TF Binding Mapped through DynaTag in Single Cells, Low-Input Samples

Mapping transcription issue (TF) binding websites throughout the genome is essential to understanding how cells management gene expression, but pinpointing their footprints throughout the genome—particularly in single cells or small samples—has remained a technical bottleneck within the fields of molecular biology, genetics, and epigenetics. A brand new approach known as DynaTag could also be a promising new method to understanding TF landscapes.

In a examine titled “DynaTag for efficient mapping of transcription factors in low-input samples and at single-cell resolution,” printed in Nature Communications, DynaTag (cleavage beneath Dynamic targets and Tagmentation) permits high-resolution mapping of transcription issue binding websites—even from low-input or single-cell samples. The methodology, developed by researchers on the University of Cologne, depends on a physiological salt buffer to protect TF–DNA interactions which might be usually misplaced throughout pattern processing with normal high-salt protocols. “TF–DNA interactions are sensitive to these stringent conditions, causing their dissociation from chromatin and incompatibility with these tagmentation-based technologies,” reported the researchers. DynaTag makes use of a physiological intracellular salt resolution all through all nuclei dealing with steps to retain particular interactions whereas suppressing nonspecific protein–DNA interactions, added the analysis workforce.

“DynaTag outperforms existing methods such as ChIP-seq and CUT&RUN in terms of sensitivity and resolution,” stated senior creator Robert Hänsel-Hertsch, PhD, principal investigator on the Center for Molecular Medicine Cologne (CMMC). “The new method delivers high-resolution mapping of the DNA regions where transcription factors bind.”

Using DynaTag, the workforce profiled 15 transcription components in each stem cell and most cancers fashions. In embryonic stem cells, the tactic revealed dynamic binding patterns for components reminiscent of NANOG, MYC, and OCT4 as cells transitioned to an epiblast-like state. Single-nuclei DynaTag additional confirmed that distinct TF occupancy patterns had been sufficient to tell apart cell states, highlighting its utility in developmental biology and heterogeneous tissue evaluation.

The authors additionally utilized DynaTag to small cell lung most cancers (SCLC), a fast-growing most cancers kind infamous for its resistance to remedy. In a patient-derived mouse mannequin, the researchers used DynaTag to check TF binding earlier than and after chemotherapy. They discovered that the transcription components FOXA1 and MYC confirmed elevated occupancy in chemotherapy-resistant tumors, whereas components like ASCL1 and POU2F3 declined. Likewise, the outcomes additional confirmed considerably elevated FOXA1 and MYC occupancies at genes concerned in a number of metabolic pathways, reminiscent of fatty acid metabolism.

Intriguingly, the tactic additionally advised a gain-of-function for a mutant p53 variant (R248Q), which turned extra lively at genes linked to epithelial-mesenchymal transition (EMT)—a possible route for most cancers cells to flee therapy. These insights, the researchers say, weren’t detectable utilizing various strategies like ATAC-seq footprinting.

“It had already been established that certain signaling pathways promoting resistance or metastasis are activated after chemotherapy in small cell lung cancer. However, it was not known which transcription factors regulate these signaling pathways,” stated Hänsel-Hertsch. “With the help of DynaTag, we were able to identify specific transcription factors that show increased binding to genes belonging to these signaling pathways after chemotherapy and are likely to promote further tumor growth.”