A Novel Sparse Cellular Labeling System with Tunable Gradients and Long-Term Stability

The dense packing of cells within tissues poses challenges for studying cellular properties. Sparse labeling, genetically targeting a small subset of densely distributed cells, provides a powerful approach to investigate cellular morphology, connectivity, dynamics, and functions, especially in neuroscience. However, current sparse labeling methods are generally restricted to fixed labeling densities and often exhibit a decline in sparsity over time. In this study, by maximizing the utility of commonly used recombinases and the relational recognition sites, we constructed a versatile sparse labeling system, termed Tri-M (Multi-recombinase, Multi-recognition site, and Multi-nested), built upon competitive recombination. The Tri-M system, which integrates transgenic mice with viral injection, enables tunable and graded sparse labeling of specific cell types within specific brain regions with long-term stability. This system significantly enhances the ability to track, analyze, and manipulate cells within tissues characterized by dense cellular packing, from single cells to populations.