Project description:Immunotherapy efficacy in solid tumors varies greatly, influenced by the tumor microenvironment (TME) and the dynamic tumor-immune interactions within it. Decoding these interactions in situ with minimal interference to native tissue architecture and delicate immune responses is critical for understanding tumor progression and optimizing therapeutic strategies. Here, we introduce CAT-Tissue, a novel deep-red photocatalytic proximity labeling method that enables ultrafast, high-resolution profiling of tumor-immune interactions in primary tissues. By leveraging nanobody-Chlorin e6 as the photocatalyst and biotin-aniline as the probe, CAT-Tissue enabled the rapid and comprehensive detection of various tumor-immune interactions in both coculture systems and primary tumor sections. Coupled with bulk RNA-sequencing, CAT-Tissue revealed distinct gene expression patterns between tumor-neighboring and tumor-distal lymphocytes, highlighting the recognition and immune responses of tumor-neighboring CD8+ T cells, which exhibited activated, effector, and exhausted phenotypes. By leveraging a deep-red photocatalytic proximity cell labeling strategy with excellent tissue penetration and biocompatibility, CAT-Tissue offers a non-genetically encoded platform with high sensitivity and spatiotemporal controllability for rapid profiling tumor-immune interactions within complex tissue environments in situ, which may advance our understanding of tumor immunology and guide the development of more effective immunotherapies.
Project description:In situ profiling of subcellular proteomic networks in primary and living systems, such as primary cells from native tissues or clinic samples, is crucial for the understanding of life processes and diseases, yet challenging for the current proximity labeling methods (e.g., BioID, APEX) due to their necessity of genetic engineering. Here we report CAT-S, a state-of-the-art bioorthogonal photocatalytic chemistry-enabled proximity labeling method, that expands proximity labeling to a wide range of primary living samples for in situ profiling of subcellular proteomes. Powered by the newly introduced thioQM labeling warhead and targeted bioorthogonal photocatalytic decaging chemistry, CAT-S enables labeling of mitochondrial proteins in living cells with high efficiency and specificity (up to 87%). We applied CAT-S to diverse cell cultures, mouse tissues as well as primary T cells from human blood, portraying the native-state mitochondrial proteomic characteristics, and unveiled a set of hidden mitochondrial proteins in human proteome. Furthermore, CAT-S allows quantitative analysis of the in situ proteomic perturbations on dysfunctional tissue samples, exampled by diabetic mouse kidneys, and revealed the alterations of lipid metabolism machinery that drive the disease progression. Given the advantages of non-genetic operation, generality, efficiency as well as spatiotemporal resolution, CAT-S may open new avenues as a proximity labeling strategy for in situ investigation of subcellular proteomic landscape of primary living samples that are otherwise inaccessible.
Project description:In eukaryotic cells, the precise spatial localization of RNAs and proteins is essential for proper cellular function. Genetically encoded photocatalytic proximity labeling techniques have expanded our ability to map subcellular proteomes and transcriptomes, but their temporal resolution remains limited. Here, we introduce Lantern, an engineered flavoprotein optimized via directed evolution, which enables sub‑minute, spatially resolved labeling of cellular biomolecules. Lantern is targetable to diverse subcellular compartments, including the endoplasmic reticulum, mitochondria, and stress granules (SGs), to map local transcriptomes (CAP-seq) and proteomes (CAP-MS). Using Lantern, we observed that m6A‑enriched RNAs are recruited to SGs within five minutes of stress induction, while ER‑proximal RNAs associate with the SG scaffold protein G3BP1 during early SG assembly. Additionally, Lantern was adapted for cell-surface tagging (CAP-CELL), enabling spatially resolved cell typing and the analysis of cell-cell interactions. Collectively, this study establishes Lantern as a powerful tool that offers unprecedented temporal resolution for investigating the dynamic organization of subcellular molecular networks.
Project description:Deep-Red and Ultrafast Photocatalytic Proximity Labeling Empowered in situ Dissection of Tumor-Immune Interactions in Primary Tissues
Project description:The growing appreciation of immune cell-cell interactions within disease environments has led to significant efforts to develop highly effective protein-, and cell-based immunotherapies. However, characterizing these complex cell-cell interactions in high resolution remains challenging. Thus, technologies that leverage therapeutic-based modalities for profiling intercellular environments can provide unique advantages towards understanding these cellular interactions at molecular-level detail. To address this, we introduce photocatalytic cell tagging (PhoTag), a platform for profiling cell-cell interactions that utilizes a single domain antibody (VHH) conjugated to a photoactivatable flavin-based cofactor. Upon irradiation with visible light, the tethered flavin photocatalyst generates phenoxy radical tags for targeted labeling within cell-cell contact environments. Using anti-PD-1 or anti-PD-L1 VHH flavin conjugates, we demonstrate that PhoTag achieves highly selective synaptic labeling in antigen presenting cell-T cell co-culture systems. By combining the high resolution transcellular biotinylation capability of PhoTag with multi-omics single cell sequencing, we interrogated transient interactions between Peripheral blood mononuclear cell (PBMC) populations and Raji PD-L1 B cells and discovered that specific T cell subtypes can transiently interact more efficiently than others. We envision that the spatio-temporal and modular nature of PhoTag will enable its broad utilization for detailed profiling of intercellular interactions across different biological systems.
Project description:Directed evolution of a genetically encoded photocatalyst for temporally resolved proximity labeling of subcellular RNAs and proteins
Project description:he spatiotemporal progression of amyloid pathology in Alzheimer's disease (AD) follows a characteristic pattern, spreading from the cortex to the hippocampus brain regions. However, analytical methods for comparative profiling of amyloid plaque composition between these two regions are limited. Herein, we developed a small molecule guided method to selectively label, enrich, profile and compare amyloid interactome in cortical and hippocampal regions of AD brain tissue. We embarked on rational design of probes to transform Congo Red derivatives from amyloid chromophore to singlet fluorescent sensor, and finally to triplet photocatalytic labeling probe. While retaining the amyloid binding selectivity, P5 outperformed other probes in photocatalytic labeling of recombinant amyloid proteins and amyloid deposits from AD mouse brain tissues. We applied P5 to selectively labeling and enrichment of amyloid plaques in hippocampus and cortex, respectively. The robustness of our methodology was confirmed by the consistent identification of established AD biomarkers (e.g. APP, ApoE) in both regions. Subsequent comparative proteomics not only demonstrated the critical involvement of the mitophagy-lysosome axis in AD pathogenesis, but also uncovered a previously unrecognized region-specific functional divergence. Proteomic profiles distinguished that AD’s cortex primarily involves upstream mitophagy, whereas AD’s hippocampus actively triggers downstream lysosomal degradation. Overall, we report a small-molecule-based photocatalytic proteomic profiling method to resolve amyloid deposits and elucidate their region-specific interactome heterogeneity.