bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.07.10.737643

AAV VP1 unique region (VP1u) determines GPR108 dependence for AAV transduction of human airway epithelium and its rescue by Doxorubicin

Abstract

rAAV2.5T was identified through directed evolution of an AAV capsid library in polarized human airway epithelium (HAE) cultured at an air-liquid interface (ALI). The capsid gene of rAAV2.5T is a chimera of the N-terminal unique region of AAV2 VP1 (VP1u) and the VP2 and VP3 regions of AAV5 with a single A581T substitution at the variable region (VR) VIII of the capsids. GPR108, a G protein-coupled receptor, is known as an essential host factor for the transduction of rAAV2 but not of rAAV5. Both AAV2 and AAV5 VP1u colocalized well with GPR108 and, to a lesser extent, with the trans-Golgi network (TGN). GPR108 knockout (KO) abolished rAAV2.5T transduction in both HeLa cells and HAE-ALI cultures. Remarkably, short-term treatment with doxorubicin (DOX) at 2 {micro}M completely restored transduction, indicating that DOX can compensate for the loss of GPR108 function. DOX enhanced rAAV2.5T transduction by 50-100-fold in wild-type HAE-ALI cultures and by over 300-fold in the GPR108-deficient cultures. Mechanistic studies demonstrated that this enhancement resulted from altered intracellular trafficking that promoted efficient vector nuclear import, rather than increased vector internalization, proteasome inhibition, or activation of the DNA damage response. Importantly, we identified that the N-terminal 15 amino acids of AAV2 VP1u as the primary determinant of rAAV2.5T dependence on GPR108 for transduction. Collectively, these findings demonstrate that productive transduction of rAAV2.5T in polarized HAE cultures depends on GPR108-mediated intracellular trafficking that limits efficient nuclear entry, and that DOX can relieve this constraint by promoting efficient vector import. SignificanceAAV2.5T is an airway-tropic vector with considerable promise for pulmonary gene therapy. We found that host factor GPR108 is required for rAAV2.5T trafficking from the TGN to the nucleus and that this step constitutes a major bottleneck to productive transduction in polarized HAE. In contrast, KIAA0319L (AAVR) plays a key role in AAV intracellular trafficking from the endosome to the TGN but not in internalization into polarized HAE during apical transduction. Transient treatment with low-dose doxorubicin (DOX, 2 {micro}M) enhanced rAAV2.5T transduction in HAE by 50-100-fold through a significant increase in vector nuclear import. Notably, DOX can overcome the transduction deficit caused by GPR108 deficiency, but not that caused by AAVR deficiency. Mechanistically, the N-terminal 15 amino acids of the VP1u confer GPR108 dependence during rAAV2.5T apical transduction of polarized HAE. DOX bypasses this requirement by promoting efficient nuclear import without affecting vector internalization, inhibiting proteasomes, or inducing DNA damage response.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hao, S., Habib, A., Zhang, X., Ning, K., Park, S. Y., Mcfarlin, S., Kuz, C. A., Richart, D., Cheng, F., Yan, Z., Qiu, J.. 2026-07-10. AAV VP1 unique region (VP1u) determines GPR108 dependence for AAV transduction of human airway epithelium and its rescue by Doxorubicin. https://doi.org/10.64898/2026.07.10.737643

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗