How many different applications of Perturb-Seq are you aware of?

How many different applications of Perturb-Seq are you aware of?

CRISPR library can screen enrich target cells through specific cell phenotypes (such as cell growth, migration, drug resistance, and expression of antigens or antibodies), and combined with NGS (Next-Generation Sequencing) to identify potential targets related to the phenotype. However, for studies that lack obvious phenotypic changes or where cells are difficult to screen based on phenotypes, it is challenging to identify potential targets solely through CRISPR library screening. Single-cell sequencing technology enables transcriptome sequencing of individual cells, allowing for the detection of molecular-level differences between cells. By combining CRISPR libraries with Perturb-Seq, it is possible to simultaneously obtain transcriptome data from multiple cells with different mutation types, enabling molecular-level detection of differences among cells.

Overview:

Single-cell CRISPR library technology was initially developed by the Dixit team at the Broad Institute (named Perturb-Seq). Perturb-Seq combines CRISPR libraries with single-cell sequencing to simultaneously detect changes in gene transcripts caused by CRISPR-mediated gene knockout or activation in multiple cells. Compared to traditional single-cell sequencing techniques, the challenge of Perturb-Seq lies in matching sgRNA information to single-cell sequencing data. Since sgRNA scaffolds lack a polyA sequence, conventional single-cell library preparation methods cannot directly obtain sgRNA information from individual cells. To address this issue, Dixit et al. added a barcode sequence in the lentiviral vector corresponding to the sgRNA sequence, which allows the sgRNA information to be matched with cellular sequencing results after identifying the barcode sequence through single-cell sequencing[1]. (Figure 1)

Figure 1 The principle of Perturb-Seq sequencing[1]

Subsequently, different research teams further optimized this method, developing approaches like CRISP-Seq, CROP-Seq, and currently the most commonly used Direct Capture Perturb-Seq. this method provides significant convenience for related research, as it requires no modification of the CRISPR library scaffold for Perturb-Seq.

Figure 2 Principle of Direct Capture perturb-seq Sequencing[4]

1. Screening Targets Through Transcriptome Changes:

As mentioned above, perturb-seq can overcome the dependence on phenotypes in CRISPR library screening. Even in the absence of identifiable phenotypic traits (such as in psychiatric diseases), this technology can be employed to seek potential targets.

For instance, 22q11.2 deletion syndrome is a hereditary disease caused by partial chromosomal deletion, involving 37 genes, 29 of which are expressed in the prefrontal cortex. Clinically, patients usually exhibit symptoms of schizophrenia or autism. To further study the target genes causing the disease, researchers constructed a CRISPR library targeting these 29 genes, sorted neural cells via flow cytometry, and analyzed transcriptome changes between different cells using single-cell sequencing(Figure 3). They identified significant changes in transcripts in neural cells with knockouts for genes such as Dgcr8, Dgcr14, Gnb1l, and Ufd1l. By comparing the differences in transcriptomes between these knockout neural cells and those in 22q11.2 deletion mouse models, they further confirmed the notable correlation between the deletions of the Dgcr8 and Gnb1l genes and the progression of the disease[5]. (Figure 4)

Figure 3 Roadmap of perturb-seq for genes related to 22q11.2 chromosome deletion syndrome[5]

Figure 4 Changes in expression profiles of different gene knockout cells[5]

2. Analyzing Functions of Different Genes/Subunits in Complexes:

The mammalian SWI/SNF complex (BAF) is composed of 10-15 subunits regulated by 29 genes, playing a crucial role in DNA accessibility and gene expression. However, the contribution of different subunits within this complex to the regulation of gene expression remains unclear. Cigall et al. designed a CRISPR knockout library targeting 28 of these genes, transfected MOLM-13 cells with lentiviruses, and combined flow sorting with single-cell sequencing for analysis. They revealed the impact of different subunits of the complex on DNA accessibility and gene expression. Given the existence of three different forms of the BAF complex (cBAF, PBAF, and ncBAF), the authors analyzed the gene expression profiles corresponding to these three forms and found that PBAF had the least impact on gene expression, while cBAF had the most substantial regulatory impact on development and differentiation-related genes[6]. (Figure 5 and Figure 6)

Figure 5 Roadmap of Perturb-seq for SWI/SNF complex[6]

Figure 6 Changes in expression profiles of different genes and subtypes of complexes[6]

3. Comparing sgRNA Differences in Different Cells to Identify Genes Related to Differentiation

CD8+ cytotoxic T cells (CTL) are crucial immune cells in anti-tumor responses, among which Tex cells form a major population and can directly kill tumor cells. Although Tex cells have limited proliferation capacity, their precursor cells, Tpex, can differentiate into numerous Tex cells. However, the gene regulatory network governing the differentiation of Tpex to Tex cells is not fully understood. To explore this, the Chi Hongbo team constructed a CRISPR knockout library targeting 180 transcription factors related to the cell cycle in CTL cells. They transferred the library into melanoma mouse models and, after one week, sorted the remaining cells through flow cytometry followed by single-cell sequencing. By clustering the cells based on differentiation-related genes and performing pseudotime analysis, the team categorized the cells into four progressively differentiated populations: Tpex1, Tpex2, Tex1, and Tex2. By comparing the sgRNA enrichment information across these distinct cell populations, they found that the Ikzf1 gene promotes Tpex1 cells' exit from a resting state, facilitating differentiation to Tpex2 cells. Meanwhile, the Ets1 gene negatively regulates the differentiation of Tpex2 to Tex1, inhibiting Tpex differentiation, while Tex1 differentiation to Tex2 relies on the activation of the Rbpj gene[7]. In summary, the team utilized single-cell CRISPR library technology to identify and establish critical regulatory pathways during the differentiation of Tpex cells into Tex cells. (Figures 7 and 8)

Figure 7 Single-cell CRISPR library screening for cell differentiation-related transcription factors[7]

Figure 8 Pseudotime analysis and sgRNA enrichment in each cell population[7]

Perturb-Seq is a method that uses CRISPR libraries to simultaneously introduce different mutations into multiple cells, and combining single-cell sequencing to obtain transcriptome data of these cells with different mutations for analysis. Compared to traditional single-cell sequencing technology, single-cell CRISPR library technology can simultaneously gather transcriptomic information for various gene-knockout cells. Combined with downstream single-cell data analysis methods, it not only enables cell clustering and pseudotime analysis but also enables categorizing cells based on sgRNA information or compare sgRNA differences among various cell populations to identify potential targets[6-7].

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Reference:

[1]Dixit A, Parnas O, Li B, Chen J, Fulco CP, Jerby-Arnon L, Marjanovic ND, Dionne D, Burks T, Raychowdhury R, Adamson B, Norman TM, Lander ES, Weissman JS, Friedman N, Regev A. Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens. Cell. 2016 Dec 15;167(7):1853-1866.e17.
[2]Jaitin DA, Weiner A, Yofe I, Lara-Astiaso D, Keren-Shaul H, David E, Salame TM, Tanay A, van Oudenaarden A, Amit I. Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq. Cell. 2016 Dec 15;167(7):1883-1896.e15.
[3]Datlinger P, Rendeiro AF, Schmidl C, Krausgruber T, Traxler P, Klughammer J, Schuster LC, Kuchler A, Alpar D, Bock C. Pooled CRISPR screening with single-cell transcriptome readout. Nat Methods. 2017 Mar;14(3):297-301.
[4]Replogle JM, Norman TM, Xu A, Hussmann JA, Chen J, Cogan JZ, Meer EJ, Terry JM, Riordan DP, Srinivas N, Fiddes IT, Arthur JG, Alvarado LJ, Pfeiffer KA, Mikkelsen TS, Weissman JS, Adamson B. Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing. Nat Biotechnol. 2020 Aug;38(8):954-961.
[5]Santinha AJ, Klingler E, Kuhn M, Farouni R, Lagler S, Kalamakis G, Lischetti U, Jabaudon D, Platt RJ. Transcriptional linkage analysis with in vivo AAV-Perturb-seq. Nature. 2023 Oct;622(7982):367-375.
[6]Otto JE, Ursu O, Wu AP, Winter EB, Cuoco MS, Ma S, Qian K, Michel BC, Buenrostro JD, Berger B, Regev A, Kadoch C. Structural and functional properties of mSWI/SNF chromatin remodeling complexes revealed through single-cell perturbation screens. Mol Cell. 2023 Apr 20;83(8):1350-1367.e7.
[7]Zhou P, Shi H, Huang H, Sun X, Yuan S, Chapman NM, Connelly JP, Lim SA, Saravia J, Kc A, Pruett-Miller SM, Chi H. Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer. Nature. 2023 Dec;624(7990):154-163.