Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Abstract

Spatially resolved transcriptomics (SRT) has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of unbiased SRT methods targeting the polyA tail of mRNA, relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available SRT assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), an SRT workflow designed to improve mRNA recovery from fresh frozen (FF) specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we demonstrate the RRST protocol on tissue sections collected from 5 challenging tissue types, including: human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyzed 52 tissue sections and our results demonstrate that RRST is a versatile, powerful, and reproducible protocol for FF specimens of different qualities and origins.

Spatial Multimodal Analysis of Transcriptomes and Metabolomes in Tissues

“…The human post-mortem sample was processed according to the RRST protocol 18 . The slide was taken out of the -80°C freezer and placed on a thermocycler, pre-heated to 37°C, for 1 minute, followed by immediate fixation in 4% methanol-free formaldehyde (ThermoFisher, Waltham, MA, USA; Catalog number: 28906) solution for 10 minutes, RT.…”

“…2Ci ). To address and overcome RNA degradation in post-mortem material, we applied a recent protocol specifically developed for gene expression measurements from fresh frozen tissue samples with low/moderate RNA quality 18 . The spatial MSI distribution of DA and 3-MT ( Fig.…”