Phospho-Connexin 43 (Ser368) Antibody

About the Target

GJA1 is a target of interest in many antibody-based workflows. Connexin 43 (Cx43) is a key gap junction protein essential for intercellular communication, allowing small molecules and signaling messengers to pass between cells. It is abundantly expressed in the heart and brain, particularly in ventricular and astrocytic tissues. Phosphorylation of Cx43 at its C-terminal tail, including sites such as Ser368 by protein kinase C (PKC), regulates the permeability of gap junctions and hemichannels. Depending on the literature source, GJA1 may also be discussed as Phospho-Connexin 43 (Ser368) and Connexin 43 / GJA1 (phospho S368).

Reported cellular context includes cell junction, cell membrane, endoplasmic reticulum, and gap junction, which can matter when signal is compared across treatments or changing cell states. Following GJA1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.

Research Context

GJA1 is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and endoplasmic reticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.

Consider these angles when interpreting target-level changes:

• apparent redistribution between cell junction, cell membrane, and endoplasmic reticulum across matched conditions
• changes linked to vascular, contractile, or hemodynamic cell-state cues
• signal-dependent shifts after ligand, inhibitor, or growth-factor perturbation
• differences between total target abundance and site-specific regulation when modified forms are compared

Variant Considerations

If your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for GJA1. 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 GJA1 reflect biology rather than handling. When interpreting GJA1, 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 GJA1 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.