Xue, A. G. | Search bioRxiv

bioRxiv2026

Computational design of a versatile, zero-radius proximity labeling enzyme

The ability to map protein interactomes and organelle proteomes is foundational for achieving a molecular understanding of living cells. Proximity labeling (PL) provides a powerful strategy for this, but existing enzymes and photocatalysts are limited by their spatial resolution, reliance on biotin, and/or in vivo compatibility. Here we report FlexID, an engineered promiscuous ligase that catalyzes the rapid attachment of diverse small-molecule probes to proximal endogenous proteins. Critically, FlexID operates through a zero-radius, direct-contact mechanism, offering superior spatial precision compared to existing PL tools. We engineered FlexID by combining the strengths of sequence- and structure-trained computational models to enhance its catalytic activity and structural stability. Biophysical analysis revealed that specific conformational changes in FlexID improve its ability to recognize diverse target proteins while simultaneously preventing the premature release of the reactive intermediate. We demonstrate FlexID's versatility through in vivo proximity labeling, comprehensive organelle proteome mapping, and a high-throughput, fluorescence-based screen for molecular glues. Our work shows that computational methods can be harnessed to create mechanistically distinct PL enzymes and establishes FlexID as a flexible, high-resolution tool for mapping protein interactions and proteomes in living cells.

bioengineering↗

bioRxiv2022

Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics

Mapping and molecularly annotating mammalian neural circuits is challenging due to the inability to uniquely label cells while also resolving subcellular features such as synaptic proteins or fine cellular processes. We argue that an ideal technology for connectomics would have the following characteristics: the capacity for robust distance-independent labeling, synaptic resolution, molecular interrogation, and scalable computational methods. The recent development of high-diversity cellular barcoding with RNA has provided a way to overcome the labeling limitations associated with spectral dyes, however performing all-optical circuit mapping has not been demonstrated because no method exists to image barcodes throughout cells at synaptic-resolution. Here we show ExBarSeq, an integrated method combining in situ sequencing of RNA barcodes, immunostaining, and Expansion Microscopy coupled with an end-to-end software pipeline that automatically extracts barcode identities from large imaging datasets without data processing bottlenecks. As a proof of concept, we applied ExBarSeq to thick tissue sections from mice virally infected with MAPseq viral vectors and demonstrated the extraction of 50 barcoded cells in the visual cortex as well as cell morphologies uncovered via immunostaining. The current work demonstrates high resolution multiplexing of exogenous barcodes and endogenous synaptic proteins and outlines a roadmap for molecularly annotated connectomics at a brain-wide scale.

neuroscience↗