title: Deep Panning: steps towards probing the IgOme.
abstract: BACKGROUND
  Polyclonal serum consists of vast collections of antibodies, products of differentiated B-cells. The spectrum of antibody specificities is dynamic and varies with age, physiology, and exposure to pathological insults. The complete repertoire of antibody specificities in blood, the IgOme, is therefore an extraordinarily rich source of information-a molecular record of previous encounters as well as a status report of current immune activity. The ability to profile antibody specificities of polyclonal serum at exceptionally high resolution has been an important and serious challenge which can now be overcome.
  
  
  RESULTS
  Here we illustrate the application of Deep Panning, a method that combines the flexibility of combinatorial phage display of random peptides with the power of high-throughput deep sequencing. Deep Panning is first applied to evaluate the quality and diversity of naïve random peptide libraries. The production of very large data sets, hundreds of thousands of peptides, has revealed unexpected properties of combinatorial random peptide libraries and indicates correctives to ensure the quality of the libraries generated. Next, Deep Panning is used to analyze a model monoclonal antibody in addition to allowing one to follow the dynamics of biopanning and peptide selection. Finally Deep Panning is applied to profile polyclonal sera derived from HIV infected individuals.
  
  
  CONCLUSIONS
  The ability to generate and characterize hundreds of thousands of affinity-selected peptides creates an effective means towards the interrogation of the IgOme and understanding of the humoral response to disease. Deep Panning should open the door to new possibilities for serological diagnostics, vaccine design and the discovery of the correlates of immunity to emerging infectious agents.
authors.affiliation: Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Arie
authors.initials: A
authors.lastname: Ryvkin
authors.forename: Haim
authors.initials: H
authors.lastname: Ashkenazy
authors.forename: Larisa
authors.initials: L
authors.lastname: Smelyanski
authors.forename: Gilad
authors.initials: G
authors.lastname: Kaplan
authors.forename: Osnat
authors.initials: O
authors.lastname: Penn
authors.forename: Yael
authors.initials: Y
authors.lastname: Weiss-Ottolenghi
authors.forename: Eyal
authors.initials: E
authors.lastname: Privman
authors.forename: Peter B
authors.initials: PB
authors.lastname: Ngam
authors.forename: James E
authors.initials: JE
authors.lastname: Woodward
authors.forename: Gregory D
authors.initials: GD
authors.lastname: May
authors.forename: Callum
authors.initials: C
authors.lastname: Bell
authors.forename: Tal
authors.initials: T
authors.lastname: Pupko
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Gershoni
mesh_terms: D000911:Antibodies, Monoclonal / Q000737:chemistry* / Q000235:genetics / Q000276:immunology; D000918:Antibody Specificity; D001402:B-Lymphocytes / Q000737:chemistry / Q000276:immunology; D006801:Humans; D019151:Peptide Library
chemical_list: D000911:Antibodies, Monoclonal; D019151:Peptide Library