Skip to main content English

Detail

Mohammed Zghaebi
Mohammed Zghaebi, MSc PhDSenior Scientist (Postdoc)

Center for Pathophysiology, Infectiology and Immunology, Department of Otorhinolaryngology
Position: Research Associate (Postdoc)

ORCID: 0000-0002-7636-2601
mohammed.zghaebi@meduniwien.ac.at

Keywords

Allergy and Immunology; Antibodies; Artificial Intelligence; Computational Biology; High-Throughput Nucleotide Sequencing; Immunity, Mucosal; Immunoglobulin E; Immunologic Memory; Inflammation; Receptors, Antigen, B-Cell; Single-Cell Analysis

Research group(s)

Research interests

    Scientific goal: To understand how cellular immunity is generated, maintained, and organised across blood and mucosal tissue, and to translate these insights into new therapeutic strategies for immune diseases.

    Areas of research:

    1. Immune memory and recall responses: I study how immunological memory arises and is re-activated, using controlled provocation to track antigen-specific B cell dynamics in humans over time.
    2. B cell repertoire and clonal architecture: Combining deep BCR sequencing of matched blood and tissue with clonal lineage tracking, I map how antigen-specific clones are distributed across anatomical compartments.
    3. Upper airway disease: I investigate B cell contributions to chronic rhinosinusitis, nasal polyps, and respiratory allergy, aiming to connect local mucosal immunity to systemic responses.
    4. Therapeutic targeting: Drawing on cellular therapy cohorts, I examine how interventions such as anti-CD19 CAR-T reshape the antibody landscape, identifying candidate vulnerabilities in immune diseases.
    5. Computational immunology: I apply high-dimensional cytometry clustering and repertoire analysis to extract mechanistic insight from longitudinal immune datasets.

    Website: https://www.viairlab.com/

    Social media: https://www.linkedin.com/in/mozg/

Techniques, methods & infrastructure

    Core methods include multiparameter flow cytometry and cell sorting of rare allergen-specific B cell populations, deep B cell receptor (BCR) repertoire sequencing of matched blood and mucosal tissue, confocal microscopy of lymphoid tissue, cell culture, and computational analysis of longitudinal immune data (including high-dimensional cytometry clustering and clonal lineage reconstruction).

Selected publications

  1. Zghaebi, M. et al. (2021) “Tracing Human IgE B Cell Antigen Receptor-Bearing Cells With a Monoclonal Anti-Human IgE Antibody That Specifically Recognizes Non-Receptor-Bound IgE,” Frontiers in Immunology. Edited by , 12. Available at: https://doi.org/10.3389/fimmu.2021.803236.
  2. Campion, N.J. et al. (2023) “Nasal IL-13 production identifies patients with late-phase allergic responses,” Journal of Allergy and Clinical Immunology. Edited by , 152(5), pp. 1167–1178.e12. Available at: https://doi.org/10.1016/j.jaci.2023.06.026.
  3. Morgenstern, C. et al. (2026) “Proteomic profiling and machine learning for endotype prediction in chronic rhinosinusitis,” Journal of Allergy and Clinical Immunology. Edited by , 157(1), pp. 190–202. Available at: https://doi.org/10.1016/j.jaci.2025.08.025.
  4. Campion, N.J. et al. (2026) “Kinetics of Antibody Responses and Effector Cell Sensitivity After High Dose Birch Extract Nasal Challenge,” Allergy [Preprint]. Edited by . Available at: https://doi.org/10.1111/all.70365.
  5. Zettl, I. et al. (2022) “Generation of high affinity ICAM-1-specific nanobodies and evaluation of their suitability for allergy treatment,” Frontiers in Immunology. Edited by , 13. Available at: https://doi.org/10.3389/fimmu.2022.1022418.