1.5 Proteinanalytik
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- Monoclonal antibody (4)
- Traceability (4)
- ABID (3)
- Mass spectrometry (3)
- Peptide mass fingerprinting (3)
- Reproducibility (3)
- Affinity chromatography (2)
- Antibody identification (2)
- Database (2)
- Diagnostics (2)
Organisationseinheit der BAM
The cowpea chlorotic mottle virus (CCMV) is a plant virus explored as a nanotechnological platform. The robust self-assembly mechanism of its capsid protein allows for drug encapsulation and targeted delivery. Additionally, the capsid nanoparticle can be used as a programmable platform to display different molecular moieties. In view of future applications, efficient production and purification of plant viruses are key steps. In established protocols, the need for ultracentrifugation is a significant limitation due to cost, difficult scalability, and safety issues. In addition, the purity of the final virus isolate often remains unclear. Here, an advanced protocol for the purification of the CCMV from infected plant tissue was developed, focusing on efficiency, economy, and final purity. The protocol involves precipitation with PEG 8000, followed by affinity extraction using a novel peptide aptamer. The efficiency of the protocol was validated using size exclusion chromatography, MALDI-TOF mass spectrometry, reversed-phase HPLC, and sandwich immunoassay. Furthermore, it was demonstrated that the final eluate of the affinity column is of exceptional purity (98.4%) determined by HPLC and detection at 220 nm. The scale-up of our proposed method seems to be straightforward, which opens the way to the large-scale production of such nanomaterials. This highly improved protocol may facilitate the use and implementation of plant viruses as nanotechnological platforms for in vitro and in vivo applications.
Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly
(2023)
Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody–antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69–99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.
MALDI-TOF-MS-Based Identification of Monoclonal Murine Anti-SARS-CoV-2 Antibodies within One Hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Im Vergleich zu anderen Proteinen ist die Identifizierung von Antikörpern anhand ihrer Sequenz zum Beispiel mittels "peptide mass fingerprinting" schwierig. Da die Sequenzinformation eines Antikörpers aufgrund der hypersomatischen Mutation während der Affinitätsreifung nicht im Genom eines Organismus gespeichert ist, kann die Aminosäuresequenz nicht auf einfachem Weg der DNA-Sequenzierung gewonnen werden. Das ist nur in seltenen Fällen möglich, wenn dem Endanwender der Zellklon der Antikörper-produzierenden Zelle zugänglich ist. Eine Sequenzierung auf Protein-Ebene ist sehr aufwändig und teuer und wird daher fast nie für die Charakterisierung von analytischen Antikörpern verwendet. Der Mangel an Validierung dieser analytischen Antikörper, die bei Experimenten verwendeten werden, löst aber eine Reihe Probleme aus, die die Wiederholbarkeit dieser Experimente schwierig und in einigen Fällen unmöglich macht. Das sorgt jährlich für verschwendete Forschungsgelder in Milliardenhöhe und hindert den wissenschaftlichen Fortschritt.
Ziel der vorliegenden Arbeit war die Entwicklung einer einfachen und schnellen Methode, die es trotzdem ermöglicht, die Identifikation von Antikörpern sicherzustellen. Dazu wurde eine Methode basierend auf dem "peptide mass fingerprinting" gewählt. Das Problem der unbekannten Aminosäuresequenz der Antikörper wurde gelöst, indem lediglich die Peptidmuster der entstehenden Fingerprint-Spektren zur Identifikation herangezogen wurden. MALDI wurde dabei als Ionisationsmethode für die Massenspektrometrie gewählt, da die resultierenden Spektren im Gegensatz zu ESI-MS einfach auszuwerten sind. Auch kann auf eine vorige Trennung der Peptide mittels LC verzichtet werden, was zusätzlich Analysenzeit spart. Für die Proteinspaltung wurde eine simple saure Hydrolyse mittels Ameisensäure gewählt. Im Vergleich zum herkömmlichen Trypsin-Verdau konnten auf zeitraubende Arbeitsschritte wie Denaturierung, Reduktion und Alkylierung der Antikörper verzichtet werden. Die Hydrolyse mittels Ameisensäure wurde bisher nur auf kleine und mittelgroße Proteine angewendet, sodass im ersten Teil dieser Arbeit mehrere Schritte optimiert wurden bevor zufriedenstellende Fingerprint-Spektren von Antikörpern erhalten wurden.
Fast and accurate determination of the protein content of a sample is an important and non-trivial task of many biochemical, biomedical, food chemical, pharmaceutical, and environmental research activities. Different methods of total protein determination are used for a wide range of proteins with highly variable properties in complex matrices. These methods usually work reasonably well for proteins under controlled conditions, but the results for non-standard and complex samples are often questionable. Here, we compare new and well-established methods, including traditional amino acid analysis (AAA), aromatic amino acid analysis (AAAA) based on the amino acids phenylalanine and tyrosine, reversed-phase liquid chromatography of intact proteins with UV absorbance measurements at 220 and 280 nm (LC-220, LC-280), and colorimetric assays like Coomassie Blue G-250 dye-binding assay (Bradford) and bicinchoninic acid (BCA) assay. We investigated different samples, including proteins with challenging properties, chemical modifications, mixtures, and complex matrices like air particulate matter and pollen extracts. All methods yielded accurate and precise results for the protein and matrix used for calibration. AAA, AAAA with fluorescence detection, and the LC-220 method yielded robust results even under more challenging conditions (variable analytes and matrices). These methods turned out to be well-suited for reliable determination of the protein content in a wide range of samples, such as air particulate matter and pollen.
MALDI-TOF-MS-based identification of monoclonal murine anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used thirty-five monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied onto the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 45 minutes and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 °C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0 (https://gets.shinyapps.io/ABID/). This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The trafficking of illegal drugs by criminal networks at borders, harbors, or airports is an increasing issue for public health as these routes ensure the main supply of illegal drugs. The prevention of drug smuggling, including the installation of scanners and other analytical devices to detect small traces of drugs within a reasonable time frame, remains a challenge. The presented immunosensor is based on a monolithic affinity column with a large excess of immobilized hapten, which traps fluorescently labeled antibodies as long as the analyte cocaine is absent. In the presence of the drug, some binding sites of the antibody will be blocked, which leads to an immediate breakthrough of the labeled protein, detectable by highly sensitive laser-induced fluorescence with the help of a Peltier-cooled complementary metal-oxide-semiconductor (CMOS) camera. Liquid handling is performed with high-precision syringe pumps and microfluidic chip-based mixing devices and flow cells. The biosensor achieved limits of detection of 7 ppt (23 pM) of cocaine with a response time of 90 s and a total assay time below 3 min. With surface wipe sampling, the biosensor was able to detect 300 pg of cocaine. This immunosensor belongs to the most sensitive and fastest detectors for cocaine and offers near-continuous analyte measurement.
Antibodies are the most used biomolecules in analytical research. Nevertheless, the sequence and structure information of antibodies is often limited, since manufacturers keep them secret or suppliers sell them under different names. This can make it difficult to reproduce even basic experiments performed in publications as the antibodies used might not be identifiable. To overcome these problems, we developed a simple and cheap method for antibody identification by MALDI-TOF-MS fingerprinting. This technique was used to generate a library of antibody fingerprints, which enables the identification and comparison of antibodies in short time.
The trafficking of illegal drugs by criminal networks at borders, harbors, or airports is an increasing issue in public health as these routes ensure the main supply of illegal drugs. The prevention of drug smuggling, including the installation of scanners and other analytical devices to detect ultra-small traces of drugs within a reasonable time frame, remains a challenge. The presented immunosensor is based on a monolithic affinity column with a large excess of immobilized hapten, which traps fluorescently labeled antibodies as long as the analyte cocaine is absent. In the presence of the drug, some binding sites of the antibody will be blocked, which leads to an immediate breakthrough of the labeled protein, detectable by highly sensitive laser-induced fluorescence with the help of a Peltier-cooled complementary metal-oxide-semiconductor (CMOS) camera. Liquid handling is performed with high-precision syringe pumps and microfluidic chip-based mixing devices and flow cells. The biosensor achieved limits of detection of 23 pM (7 ppt) of cocaine with a response time of 90 seconds and a total assay time below 3 minutes. With surface wipe sampling, the biosensor was able to detect 300 pg of cocaine. This immunosensor belongs to the most sensitive and fastest detectors for cocaine and offers near-continuous analyte measurement.
The allergenic and inflammatory potential of proteins can be enhanced by chemical modification upon exposure to atmospheric or physiological oxidants. The molecular mechanisms and kinetics of such modifications, however, have not yet been fully resolved. We investigated the oligomerization and nitration of the grass pollen allergen Phl p 5 by ozone (O3), nitrogen dioxide (NO2), and peroxynitrite (ONOO–). Within several hours of exposure to atmospherically relevant concentration levels of O3 and NO2, up to 50% of Phl p 5 were converted into protein oligomers, likely by formation of dityrosine cross-links. Assuming that tyrosine residues are the preferential site of nitration, up to 10% of the 12 tyrosine residues per protein monomer were nitrated. For the reaction with peroxynitrite, the largest oligomer mass fractions (up to 50%) were found for equimolar concentrations of peroxynitrite over tyrosine residues. With excess peroxynitrite, the nitration degrees increased up to 40% whereas the oligomer mass fractions decreased to 20%. Our results suggest that protein oligomerization and nitration are competing processes, which is consistent with a two-step mechanism involving a reactive oxygen intermediate (ROI), as observed for other proteins. The modified proteins can promote pro-inflammatory cellular signaling that may contribute to chronic inflammation and allergies in response to air pollution.