The mouse epidermis harbors two key resident immune populations—dendritic epidermal T cells (DETCs), a subset of invariant γδ T cells, and Langerhans cells (LCs), specialized tissue-resident macrophages—both of which play critical roles in immune surveillance, barrier integrity, and tissue homeostasis. While their fetal origin has been defined, the mechanisms governing their postnatal maturation remain poorly understood. Here, we present a combined immunophenotypic and single-cell transcriptomic map of DETC and LC development from late embryogenesis through adulthood in mice. We delineate distinct differentiation trajectories characterized by dynamic changes in morphology, proliferation, and transcriptional programming. Using γδ T cell deficient mice, we show that LC maturation proceeds independently of canonical γδDETCs, likely due to compensatory αβDETCs. Analysis of germfree mice and wildlings further demonstrates that the postnatal DETC and LC differentiation is independent of microbial colonization. Comparative analysis with developing human epidermis reveals partially conserved differentiation programs. Together, our findings define core principles underlying establishment of the epidermal immune niche.
D. Obwegs, Alexander Oschwald, L. Koetter et al.· Science Advances· 0 citations
Experimental validation and functional optimization remain bottlenecks in AI-based protein design. We present a scalable workflow for developing AI-designed minibinders against cancer-associated surface proteins. Screening thousands of designs using mammalian cell-surface display identifies several high-affinity PD-L1 minibinders but far fewer for CD276 (B7-H3) and VTCN1 (B7-H4), highlighting substantial target dependence. Interface predicted template modeling (ipTM) scores generated by Chai-1 with ESM embeddings correlate with binding success and capture deleterious effects of interface mutations. Fluorophore-labeled AI-minibinders enable flow-cytometric staining comparable to conventional antibodies. However, when incorporated into chimeric antigen receptors (CAR), some show poor cell-surface trafficking and limited functionality. Redesign through a genetic algorithm-based diversification strategy that preserves the binding interface while changing non-binding surfaces experimentally reveals an isoelectric point (pI) window that improves CAR expression and enhances target-selective tumor cell killing. Our findings identify biochemical optimization beyond the binding interface as a critical requirement for translating AI-minibinders into functional applications. In this work the authors present a scalable mammalian cell-display workflow to identify AI-designed minibinders against cancer surface targets. AI-guided optimization beyond the binding interface improves their expression as chimeric antigen receptors and target-selective killing.
B. Broske, B. McEnroe, S. C. Frechen et al.· Nature Communications· 0 citations
