Biology subjects

Greiff, V.

Publications and source records attributed to Greiff, V..

3 recordsLinked to original sources

bioRxiv2018

High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis

Antibody engineering is performed to improve therapeutic properties by directed evolution, usually by high-throughput screening of phage or yeast display libraries. Engineering antibodies in mammalian cells offers advantages associated with expression in their final therapeutic format (full-length glycosylated IgG), however, the inability to express large and diverse libraries severely limits their potential throughput. To address this limitation, we have developed homology-directed mutagenesis (HDM), a novel method which extends the concept of CRISPR/Cas9-mediated homology-directed repair (HDR). HDM leverages oligonucleotides with degenerate codons to generate site-directed mutagenesis libraries in mammalian cells. By improving HDM efficiency (>35-fold) and combining mammalian display screening with next-generation sequencing (NGS), we validated this approach can be used for key applications in antibody engineering at high-throughput: rational library construction, novel variant discovery, affinity maturation, and deep mutational scanning (DMS). We anticipate that HDM will be a valuable tool for engineering and optimizing antibodies in mammalian cells, and eventually enable directed evolution of other complex proteins and cellular therapeutics.

bioengineering↗

bioRxiv2017

Learning The High-Dimensional Immunogenomic Features That Predict Public And Private Antibody Repertoires

Recent studies have revealed that immune repertoires contain a substantial fraction of public clones, which are defined as antibody or T-cell receptor (TCR) clonal sequences shared across individuals. As of yet, it has remained unclear whether public clones possess predictable sequence features that separate them from private clones, which are believed to be generated largely stochastically. This knowledge gap represents a lack of insight into the shaping of immune repertoire diversity. Leveraging a machine learning approach capable of capturing the high-dimensional compositional information of each clonal sequence (defined by the complementarity determining region 3, CDR3), we detected predictive public- and private-clone-specific immunogenomic differences concentrated in the CDR3s N1-D-N2 region, which allowed the prediction of public and private status with 80% accuracy in both humans and mice. Our results unexpectedly demonstrate that not only public but also private clones possess predictable high-dimensional immunogenomic features. Our support vector machine model could be trained effectively on large published datasets (3 million clonal sequences) and was sufficiently robust for public clone prediction across studies prepared with different library preparation and high-throughput sequencing protocols. In summary, we have uncovered the existence of high-dimensional immunogenomic rules that shape immune repertoire diversity in a predictable fashion. Our approach may pave the way towards the construction of a comprehensive atlas of public clones in immune repertoires, which may have applications in rational vaccine design and immunotherapeutics.

systems biology↗

bioRxiv2017

The fundamental principles of antibody repertoire architecture revealed by large-scale network analysis

The antibody repertoire is a vast and diverse collection of B-cell receptors and antibodies that confer protection against a plethora of pathogens. The architecture of the antibody repertoire, defined by the network similarity landscape of its sequences, is unknown. Here, we established a novel high-performance computing platform to construct large-scale networks from high-throughput sequencing data (>100000 unique antibodies), in order to uncover the architecture of antibody repertoires. We identified three fundamental principles of antibody repertoire architecture across B-cell development: reproducibility, robustness and redundancy. Reproducibility of network structure explains clonal expansion and selection. Robustness ensures a functional immune response even under extensive loss of clones (50%). Redundancy in mutational pathways suggests that there is a pre-programmed evolvability in antibody repertoires. Our analysis provides guidelines for a quantitative network analysis of antibody repertoires, which can be applied to other facets of adaptive immunity (e.g., T cell receptors), and may direct the construction of synthetic repertoires for biomedical applications.

systems biology↗