{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T18:59:51Z","timestamp":1793041191588,"version":"4.5.0"},"reference-count":53,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biology"],"abstract":"<jats:p>Stress-associated transcriptional programs are common in single-cell perturbation data, but they are often treated as technical or experimental nuisance signals. Whether rare high-stress populations arise stochastically after perturbation or reflect outcomes associated with pre-existing cellular heterogeneity remains unclear. Herein, we build a cross-dataset stress-program prediction framework spanning 146,321 single cells and 926 perturbation\u2013cell-line tasks. Untreated baseline heterogeneity, together with perturbation identity, predicted future rare integrated-stress burden across held-out cell-line\u2013drug pairs (R2=0.742, Pearson r=0.862). Single-cell stress-program prediction generalized across leave-task-out, leave-cell-line-out and leave-perturbation-out splits; retained signal in leave-dataset-out evaluation; and collapsed to near-null performance under within-task label permutation. Independent validation datasets provided external support for the inferred stress axes: tunicamycin and thapsigargin activated unfolded protein response\/integrated stress response (UPR\/ISR) modules in bulk RNA sequencing (RNA-seq), thapsigargin expanded populations with high X-box binding protein 1 (XBP1) UPR or activating transcription factor 4 (ATF4) ISR activity in donor-paired single-cell data, and an independent protocol-stress dataset indicated heat shock\/proteostasis structure beyond cell type and quality control (QC). The resulting resource summarizes perturbation responses as activator protein 1 (AP1) immediate, UPR\/ATF4, heat shock, replication-coupled and low\/mixed dominant stress-program patterns. These findings suggest that stress variation should not be viewed solely as a nuisance covariate but may represent a predictable and biologically structured dimension of perturbation response space.<\/jats:p>","DOI":"10.3390\/biology15151230","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T15:05:42Z","timestamp":1784819142000},"page":"1230","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Pre-Existing Heterogeneity Predicts Rare Proteostasis-Stress Programs Across Diverse Perturbations"],"prefix":"10.3390","volume":"15","author":[{"given":"Zongnan","family":"Lyu","sequence":"first","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunxue","family":"Shao","sequence":"additional","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Yu","sequence":"additional","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7236-7483","authenticated-orcid":false,"given":"Guang","family":"Yang","sequence":"additional","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3953-0493","authenticated-orcid":false,"given":"Ziheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.1016\/j.cell.2016.11.038","article-title":"Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens","volume":"167","author":"Dixit","year":"2016","journal-title":"Cell"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1016\/j.cell.2022.05.013","article-title":"Mapping information-rich genotype\u2013phenotype landscapes with genome-scale Perturb-seq","volume":"185","author":"Replogle","year":"2022","journal-title":"Cell"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1126\/science.aax6234","article-title":"Massively multiplex chemical transcriptomics at single-cell resolution","volume":"367","author":"Srivatsan","year":"2020","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4296","DOI":"10.1038\/s41467-020-17440-w","article-title":"Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action","volume":"11","author":"McFarland","year":"2020","journal-title":"Nat. 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