Comprehensive mutagenesis maps the effect of all single-codon mutations in the AAV2 rep gene on AAV production.

Recombinant adeno-associated viruses (rAAVs) are the predominant gene therapy vector. Several rAAV vectored therapies have achieved regulatory approval, but production of sufficient rAAV quantities remains difficult. The AAV Rep proteins, which are essential for genome replication and packaging, represent a promising engineering target for improvement of rAAV production but remain underexplored. To gain a comprehensive understanding of the Rep proteins and their mutational landscape, we assayed the effects of all 39,297 possible single-codon mutations to the AAV2 rep gene on AAV2 production. Most beneficial variants are not observed in nature, indicating that improved production may require synthetic mutations. Additionally, the effects of AAV2 rep mutations were largely consistent across capsid serotypes, suggesting that production benefits are capsid independent. Our results provide a detailed sequence-to-function map that enhances our understanding of Rep protein function and lays the groundwork for Rep engineering and enhancement of large-scale gene therapy production.

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics.

Large-scale functional LIPA variant characterization to improve birth prevalence estimates of lysosomal acid lipase deficiency.

Lysosomal acid lipase (LAL) deficiency is an autosomal recessive disorder caused by LIPA gene mutations that disrupt LAL activity. We performed in vitro functional testing of 149 LIPA variants to increase the understanding of the variant effects on LAL deficiency and to improve disease prevalence estimates. Chosen variants had been reported in literature or population databases. Functional testing was done by plasmid transient transfection and LAL activity assessment. We assembled a set of 165 published LAL deficient patient genotypes to evaluate this assay's effectiveness to recapitulate genotype/phenotype relationships. Rapidly progressive LAL deficient patients showed negligible enzymatic activity (<1%), whereas patients with childhood/adult LAL deficiency typically have 1-7% average activity. We benchmarked six in silico variant effect prediction algorithms with these functional data. PolyPhen-2 was shown to have a superior area under the receiver operating curve performance. We used functional data along with Genome Aggregation Database (gnomAD) allele frequencies to estimate LAL deficiency birth prevalence, yielding a range of 3.45-5.97 cases per million births in European-ancestry populations. The low estimate only considers functionally assayed variants in gnomAD. The high estimate computes allele frequencies for variants absent in gnomAD, and uses in silico scores for unassayed variants. Prevalence estimates are lower than previously published, underscoring LAL deficiency's rarity.

3-D intestinal scaffolds for evaluating the therapeutic potential of probiotics.

Biomimetic in vitro intestinal models are becoming useful tools for studying host-microbial interactions. In the past, these models have typically been limited to simple cultures on 2-D scaffolds or Transwell inserts, but it is widely understood that epithelial cells cultured in 3-D environments exhibit different phenotypes that are more reflective of native tissue, and that different microbial species will preferentially adhere to select locations along the intestinal villi. We used a synthetic 3-D tissue scaffold with villous features that could support the coculture of epithelial cell types with select bacterial populations. Our end goal was to establish microbial niches along the crypt-villus axis in order to mimic the natural microenvironment of the small intestine, which could potentially provide new insights into microbe-induced intestinal disorders, as well as enabling targeted probiotic therapies. We recreated the surface topography of the small intestine by fabricating a biodegradable and biocompatible villous scaffold using poly lactic-glycolic acid to enable the culture of Caco-2 with differentiation along the crypt-villus axis in a similar manner to native intestines. This was then used as a platform to mimic the adhesion and invasion profiles of both Salmonella and Pseudomonas, and assess the therapeutic potential of Lactobacillus and commensal Escherichia coli in a 3-D setting. We found that, in a 3-D environment, Lactobacillus is more successful at displacing pathogens, whereas Nissle is more effective at inhibiting pathogen adhesion.

Synthetic small intestinal scaffolds for improved studies of intestinal differentiation.

In vitro intestinal models can provide new insights into small intestinal function, including cellular growth and proliferation mechanisms, drug absorption capabilities, and host-microbial interactions. These models are typically formed with cells cultured on 2D scaffolds or transwell inserts, but it is widely understood that epithelial cells cultured in 3D environments exhibit different phenotypes that are more reflective of native tissue. Our focus was to develop a porous, synthetic 3D tissue scaffold with villous features that could support the culture of epithelial cell types to mimic the natural microenvironment of the small intestine. We demonstrated that our scaffold could support the co-culture of Caco-2 cells with a mucus-producing cell line, HT29-MTX, as well as small intestinal crypts from mice for extended periods. By recreating the surface topography with accurately sized intestinal villi, we enable cellular differentiation along the villous axis in a similar manner to native intestines. In addition, we show that the biochemical microenvironments of the intestine can be further simulated via a combination of apical and basolateral feeding of intestinal cell types cultured on the 3D models.