Assessment of antibody library diversity through next generation sequencing and technical error compensation

• DOI: 10.1371/journal.pone.0177574
• Publication Date: 2017-05-15T14:07:11Z
• Authors: Marco Fantini; Luca Pandolfini; Simonetta Lisi; Michele Chirichella; Ivan Arisi; Marco Terrigno; Martina Goracci; Federico Cremisi; Antonino Cattaneo
• Keywords: 0301 basic medicine; 0303 health sciences; anticorpi; sequenziamento; librerie; bioinformatica; Science; Q; R; Computational Biology; High-Throughput Nucleotide Sequencing; Antibodies; V(D)J Recombination; Workflow; 03 medical and health sciences; Medicine; Cluster Analysis; Humans; Computer Simulation; Research Article; Antibody Diversity; Gene Library; Single-Chain Antibodies

Antibody libraries are important resources to derive antibodies be used for a wide range of applications, from structural and functional studies intracellular protein interference developing new diagnostics therapeutics. Whatever the goal, key parameter an antibody library is its complexity (also known as diversity), i.e. number distinct elements in collection, which directly reflects probability finding against given antigen, sufficiently high affinity. Quantitative evaluation quality has been long time inadequately addressed, due similarity length sequences library. Complexity was usually inferred by transformation efficiency tested either fingerprinting and/or sequencing few hundred random elements. Inferring such small sampling is, however, very rudimental gives limited information about real diversity, because does not scale linearly with sample size. Next-generation (NGS) opened ways tackle assessment. However, much remains done fully exploit potential NGS quantitative analysis repertoires overcome current limitations. To obtain more reliable estimate here we show new, PCR-free, approach sequence on Illumina platform, coupled bioinformatic software (Diversity Estimator Library, DEAL) that allows reliably complexity, taking consideration error.