Back

Liquid-Liquid Phase Separation of the m6A RNA ALKBH9B Demethylase: An IDR-dependent Mechanism driving the Alfalfa Mosaic Virus Infection

Gonzalez-Silva, V.; Leastro, M. O.; Navarro, J. A.; SANCHEZ-NAVARRO, J. A.; APARICIO, F.; PALLAS, V.

2026-07-30 plant biology
10.64898/2026.07.30.741775 bioRxiv
Show abstract

Biomolecular condensates play crucial role in plant-virus interactions. The plant m6A demethylase ALKBH9B acts as a proviral factor for Alfalfa mosaic virus (AMV), yet the biophysical mechanisms underlying its function remain elusive. Here, we investigate the liquid-liquid phase separation (LLPS) properties of ALKBH9B and their requirements for viral infection. Using in vitro and in vivo assays (Nicotiana benthamiana), we demonstrate that ALKBH9B assembles into highly dynamic, liquid-like cytoplasmic condensates driven primarily by weak hydrophobic interactions. Deletion and mutagenesis analysis identified a C-terminal intrinsically disordered region (IDR3), specifically its arginine-glycine (RG) motifs, as the essential molecular driver of LLPS. Importantly, this domain exhibits dual functionality, mediating both phase separation and direct binding to AMV RNA, which regulates condensate assembly and size. Disruption of the RG motifs completely abolishes ALKBH9B condensation and reduces its proviral capacity, compromising viral accumulation. Collectively, our findings reveal that the spatial compartmentalization of ALKBH9B into dynamic liquid hubs is functionally indispensable for AMV infection. This establishes LLPS as a critical regulatory checkpoint in viral pathogenesis, highlighting how plant viruses exploit the biophysical properties of host epitranscriptomic enzymes to establish specialized, protective microenvironments. HighlightsOur study establishes a direct mechanistic link between the biophysical properties of a plant m6A demethylase and viral pathogenesis, demonstrating that ALKBH9B functions as a key host factor by harnessing LLPS to regulate virus-host interactions.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.