Seq-Scope: Microscopic Examination of Spatial Single Cell Transcriptome in Cell and Tissue Senescence

University Of Michigan At Ann Arbor, Ann Arbor MI

Investigators

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Abstract

ABSTRACT The parent grant (UG3/UH3CA268091) aims to develop a high-resolution, cost-effective spatial transcriptomics tool for detecting and characterizing senescent cells and their microenvironment in intact tissues. Building on our initial proof-of-concept Seq-Scope prototype, which exhibited orders of magnitude improvements over existing spatial technologies at the time, we have made substantial advancements in both the experimental and computational workflows, enhancing robustness, accessibility, and precision. We expanded Seq-Scope’s imaging area by leveraging sequencing flow cells with larger capacities (e.g., Illumina NovaSeq 6000) and optimized a cost-effective Seq-Scope protocol for generating high-resolution spatial data. Additionally, we developed FICTURE, a computational algorithm that preserves Seq-Scope’s original high-resolution spatial data without requiring cell segmentation or pixel binning. These advancements have significantly impacted various SenNet programs, fostering collaborations to study cellular senescence in diverse contexts. Furthermore, FICTURE’s platform-independent framework enables its application across both sequencing- and imaging-based spatial transcriptomics technologies, broadening its utility. Recently, we achieved another major technological breakthrough by integrating Seq-Scope with tissue expansion, dramatically surpassing optical resolution limits in a new platform tentatively named Seq-Scope-eXpanded (Seq-Scope-X). In addition to its unprecedented resolution, Seq-Scope-X demonstrates enhanced compatibility with multi-omics applications, enabling the profiling of over 100 protein expression patterns in a single experiment using antibody-tagged oligos. This supplement seeks to capitalize on these unanticipated advancements to deepen our understanding of cellular and tissue senescence across various physiological contexts. Specifically, we propose to: (1) evaluate Seq-Scope-X’s tissue compatibility by applying it to diverse mouse and human tissues, (2) integrate barcode-encoded senescence markers into Seq-Scope-X’s proteome detection workflow to simultaneously profile transcriptomes, immune surface proteomes, and senescence markers, (3) examine mouse liver tissues under various physiological and pathological conditions to assess the contribution of senescence to disease progression, and (4) characterize nuclear vs. cytoplasmic transcriptomes using Seq- Scope-X to distinguish between present (cytoplasmic) and future (nuclear) transcriptomic states, shedding light on the reversibility of senescence and its role in cellular phenotype transitions over time. By refining Seq- Scope-X’s resolution, multi-omic integration, and analytical capacity, this supplement will significantly enhance our ability to characterize senescent cells and their functional impact on tissue homeostasis and disease. These advancements will not only benefit SenNet initiatives but also contribute broadly to the fields of spatial transcriptomics and cellular senescence research.