ArticleBioinformatics and biology insights2020
Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA.
Article in Bioinformatics and biology insights, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Phage Display Technology: Design, Library Construction, and Panning Strategies for Antibody Development.Biomolecules & therapeutics · 2026Review
- Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data.Bioinformatics (Oxford, England) · 2023Article
- New Anti-Flavivirus Fusion Loop Human Antibodies with Zika Virus-Neutralizing Potential.International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs).
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Registered trials
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