RTN4RL1 Recombinant Monoclonal Antibody

RTN4RL1, also known as Nogo receptor-like 2 or NgR3, belongs to the Nogo receptor family that plays important roles in regulating axonal regeneration and neural plasticity. As a member of this receptor family, RTN4RL1 participates in signaling pathways that influence neuronal growth and connectivity, making it a valuable target for researchers investigating nervous system development, injury response, and neurodegenerative conditions.

This recombinant rabbit monoclonal antibody, clone 5C1, offers the consistency and reliability that demanding experimental workflows require. Generated against a synthetic peptide derived from human RTN4RL1, the antibody is produced using recombinant technology, ensuring sequence-defined specificity and eliminating the lot-to-lot variability that can compromise longitudinal studies or multi-site collaborations. Affinity chromatography purification further enhances performance by removing non-specific immunoglobulins.

Validation studies demonstrate this antibody's versatility across multiple detection platforms. Immunohistochemistry performed on paraffin-embedded human brain and kidney tissues using a Leica Bond system shows clear target detection at 1:100 dilution following citrate buffer antigen retrieval. Flow cytometry analysis using MCF-7 cells confirms intracellular detection capability, with fixed and permeabilized cells showing distinct positive signal separation from isotype control when stained at 1:100 dilution. These validated applications provide researchers flexibility in experimental design, whether examining tissue architecture or analyzing protein expression at the single-cell level.

The unconjugated format allows pairing with detection systems of choice, supporting integration into established laboratory protocols. For neuroscience researchers exploring Nogo receptor family biology or those investigating RTN4RL1 expression patterns in human tissues, this antibody delivers the reproducible performance essential for generating publication-quality data.