单细胞CRISPR扰动几何相干性揭示调控结构并预测细胞应激反应

Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress

April 17, 2026

作者: Prashant C. Raju

cs.AI

摘要

基因組工程已實現卓越的序列層級精準度，但預測細胞在受干擾後將佔據的轉錄組狀態仍是未解難題。單細胞CRISPR篩選技術能測量細胞偏離未受擾動狀態的距離，然而這種效應強度忽略了一個根本問題：細胞是否協同移動？若某次干擾使細胞沿共享軌跡一致移動，而另一次干擾使細胞在表達空間中分散，即使兩者強度相同也會產生質性不同的結果。我們提出名為Shesha的幾何穩定性指標，通過計算單個細胞位移向量與平均擾動方向間餘弦相似度的均值，量化單細胞擾動反應的方向一致性。在五個CRISPR數據集（涵蓋CRISPRa、CRISPRi及混合篩選的2,200+次擾動）中，穩定性與效應強度呈現強相關（斯皮爾曼ρ=0.75-0.97），經校準的跨數據集相關性達0.97。關鍵在於，當兩項指標解耦時的不一致案例能揭示調控架構：如CEBPA和GATA1等多效性主調控因子需支付「幾何代價」，產生強烈但雜亂的位移；而如KLF1等譜系特異性因子則能產生高度協調的反應。控制強度變量後，幾何不穩定性獨立伴隨分子伴侶活化升高（HSPA5/BiP；跨數據集偏相關ρ為-0.34與-0.21），且高穩定性/高應力象限出現系統性耗竭。這種強度-穩定性關係在scGPT基礎模型嵌入中持續存在，證實其為生物狀態空間的固有特性而非線性投影的產物。擾動穩定性為篩選中的靶點優先級排序、細胞製造中的表型質量控制，以及計算機模擬擾動預測的評估提供了補充維度。

English

Genome engineering has achieved remarkable sequence-level precision, yet predicting the transcriptomic state that a cell will occupy after perturbation remains an open problem. Single-cell CRISPR screens measure how far cells move from their unperturbed state, but this effect magnitude ignores a fundamental question: do the cells move together? Two perturbations with identical magnitude can produce qualitatively different outcomes if one drives cells coherently along a shared trajectory while the other scatters them across expression space. We introduce a geometric stability metric, Shesha, that quantifies the directional coherence of single-cell perturbation responses as the mean cosine similarity between individual cell shift vectors and the mean perturbation direction. Across five CRISPR datasets (2,200+ perturbations spanning CRISPRa, CRISPRi, and pooled screens), stability correlates strongly with effect magnitude (Spearman ρ=0.75-0.97), with a calibrated cross-dataset correlation of 0.97. Crucially, discordant cases where the two metrics decouple expose regulatory architecture: pleiotropic master regulators such as CEBPA and GATA1 pay a "geometric tax," producing large but incoherent shifts, while lineage-specific factors such as KLF1 produce tightly coordinated responses. After controlling for magnitude, geometric instability is independently associated with elevated chaperone activation (HSPA5/BiP; ρ_{partial}=-0.34 and -0.21 across datasets), and the high-stability/high-stress quadrant is systematically depleted. The magnitude-stability relationship persists in scGPT foundation model embeddings, confirming it is a property of biological state space rather than linear projection. Perturbation stability provides a complementary axis for hit prioritization in screens, phenotypic quality control in cell manufacturing, and evaluation of in silico perturbation predictions.