Rabbit monoclonal antibodies: Synergistic innovation and breakthrough based on B-cell development mechanism and single B-cell technology

Rabbit monoclonal antibodies (RabMabs) exhibit high affinity, specificity, sensitivity, and broad antigen recognition, offering considerable potential for biomedical applications. These unique advantages derive from the distinct B-cell developmental machinery in rabbits, which encompasses not only somatic hypermutation but also gene conversion in intestinal tissues, thereby enhancing the diversity of the antibody repertoire and promoting antibody affinity maturation. However, large-scale production and industrial-scale implementation of RabMabs remain challenged by patent barriers related to cell fusion technologies and the inherent limitations of current antibody screening methodologies. In this review, we systematically examine the latest advancements in core RabMab preparation technologies, including hybridoma technology, phage display systems, and the recently emerging single B-cell antibody screening approaches. Notably, microfluidic-based single-cell analysis platforms can achieve high-precision manipulation and high-throughput screening of individual B cells, representing a breakthrough in single-cell sorting efficiency. Nevertheless, the current lack of universally applicable surface markers for rabbit B cells, particularly plasma cells, remains a critical bottleneck, restricting both cell sorting efficiency and the success rate of antibody gene isolation. Therefore, we review the recent progress in the identification of rabbit B-cell surface markers, with a focus on their application in improving sorting strategies. Meanwhile, we deeply discuss the prospective integration of precise microfluidic operation systems, single-cell reverse transcription PCR (scRT-PCR) with next-generation sequencing, and artificial intelligence (AI) algorithms into the antibody discovery pipeline. These technologies hold promise for overcoming current technical hurdles, streamlining the screening workflow, and accelerating the translation of RabMabs from bench to bedside.