Maximum Potential

Fluorescence imaging of transcription factor-mediated differentiation of early mouse muscle cells using the wild type transcription factor Myod1 (left) and the sequence optimized Myod1 variant (right). (c) Julian Naderi, MPIMG

How to improve transcription factors.

Transcription factors regulate gene expression by binding specific sequences on DNA, which is an essential step to produce messenger RNAs from protein-coding genes. Denes Hnisz’s lab, in collaboration with Martin Vingron’s lab at the MPIMG, has discovered that human transcription factors don’t typically use their full potential to help transcribe mRNA. Instead, important protein regions within transcription factors encode chemical features that generate submaximal transcriptional activity. The findings, published in Nature Cell Biology, suggest simple ways to engineer natural transcription factor variants with elevated or “optimized” activity, with potential applications for regenerative therapy.

Every cell contains the same set of genetic information, but not all of the genes are expressed in every cell. The specific patterns of gene expression in cells make a neuron look different and perform different functions than cells in other organs or tissues. Transcription factors guide the formation of tissues and organs during development, and help maintain the identity of adult cells, by binding specific DNA sequences and activating or repressing them. They face the complex problem of balancing which genes to bind and how much to activate them. How transcription factors perform and balance these functions has been a long-standing mystery. Insights from the past few years suggested that transcription factors may exert some of their functions through forming liquid-like proteinaceous droplets, called condensates. “We and others have shown that inhibiting the ability of transcription factors to form condensates also reduces their activity in cells,” explains group leader Denes Hnisz. “In our study, we now did the opposite: We enhanced the ability of transcription factors to form liquid-like droplets and found that this, in turn, improved their activity”. However, this improvement comes with a trade-off.

Improving patterns

In 2020, scientists made an observation that would provide inspiration for the current study: “It was shown that in RNA-binding proteins, periodically spaced amino acids contribute to the ability of the proteins to form liquid-like condensates. We asked whether such periodic patterns also exist in transcription factors,” says Alexandre Magalhães, a scientist in the Hnisz lab and one of the study’s first authors. In collaboration with Martin Vingron’s lab at the MPIMG, the researchers developed bioinformatics approaches to identify these periodically arranged chemical features, so called aromatic residues, in about 1,500 human transcription factors. Starting with the protein sequences of the transcription factors, the team looked for the positions of the aromatic amino acids and quantified how regularly they were arranged. “We found some traces of periodicity, but for the vast majority of factors, the patterning was quite imperfect, leaving room for improvement. We started moving the amino acids around computationally to make the spacing of the aromatic residues more uniform,” explains Denes Hnisz. Moving from computers to cells, the scientists then tested the effects of the improved protein sequences. “The transcription factors became more active. To our surprise, however, they also became less specific in binding DNA,” says Denes Hnisz.
An evolutionary trade off

“Our model is that the functional features of transcription factors, such as DNA binding specificity or activation strength are not maximal, because they are optimized for the overall contribution of the transcription factor to evolutionary fitness,” explains Julian Naderi, a PhD student and another of the paper’s first authors. “We can now show that the reason for this is that their features are in a trade-off, meaning that if you improve one, the other gets weaker and vice versa.” However, this provides an opportunity to adjust the balance between the two properties: “If you know the trade-offs, it is conceivable to tweak transcription factors, depending on which function is needed more in an application,” he adds. One possible application could be in regenerative medicine, where scientists are trying to replace damaged or lost tissue with a patient’s own cells. Since only a few transcription factors can maintain a particular cell type, it is a tempting approach to reprogram other cells into the desired type by upregulating these factors. Such approaches are currently in pre-clinical testing for example, to repair brain damage after stroke by reprogramming astrocytes into neurons. “We have shown in the study that with a minor sequence adjustment in a single transcription factor, we can significantly enhance its ability to convert cells into neurons in a cell culture dish,” says Denes Hnisz. “It will be very exciting to test whether the approach works in a stroke model.”

Originalpublikation:

Naderi J., Magalhaes AP., et. al. An activity-specificity trade-off encoded in human transcription factors. Nature Cell Biology 2024
https://doi.org/10.1038/s41556-024-01411-0

https://www.molgen.mpg.de/4726976/news_publication_22178433_transferred?c=2168

Media Contact

Sándor Fülöp Presse- und Öffentlichkeitsarbeit
Max-Planck-Institut für molekulare Genetik

All latest news from the category: Life Sciences and Chemistry

Articles and reports from the Life Sciences and chemistry area deal with applied and basic research into modern biology, chemistry and human medicine.

Valuable information can be found on a range of life sciences fields including bacteriology, biochemistry, bionics, bioinformatics, biophysics, biotechnology, genetics, geobotany, human biology, marine biology, microbiology, molecular biology, cellular biology, zoology, bioinorganic chemistry, microchemistry and environmental chemistry.

Back to home

Comments (0)

Write a comment

Newest articles

Logic with light

Introducing diffraction casting, optical-based parallel computing. Increasingly complex applications such as artificial intelligence require ever more powerful and power-hungry computers to run. Optical computing is a proposed solution to increase…

A chip-based tractor beam for biological particles

The tiny device uses a tightly focused beam of light to capture and manipulate cells. MIT researchers have developed a miniature, chip-based “tractor beam,” like the one that captures the…

A new era of solar observation

International team produces global maps of coronal magnetic field. For the first time, scientists have taken near-daily measurements of the Sun’s global coronal magnetic field, a region of the Sun…

Partners & Sponsors