IgM

IgM profiles the human public IgM repertoire using a scalable mimotope library to enable diagnostic biomarker discovery.

Key Features:

• Rationally Designed Peptide Arrays: Peptide arrays are used as probes for system-level biomarkers, providing analysis beyond immunodominant self-proteins.
• Mimotope Library Generation: A mimotope library was constructed from the common IgM repertoire of 10,000 healthy donors.
• Phage Display and Next-Generation Sequencing: A 7-mer random peptide phage display library was panned against pooled human IgM and next-generation sequencing identified 224,087 selected sequences clustered into 790 sequence clusters.
• Representative Mimotope Subset: A subset of 594 mimotopes was selected to symmetrically probe the IgM reactivity space, with scalability to increase array size and resolution.
• Idiotypic Connectivity Analysis: BLAST searches against non-redundant protein databases revealed significant immunoglobulin J region hits among mimotope sequences.
• Diagnostic Predictor Construction: Mimotope reactivity profiles generate over 10^70 potential profiles, enabling feature selection and predictor model construction for diagnostics.

Scientific Applications:

• Biomarker Discovery: Profiling IgM reactivities to identify antibody biomarkers relevant for disease diagnosis.
• Disease Profiling: Symmetric sampling of mimotope sequence and reactivity spaces to support detailed immune-response profiling across diseases.
• Antibody Repertoire Research: Investigation of the public IgM repertoire properties such as limited somatic mutation, polyspecificity, and physiological autoreactivity.

Methodology:

Panning a 7-mer random peptide phage display library against pooled human IgM, next-generation sequencing of selected phages (224,087 sequences), clustering into 790 sequence clusters, selection of 594 representative mimotopes, BLAST searches against non-redundant protein databases to identify immunoglobulin J region hits, and construction of mimotope reactivity profiles for feature selection and predictor model building.