jonathan P. Marangos ◽

Vitali Averbukh ◽

...

Keyword(s):

Mass Spectrometry ◽

Peptide Sequence ◽

Two Dimensional ◽

Peptide Ions ◽

Finite Mass ◽

Protein Database ◽

Spectra Analysis ◽

Fragment Ions ◽

Single Precursor ◽

The Common

The rate of successful identification of peptide sequences by tandem mass spectrometry (MS/MS) is adversely affected by the common occurrence of co-isolation and co-fragmentation of two or more isobaric or isomeric parent ions. This results in so-called `chimera spectra’, which feature peaks of the fragment ions from more than a single precursor ion. The totality of the fragment ion peaks in chimera spectra cannot be assigned to a single peptide sequence, which contradicts a fundamental assumption of the standard automated MS/MS spectra analysis tools, such as protein database search engines. This calls for a diagnostic method able to identify chimera spectra to single out the cases where this assumption is not valid. Here, we demonstrate that, within the recently developed two-dimensional partial covariance mass spectrometry (2D-PC-MS), it is possible to reliably identify chimera spectra directly from the two-dimensional fragment ion spectrum, irrespective of whether the co-isolated peptide ions are isobaric up to a finite mass accuracy or isomeric. We introduce ‘3-57 chimera tag’ technique for chimera spectrum diagnostics based on 2D-PC-MS and perform numerical simulations to examine its efficiency. We experimentally demonstrate the detection of a mixture of two isomeric parent ions, even under conditions when one isomeric peptide is at one five-hundredth of the molar concentration of the second isomer.

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