Integrin α4 Antibody

About the Target

Integrin α4 (CD49d), encoded by the ITGA4 gene, is a transmembrane adhesion receptor that forms heterodimers with β1 (α4β1/VLA-4) or β7 (α4β7), mediating cell-cell and cell-ECM interactions. Structurally, it consists of a large extracellular domain that binds ligands like VCAM-1 and fibronectin, a single transmembrane helix, and a short cytoplasmic tail that interacts with intracellular signaling proteins such as paxillin. Depending on the literature source, ITGA4 may also be discussed as Integrin alpha4 and CD49d.

Reported cellular context includes membrane, which can matter when signal is compared across treatments or changing cell states. Following ITGA4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.

Research Context

ITGA4 is commonly interpreted in the context of immunology, developmental biology, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.

Consider these angles when interpreting target-level changes:

• signal enrichment within membrane relative to the broader cellular background
• context differences tied to immune-cell state, activation, or lineage composition
• stage-dependent patterns during differentiation, morphogenesis, or lineage commitment
• signal-dependent shifts after ligand, inhibitor, or growth-factor perturbation

Variant Considerations

If your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ITGA4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.

Standardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ITGA4 reflect biology rather than handling. When interpreting ITGA4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.

For multi-run studies, a shared reference condition can keep ITGA4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.