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IgRepertoireConstructor: a novel algorithm for antibody repertoire construction and immunoproteogenomics analysis.

Safonova Y, Bonissone S, Kurpilyansky E, Starostina E, Lapidus A, Stinson J, DePalatis L, Sandoval W, Lill J, Pevzner PA - Bioinformatics (2015)

Bottom Line: Therefore, the protein database required for the interpretation of spectra from circulating antibodies is custom for each individual.Although such a database can be constructed via NGS, the reads generated by NGS are error-prone and even a single nucleotide error precludes identification of a peptide by the standard proteomics tools.IgRepertoireConstructor is open source and freely available as a C++ and Python program running on all Unix-compatible platforms.

View Article: PubMed Central - PubMed

Affiliation: Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA.

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(a) An overview of immunoglobulin (Ig-seq) sequencing. Briefly, B-cells are isolated; transcripts are purified; antibody chains are amplified by PCR; and finally, paired-end sequencing of the Ig variable region is performed on the amplified Ig transcript molecules. (b) An antibody repertoire containing five different antibodies (shown on the left) is characterized by a set of pairs <sequence, abundance > (shown on the right). For example, the abundance of the ‘red’ antibody is 3. (c) The varying levels of sequence information. First, the paired reads are stitched together to form contiguous reads. These reads are then compressed to unique reads with count information, and finally clustered reads. E.g. the red and blue unique reads (with counts 3 and 1) are clustered into a single cluster with count 4 because they represent reads (with errors) derived from the same antibody. (d) Reads are partitioned according to identical CDR3 sequences (shown in the black rectangles). Each resulting cluster of antibodies is referred to as a clone
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btv238-F1: (a) An overview of immunoglobulin (Ig-seq) sequencing. Briefly, B-cells are isolated; transcripts are purified; antibody chains are amplified by PCR; and finally, paired-end sequencing of the Ig variable region is performed on the amplified Ig transcript molecules. (b) An antibody repertoire containing five different antibodies (shown on the left) is characterized by a set of pairs <sequence, abundance > (shown on the right). For example, the abundance of the ‘red’ antibody is 3. (c) The varying levels of sequence information. First, the paired reads are stitched together to form contiguous reads. These reads are then compressed to unique reads with count information, and finally clustered reads. E.g. the red and blue unique reads (with counts 3 and 1) are clustered into a single cluster with count 4 because they represent reads (with errors) derived from the same antibody. (d) Reads are partitioned according to identical CDR3 sequences (shown in the black rectangles). Each resulting cluster of antibodies is referred to as a clone

Mentions: Until 2009, the computational analysis of antibodies had been performed via proteomics techniques (Bandeira et al.., 2008) and had not utilized DNA sequencing technologies. Weinstein et al. (2009) were the first to demonstrate the power of DNA sequencing for analyzing antibody repertoires and to open a ‘next generation sequencing (NGS) era’ in antibody analysis (Fig. 1a). Although this study was quickly followed by many other immunosequencing (Ig-seq) studies (Arnaout et al., 2011; Jiang et al., 2011, 2013; Laserson et al. 2014; Vollmers et al.., 2013); until 2012, there were no attempts to integrate NGS and mass spectrometry (MS) approaches for antibody analysis. Such integration (immunoproteogenomics) is important since it represents a bottleneck for an emerging approach that promises to transform the antibody industry from focusing on single (monoclonal) antibodies, toward analyzing polyclonal antibodies.Fig. 1.


IgRepertoireConstructor: a novel algorithm for antibody repertoire construction and immunoproteogenomics analysis.

Safonova Y, Bonissone S, Kurpilyansky E, Starostina E, Lapidus A, Stinson J, DePalatis L, Sandoval W, Lill J, Pevzner PA - Bioinformatics (2015)

(a) An overview of immunoglobulin (Ig-seq) sequencing. Briefly, B-cells are isolated; transcripts are purified; antibody chains are amplified by PCR; and finally, paired-end sequencing of the Ig variable region is performed on the amplified Ig transcript molecules. (b) An antibody repertoire containing five different antibodies (shown on the left) is characterized by a set of pairs <sequence, abundance > (shown on the right). For example, the abundance of the ‘red’ antibody is 3. (c) The varying levels of sequence information. First, the paired reads are stitched together to form contiguous reads. These reads are then compressed to unique reads with count information, and finally clustered reads. E.g. the red and blue unique reads (with counts 3 and 1) are clustered into a single cluster with count 4 because they represent reads (with errors) derived from the same antibody. (d) Reads are partitioned according to identical CDR3 sequences (shown in the black rectangles). Each resulting cluster of antibodies is referred to as a clone
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4542777&req=5

btv238-F1: (a) An overview of immunoglobulin (Ig-seq) sequencing. Briefly, B-cells are isolated; transcripts are purified; antibody chains are amplified by PCR; and finally, paired-end sequencing of the Ig variable region is performed on the amplified Ig transcript molecules. (b) An antibody repertoire containing five different antibodies (shown on the left) is characterized by a set of pairs <sequence, abundance > (shown on the right). For example, the abundance of the ‘red’ antibody is 3. (c) The varying levels of sequence information. First, the paired reads are stitched together to form contiguous reads. These reads are then compressed to unique reads with count information, and finally clustered reads. E.g. the red and blue unique reads (with counts 3 and 1) are clustered into a single cluster with count 4 because they represent reads (with errors) derived from the same antibody. (d) Reads are partitioned according to identical CDR3 sequences (shown in the black rectangles). Each resulting cluster of antibodies is referred to as a clone
Mentions: Until 2009, the computational analysis of antibodies had been performed via proteomics techniques (Bandeira et al.., 2008) and had not utilized DNA sequencing technologies. Weinstein et al. (2009) were the first to demonstrate the power of DNA sequencing for analyzing antibody repertoires and to open a ‘next generation sequencing (NGS) era’ in antibody analysis (Fig. 1a). Although this study was quickly followed by many other immunosequencing (Ig-seq) studies (Arnaout et al., 2011; Jiang et al., 2011, 2013; Laserson et al. 2014; Vollmers et al.., 2013); until 2012, there were no attempts to integrate NGS and mass spectrometry (MS) approaches for antibody analysis. Such integration (immunoproteogenomics) is important since it represents a bottleneck for an emerging approach that promises to transform the antibody industry from focusing on single (monoclonal) antibodies, toward analyzing polyclonal antibodies.Fig. 1.

Bottom Line: Therefore, the protein database required for the interpretation of spectra from circulating antibodies is custom for each individual.Although such a database can be constructed via NGS, the reads generated by NGS are error-prone and even a single nucleotide error precludes identification of a peptide by the standard proteomics tools.IgRepertoireConstructor is open source and freely available as a C++ and Python program running on all Unix-compatible platforms.

View Article: PubMed Central - PubMed

Affiliation: Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA.

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