Perturb-FISH uses imaging spatial transcriptomics and multiplexed error robust fluorescence in situ hybridization to give scientists a new window into intercellular interactions.
Scientists use high-throughput genetic screens to look at systemic effects from individual gene manipulation. However, these screens do not retain spatial information. Samouil Farhi, a chemical biologist from the Broad Institute, looks to overcome this limitation. In a recent study published in Cell, Farhi presented perturbation-based fluorescence in situ hybridization (Perturb-FISH), a technique that spatially detects inserted CRISPR guide RNAs (gRNAs) and allows imaging-based spatial transcriptomic measurements. Farhi and his research team then used Perturb-FISH to examine how gene modulation changes cellular behavior in autism spectrum disorder (ASD) and cancer models.1
The CRISPR Revolution
Pooled high-throughput CRISPR screens have become standard practice for loss-of-function genetic screening.1,2 Furthermore, pooled screening combined with single-cell RNA sequencing (scRNA-seq) can examine genome-transcriptome relationships.1 However, because these screens separate single cells into individual droplets, they cannot preserve spatial information.
Researchers therefore have sought techniques that combine in situ gRNA sequencing with imaging-based profiling. In 2022, scientists from the Icahn School of Medicine at Mount Sinai created Perturb-map, a technique linking CRISPR perturbation, transcriptomics, and spatial information.3 However, because it uses barcodes to identify and track gRNAs, it is relatively limited in throughput and scaling capacity.1
Perturb-FISH aims to address both challenges. Because this technique harnesses imaging spatial transcriptomics (iST), it offers high resolution and scalability, as well as relatively low costs. To combat background autofluorescence, Farhi and his team turned to a combination of multiplexed error robust fluorescence in situ hybridization (MERFISH) and local gRNA amplification to generate distinct signals.
Testing Perturb-FISH
Farhi’s research team then validated Perturb-FISH by using it to evaluate a known response: how THP1-derived macrophages react to lipopolysaccharide (LPS) stimulation. Their data was not only consistent across different experimental runs, but with previously generated Perturb-seq findings. These consistencies applied whether looking at individual genes or the overall global structure of perturbation effects. Finally, the researchers ran a power analysis and found that 20-50 cells per perturbation target was the minimum required to obtain reliable effects from Perturb-FISH data.
Applying Perturb-FISH
In this study, Farhi and his colleagues wanted to accomplish two things with Perturb-FISH. First, they sought to match perturbation data with functional imaging. To do this, they used the technique to investigate how ASD risk genes regulate gene expression and calcium activity in astrocytes. Farhi’s team designed a Perturb-FISH screen measuring 485 genes: 127 ASD risk genes to be directly knocked down and 358 genes differentially expressed between ASD and control patients in astrocytes. They found 566 specific effects after gene perturbation: 27 perturbations were linked with more than three significant effects, while the expression levels of 142 genes were significantly altered by at least three perturbations. The researchers noted that many cholesterol-associated genes were affected by ASD risk gene perturbation, which aligns with recent studies reporting altered cholesterol biosynthesis gene expression in ASD and schizophrenia.4
Second, the researchers wanted to see if they could use Perturb-FISH to study complex tissue environments. Therefore, they looked at NF-κB pathways, which play significant roles in tumor development. Using a mouse xenograft model, Farhi’s team perturbed 35 target genes in melanoma cells and examined the expression of 500 immune response-related genes after two weeks of tumor growth. Here, 32 perturbations significantly affected the expression of at least three genes, while the expression of 164 genes were affected by at least one perturbation. In particular, the team could examine cell-cell interactions using Perturb-FISH, noting that knocking out three specific genes in tumor cells downregulated activation markers in surrounding T cells. Moreover, T cells located beside tumor cells overexpressed genes associated with poor prognosis.
From a Cell to a System
With Perturb-FISH, Farhi and his team have created an important tool that lets scientists simultaneously investigate the intracellular and intercellular networks that regulate health and disease. This sheds light on the underlying causes for genetic disorders such as ASD and shows how gene-level alterations alter cellular function and affect the progression of chronic diseases such as cancer.
