Antwi, E. B. | Search bioRxiv

bioRxiv2025

A transcription factor-responsive enhancer discovery platform for targeted immunotherapy

Synthetic enhancers with high specificity are crucial for therapeutic gene control. However, experimental screens and machine learning-guided design typically require context-specific datasets, limiting generalizability. Because transcription factor (TF) activity reflects cellular state, TF-responsive enhancer libraries offer a universal starting point. Here, we developed TREND (transcription factor-responsive enhancer discovery), a massively parallel reporter assay of [~]2.7 million enhancer-barcode constructs representing 57,715 designs. TREND covers 1,068 motif-annotated proteins, including 729 confirmed TFs across 49 DNA-binding domain families. Applied to ovarian cancer, TREND identified enhancers that discriminate cancer from normal epithelial cells. These enhancers enabled protein-interaction-based AND-gate circuits with reduced OFF-state leakage and amplified ON-state output, driving tumor-restricted expression of combinatorial immune effectors and robust antitumor responses in murine ovarian cancer models. TREND also identified T-cell activation-responsive enhancers with greater inducibility and lower basal activity than conventional NFAT-motif-based elements. Together, TREND provides a generalizable framework for context-specific enhancer discovery and therapeutic gene regulation.

synthetic biology↗

bioRxiv2021

Requirements for mammalian promoters to decode transcription factor dynamics

In response to different stimuli many transcription factors (TFs) display different activation dynamics that trigger the expression of specific sets of target genes, suggesting that promoters have a way to decode them. Combining optogenetics, deep learning-based image analysis and mathematical modeling, we find that decoding of TF dynamics occurs only when the coupling between TF binding and transcription pre-initiation complex formation is inefficient and that the ability of a promoter to decode TF dynamics gets amplified by inefficient translation initiation. Furthermore, we propose a theoretical mechanism based on phase separation that would allow a promoter to be activated better by pulsatile than sustained TF signals. These results provide an understanding on how TF dynamics are decoded in mammalian cells, which is important to develop optimal strategies to counteract disease conditions, and suggest ways to achieve multiplexing in synthetic pathways.

systems biology↗

bioRxiv2019

Whole-genome fingerprint of the DNA methylome during chemically induced differentiation of the human AML cell line HL-60/S4

BackgroundMyeloid differentiation gives rise to a plethora of immune cells in the human body. This differentiation leaves strong signatures in the epigenome through each differentiated state of genetically identical cells. The leukemic HL-60/S4 promyelocytic cell can be easily differentiated from its undifferentiated promyelocyte state into neutrophil-and macrophage-like cell states, making it an excellent system for studying myeloid differentiation. In this study, we present the underlying genome and epigenome architecture of HL-60/S4 through its undifferentiated and differentiated cell states.\n\nResultsWe performed whole genome bisulphite sequencing of HL-60/S4 cells and their differentiated counterparts. With the support of karyotyping, we show that HL-60/S4 maintains a stable genome throughout differentiation. Analysis of differential CpG methylation reveals that most methylation changes occur in the macrophage-like state. Differential methylation of promoters was associated with immune related terms. Key immune genes, CEBPA, GFI1, MAFB and GATA1 showed differential expression and methylation. However, we observed strongest enrichment of methylation changes in enhancers and CTCF binding sites, implying that methylation plays a major role in large scale transcriptional reprogramming and chromatin reorganisation during differentiation. Correlation of differential expression and distal methylation with support from chromatin capture experiments allowed us to identify putative proximal and long-range enhancers for a number of immune cell differentiation genes, including CEBPA and CCNF. Integrating expression data, we present a model of HL-60/S4 differentiation in relation to the wider scope of myeloid differentiation.\n\nConclusionsFor the first time, we elucidate the genome and CpG methylation landscape of HL-60/S4 during differentiation. We identify all differentially methylated regions and positions. We link these to immune function and to important factors in myeloid differentiation. We demonstrate that methylation plays a more significant role in modulating transcription via enhancer reprogramming, rather than by promoter regulation. We identify novel regulatory regions of key components in myeloid differentiation that are regulated by differential methylation. This study contributes another layer of \"omics\" characterisation of the HL-60/S4 cell line, making it an excellent model system for studying rapid in vitro cell differentiation.\n\nSummary statementEpigenomics plays a major role in cell identity and differentiation. We present the DNA methylation landscape of leukemic cells during in-vitro differentiation, to add another omics layer to better understand the mechanisms behind differentiation.

genomics↗