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Mikulik, K.

Publications and source records attributed to Mikulik, K..

2 recordsLinked to original sources

Time-resolved single-cell screening reveals the dynamic regulatory architecture of human cardiogenesis

Congenital heart disease (CHD) originates during early embryogenesis, yet when disease genes act cannot be determined from existing data. Human fetal heart atlases lack critical time points, and perturbation screens that systematically assess gene function currently profile at most a few time points. Here we combined single-cell CRISPR screening of 400 disease-relevant genes in cardioids, sampled daily over seven developmental days (~975,000 cells), with a matched multiome atlas. Perturbation phenotypes were strongly dependent on developmental stage. Perturbations that reshaped cell-fate allocation or gene expression were enriched for CHD-linked genes, and most acted already during progenitor stages. Timing was largely independent of the target gene's own expression, marking instead when a cell state became functionally dependent on it, and some effects persisted after expression declined. Consensus gene regulatory networks integrating perturbation and multiome data recovered stage-specific regulators and nominated HOXB2 and HOXB3 as candidate cardiac regulators. Many perturbations converged on shared downstream programmes, which were reorganised through differentiation. Effects correlated in progenitors were maintained in differentiated cells, split into distinct programmes, converged with other perturbations or disappeared entirely, indicating that gene function is highly context dependent. Beyond advancing our understanding of the developmental regulatory logic underlying CHD, our work provides a resource for developing context-dependent models for in silico prediction of perturbation effects.

genomics↗

Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics

Glioblastoma (GB) is one of the most lethal human cancers, marked by profound intratumoral heterogeneity and near-universal treatment resistance. Cellular plasticity, the capacity of cancer cells to transition between phenotypic states, drives GB progression and resistance. However, the regulatory logic that permits or restricts specific state transitions remains poorly understood. Here, we integrated single-nucleus RNA and chromatin accessibility multi-ome profiles from over one million cells across primary IDH-wildtype GBs and developed scDORI, a scalable deep-learning framework to infer enhancer-driven gene regulatory networks (eGRNs) at single-cell resolution. Our analysis revealed a structured hierarchy of GB cell states governed by distinct regulatory programs, with marked variability in epigenetic plasticity that enables or constrains transitions. Neuronal-like tumor cells emerge as a low plasticity state that deploys active repression, in contrast to more permissive progenitor-like and astrocytic states. We identified the neuronal-like state-specific repressor MYT1L as a key regulator that silences master transcription factors of alternative states. MYT1L gain-of-function in patient-derived GB cells reduced chromatin accessibility, induced neuronal-like identity, and restricted proliferation and invasion in vivo, whereas loss-of-function reactivated plasticity and accelerated malignant features. Our findings delineate the epigenetic architecture and associated transcriptional master regulators that shape GB state trajectories, and establish safeguard repressors such as MYT1L as potential therapeutic targets to constrain malignant plasticity.

cancer biology↗