Premed · Premed · Cell Biology
Lecture 27: Current Methods: CRISPR, Single-Cell Techniques
Cell Biology
Learning Objectives
By the end of this lecture, students will be able to:
- Explain the mechanism of CRISPR-Cas9 genome editing and its applications in cell biology
- Describe advanced CRISPR tools (base editing, prime editing, CRISPRi/a, screens)
- Explain the principles and workflow of single-cell RNA sequencing (scRNA-seq)
- Describe how single-cell techniques reveal cellular heterogeneity and cell state transitions
- Discuss the integration of CRISPR and single-cell approaches in modern cell biology research
Lecture Content
I. CRISPR-Cas9: Mechanism and Components
Origin: bacterial adaptive immune system against bacteriophages. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats): array of viral-derived spacer sequences in the bacterial genome. Cas9: RNA-guided endonuclease from Streptococcus pyogenes (SpCas9) Components for genome editing: Cas9 protein: endonuclease with two nuclease domains (RuvC and HNH) Guide RNA (gRNA): ~20 nt sequence complementary to the genomic target + scaffold sequence that binds Cas9. Single guide RNA (sgRNA): engineered fusion of crRNA and tracrRNA. PAM (protospacer adjacent motif): short sequence (5'-NGG-3' for SpCas9) that must be adjacent to the target site on the DNA. Cas9 will not cut without PAM recognition — provides target specificity and prevents self-cleavage in bacteria. Mechanism: Cas9-sgRNA complex scans the genome for PAM sequences. Upon PAM recognition, Cas9 unwinds DNA and the sgRNA base-pairs with the target strand. If there is full complementarity (~20 bp), both nuclease domains cleave the DNA -> double-strand break (DSB). The cell repairs the DSB by one of two pathways: Non-homologous end joining (NHEJ): error-prone; introduces insertions/deletions (indels) -> gene knockout. Homology-directed repair (HDR): if a donor DNA template is provided, precise sequence changes can be introduced (knockin, point mutations, tag insertion) HDR is less efficient; mainly active in S/G2 phase (not in post-mitotic cells).
II. Advanced CRISPR Tools
CRISPRi (interference): catalytically dead Cas9 (dCas9) fused to a transcriptional repressor (KRAB) Targeted to a promoter -> blocks transcription without altering DNA sequence -> reversible knockdown. CRISPRa (activation): dCas9 fused to transcriptional activators (VP64, p65, Rta) Targeted to a promoter -> upregulates gene expression. Base editing: precise single-nucleotide changes without DSBs. Cytosine base editor (CBE): dCas9/nickase + cytidine deaminase -> C-to-T (G-to-A) conversion. Adenine base editor (ABE): dCas9/nickase + evolved adenosine deaminase -> A-to-G (T-to-C) conversion. No DSB required; no donor template needed; works in non-dividing cells. Limited to transition mutations within a ~5 bp editing window. Prime editing: "search and replace" editing. Prime editor: Cas9 nickase fused to reverse transcriptase. pegRNA (prime editing guide RNA): contains the target sequence + a template for the desired edit. Mechanism: Cas9 nickase cuts one strand; reverse transcriptase copies the edit template into the genome. Can install any point mutation, small insertions, and small deletions without DSBs or donor DNA. CRISPR screens: genome-wide functional genomics. Library of sgRNAs (targeting every gene) delivered to cells (one sgRNA per cell via lentivirus) Apply a selective pressure (e.g., drug treatment, growth competition) Sequence sgRNAs in surviving/selected cells -> identify genes whose loss confers resistance or sensitivity. Perturb-seq / CROP-seq: combine CRISPR perturbation with single-cell RNA-seq readout -> link genotype to phenotype at single-cell resolution.
<image>CRISPR-Cas9 mechanism and advanced tools. Panel A: CRISPR-Cas9 gene editing — Cas9 protein (blue) bound to sgRNA (orange), recognizing the PAM (red, NGG) on the target DNA. The sgRNA base-pairs with the 20 nt target sequence. Cas9 RuvC and HNH domains each cut one strand, creating a DSB. Two repair outcomes shown: NHEJ (indels, gene disruption) and HDR (precise editing using a donor template). Panel B: Base editing — cytosine base editor (CBE) with nickase Cas9 fused to cytidine deaminase converting C to U (read as T) without a DSB; adenine base editor (ABE) converting A to inosine (read as G). Panel C: Prime editing — prime editor (nickase Cas9 + reverse transcriptase) guided by pegRNA; nicks one strand, reverse transcriptase copies the edit template into the nicked strand, and cellular repair incorporates the edit into both strands. All three types of edits (substitutions, insertions, deletions) shown as possible outcomes.</image>
III. Single-Cell RNA Sequencing (scRNA-seq)
Rationale: bulk RNA-seq averages gene expression across millions of cells -> masks cellular heterogeneity. Individual cells within a tissue can have vastly different transcriptomes; scRNA-seq profiles the transcriptome of individual cells. General workflow: Cell isolation: tissue dissociation into single-cell suspension. Cell capture: microfluidics (10x Genomics Chromium), droplet-based, plate-based (SMART-seq), or combinatorial indexing (sci-RNA-seq) Barcoding: each cell's mRNAs are tagged with a unique cell barcode + unique molecular identifier (UMI) within a droplet or well. Reverse transcription and amplification: mRNA -> cDNA -> amplified library. Sequencing: high-throughput next-generation sequencing. Computational analysis: demultiplexing by cell barcode; UMI counting for quantification; quality filtering. 10x Genomics Chromium (most widely used platform): Cells partitioned into nanoliter droplets, each containing a gel bead with unique barcoded primers. Captures 1,000-10,000+ cells per run. Detects ~2,000-5,000 genes per cell (3' end counting) Key computational analysis steps: Dimensionality reduction: PCA, then UMAP or t-SNE for visualization. Clustering: cells grouped by transcriptomic similarity (Louvain/Leiden algorithms) Cell type annotation: marker genes identify clusters as known cell types. Differential expression: identify genes enriched in each cluster. Trajectory analysis / pseudotime: order cells along a differentiation trajectory (Monocle, RNA velocity) RNA velocity: ratio of unspliced to spliced mRNA predicts future transcriptional state.
IV. Applications of Single-Cell Technologies
Cell atlas projects: comprehensive catalogs of all cell types in tissues/organisms. Human Cell Atlas: international effort to map every cell type in the human body. Tabula Muris, Tabula Sapiens: mouse and human cell atlases. Developmental biology: tracing cell fate decisions during embryogenesis at single-cell resolution. Lineage reconstruction from scRNA-seq combined with CRISPR-based barcoding (e.g., CARLIN, scGESTALT) Disease characterization: Tumor heterogeneity: identifying cancer cell subtypes, immune cell infiltrates, therapy-resistant populations. Neurodegenerative disease: identifying vulnerable neuronal subtypes. COVID-19: mapping SARS-CoV-2 receptor (ACE2) expression across cell types. Beyond transcriptomics — multi-omic single-cell methods: scATAC-seq: chromatin accessibility at single-cell level (identifies open regulatory regions) CITE-seq: simultaneous measurement of surface proteins (antibody-derived tags) and mRNA. Spatial transcriptomics: measure gene expression while preserving tissue spatial context. MERFISH, seqFISH, Visium (10x Genomics), SLIDE-seq. Maps which cell types are located where in a tissue and which genes they express.
<image>Single-cell RNA sequencing workflow and analysis. Panel A: Experimental workflow — tissue dissociation into single cells; cell capture in droplets (10x Genomics Chromium shown), each droplet containing one cell and one gel bead with barcoded primers; cell lysis and mRNA capture by barcoded oligo-dT primers; reverse transcription to barcoded cDNA; pooling and sequencing. Panel B: Computational analysis pipeline — raw sequencing reads demultiplexed by cell barcode; gene-by-cell expression matrix generated using UMI counts; dimensionality reduction (PCA) followed by UMAP visualization; colored clusters represent distinct cell types identified by marker gene expression. Panel C: UMAP plot of a hypothetical tissue showing 8 distinct clusters (each a different color representing a cell type), with marker genes listed for select clusters (e.g., CD3 for T cells, CD19 for B cells, COL1A1 for fibroblasts). Arrows between clusters indicate trajectory/pseudotime analysis showing a differentiation path.</image>
V. Integrating CRISPR and Single-Cell Approaches
Perturb-seq: perform CRISPR screen and read out phenotype by scRNA-seq. Each cell receives one sgRNA perturbation; the transcriptomic consequence is measured. Reveals gene regulatory networks: how loss of each gene affects the expression of all other genes. Genome-scale Perturb-seq: performed in human cell lines targeting all ~20,000 genes. CRISPR lineage tracing: evolving CRISPR barcodes record cell division history. Express Cas9 + sgRNA targeting a synthetic barcode; cumulative indels create unique signatures in each cell lineage. Combined with scRNA-seq: reconstruct lineage trees and correlate with cell fate. CRISPR-based functional genomics in organoids: Introduce CRISPR perturbations into patient-derived organoids. Assess effects on growth, differentiation, drug response in 3D tissue models. Optical pooled screening: CRISPR screen with in situ sequencing of sgRNAs and imaging-based phenotyping. Read out cellular phenotypes (morphology, protein localization, signaling) at single-cell level within a pooled screen.
VI. Therapeutic Applications of Genome Editing
Ex vivo gene therapy: Sickle cell disease / beta-thalassemia: exa-cel (Casgevy) — first FDA-approved CRISPR therapy (2023) Patient HSCs edited ex vivo to reactivate fetal hemoglobin (disrupt BCL11A erythroid enhancer) Edited cells transplanted back to the patient. CAR-T cells: CRISPR used to knock out endogenous TCR and insert CAR -> "universal" allogeneic CAR-T cells. In vivo gene editing: Lipid nanoparticle delivery of Cas9 mRNA + sgRNA to the liver. NTLA-2001: targets TTR gene for transthyretin amyloidosis; single IV infusion reduces serum TTR by >90%. Ethical considerations: Somatic cell editing: widely accepted (changes not heritable) Germline editing: heritable changes; highly controversial. He Jiankui CRISPR-edited human embryos (2018) — widely condemned; CCR5 editing of twin girls. International moratorium on clinical germline editing. Off-target effects: potential unintended edits at other genomic loci. Mitigated by: high-fidelity Cas9 variants (eSpCas9, HiFi Cas9), careful sgRNA design, whole-genome off-target detection methods (GUIDE-seq, CIRCLE-seq).
