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A whole-genome bioinformatics approach to selection of antigens for systematic antibody generation
KTH, School of Biotechnology (BIO).
KTH, School of Biotechnology (BIO).
KTH, School of Biotechnology (BIO).
KTH, School of Biotechnology (BIO).ORCID iD: 0000-0002-9977-5724
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2008 (English)In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 8, no 14, 2832-2839 p.Article in journal (Refereed) Published
Abstract [en]

Here, we present an antigen selection strategy based on a whole-genome bioinformatics approach, which is facilitated by an interactive visualization tool displaying protein features from both public resources and in-house generated data. The web-based bioinformatics platform has been designed for selection of multiple, non-overlapping recombinant protein epitope signature tags by display of predicted information relevant for antigens, including domain- and epitope sized sequence similarities to other proteins, transmembrane regions and signal peptides. The visualization tool also displays shared and exclusive protein regions for genes with multiple splice variants. A genome-wide analysis demonstrates that antigens for approximately 80% of the human protein-coding genes can be selected with this strategy.

Place, publisher, year, edition, pages
2008. Vol. 8, no 14, 2832-2839 p.
Keyword [en]
antibody generation, antigen selection, bioinformatics, epitope, sequence similarity, CELL EPITOPE PREDICTION, HUMAN PROTEOME, B-CELL, DETERMINANTS, EXPRESSION, PROTEINS, PROGRAM, SITES, ATLAS, GENE
National Category
Industrial Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-8256DOI: 10.1002/pmic.200800203ISI: 000258117400007Scopus ID: 2-s2.0-48949107645OAI: oai:DiVA.org:kth-8256DiVA: diva2:13530
Note
QC 20100705Available from: 2008-04-22 Created: 2008-04-22 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Methods for Generation and Characterization of Monospecific Antibodies
Open this publication in new window or tab >>Methods for Generation and Characterization of Monospecific Antibodies
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Recent advances in biotechnology have generated possibilities to investigate and measure parts of life previously left for believers to explain. Utilizing the same book of recipes, the genome, our cells produce selections of proteins at a time and thereby niche into a multitude of specialized cell types, tissues and organs comprising our body. Knowledge of the precise protein composition in a given organ at normal and disease condition would be of invaluable importance, both for identification of disease causes and the design of new pharmaceuticals, as well as for a deeper understanding of the processes of life. This doctoral thesis describes the start and progress of a visionary project (HPR) to localize all human proteins in our body, with emphasis on the generation and characterization of antibodies used as protein targeting missiles. To facilitate the identification of one human protein in a complex environment like our body, it is of significant importance to have precise and specific means of detection. The first two papers (I-II), describe software developed for generation of monospecific antibodies satisfying such needs, using a set of rules for antigen optimization. Five years after project start a large amount of antibodies with documented characteristics have been generated. The third paper (III), illustrates an attempt to sieve these antibody characteristics to develop a tool, for further improvement of antigen selection, based on the correlation between antigen sequence and amount of specific antibody generated.Having a panel of protein-specific antibodies is a possession of a great value, not only for localization studies, but also as possible target-directed pharmaceuticals. In such cases, knowledge of the precise epitope recognized by the antibody on its target protein, is an important aid, both for understanding its effect as well as unwanted cross-reactivity. Paper (IV) describes the development of a high-resolution method for epitope mapping of antibodies using staphylococcal display. An application of the method is described in the last paper (V) where it is used to map an anti-HER2 monospecific antibody with growth-inhibiting effects on breast cancer cells. The monospecific antibody was fractionated into separate populations and five novel epitopes related to cancer cell growth-inhibition was determined.Altogether these methods are valuable tools for generation and characterization of monospecific antibodies.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. xii, 66 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2008:20
Keyword
antibody, epitope mapping, HER2, human protein atlas, immunogenicity, proteomics
National Category
Industrial Biotechnology
Identifiers
urn:nbn:se:kth:diva-9338 (URN)978-91-7415-139-8 (ISBN)
Public defence
2008-10-31, F3, KTH, Lindstedtsvägen 26, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
QC 20100907Available from: 2008-10-21 Created: 2008-10-21 Last updated: 2010-09-07Bibliographically approved
2. Selection of antigens for antibody-based proteomics
Open this publication in new window or tab >>Selection of antigens for antibody-based proteomics
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

The human genome is predicted to contain ~20,500 protein-coding genes. The encoded proteins are the key players in the body, but the functions and localizations of most proteins are still unknown. Antibody-based proteomics has great potential for exploration of the protein complement of the human genome, but there are antibodies only to a very limited set of proteins. The Human Proteome Resource (HPR) project was launched in August 2003, with the aim to generate high-quality specific antibodies towards the human proteome, and to use these antibodies for large-scale protein profiling in human tissues and cells.

The goal of the work presented in this thesis was to evaluate if antigens can be selected, in a high-throughput manner, to enable generation of specific antibodies towards one protein from every human gene. A computationally intensive analysis of potential epitopes in the human proteome was performed and showed that it should be possible to find unique epitopes for most human proteins. The result from this analysis was implemented in a new web-based visualization tool for antigen selection. Predicted protein features important for antigen selection, such as transmembrane regions and signal peptides, are also displayed in the tool. The antigens used in HPR are named protein epitope signature tags (PrESTs). A genome-wide analysis combining different protein features revealed that it should be possible to select unique, 50 amino acids long PrESTs for ~80% of the human protein-coding genes.

The PrESTs are transferred from the computer to the laboratory by design of PrEST-specific PCR primers. A study of the success rate in PCR cloning of the selected fragments demonstrated the importance of controlled GC-content in the primers for specific amplification. The PrEST protein is produced in bacteria and used for immunization and subsequent affinity purification of the resulting sera to generate mono-specific antibodies. The antibodies are tested for specificity and approved antibodies are used for tissue profiling in normal and cancer tissues. A large-scale analysis of the success rates for different PrESTs in the experimental pipeline of the HPR project showed that the total success rate from PrEST selection to an approved antibody is 31%, and that this rate is dependent on PrEST length. A second PrEST on a target protein is somewhat less likely to succeed in the HPR pipeline if the first PrEST is unsuccessful, but the analysis shows that it is valuable to select several PrESTs for each protein, to enable generation of at least two antibodies, which can be used to validate each other.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. 65 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2008:5
Keyword
epitope, antigen, antibody, affinity, protein, proteome, proteomics, bioinformatics, prediction, primer design, sequence similarity
National Category
Industrial Biotechnology
Identifiers
urn:nbn:se:kth:diva-4706 (URN)978-91-7178-930-3 (ISBN)
Public defence
2008-05-09, F3, Lindstedsvägen 26, Stockholm, 10:00
Opponent
Supervisors
Note
QC 20100705Available from: 2008-04-22 Created: 2008-04-22 Last updated: 2010-09-15Bibliographically approved

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Fagerberg, LinnAl-Khalili Szigyarto, CristinaUhlén, Mathias

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