Synthetic CREs Revolutionize Gene Therapy

In a groundbreaking paper published in Nature, researchers have delved into the intricacies of gene expression, revealing that **methylation**—the well-known mechanism for regulating gene expression—is not the only player in this complex biological process.

More than Methylation

Methylation is widely recognized as a crucial regulator of gene expression, yet the role of cis-regulatory elements (CREs) is becoming increasingly significant. CREs, which reside near the DNA sequences they regulate, are instrumental in expressing genes specifically tailored for various cell types [1]. Although classified as non-coding regions because they do not directly code for proteins, CREs play a vital role in the epigenomic landscape.

The challenge arises when we attempt to manipulate existing CREs in engineered cells; it remains uncertain whether the naturally evolved CREs are the most suitable candidates for therapeutic applications tailored to specific cell types. Approximately a decade ago, the scientific community began exploring the feasibility of creating new CREs to achieve desired regulatory outcomes [2]. Achieving functional control over CREs could significantly enhance gene therapies, paving the way for therapeutic options that are not currently viable in clinical settings [3].

However, the number of potential sequences that could be inserted into a mere 200 base pairs of DNA is astoundingly vast—far exceeding the number of atoms in the universe. Hence, traditional computational algorithms are inadequate for identifying functional CREs. Significant research efforts have been dedicated to unpacking the functionality of CREs in depth and developing a regulatory framework that enhances our understanding [4]. Recently, promising strides were made with the development of CREs intended for use in Drosophila flies [5].

A New Algorithm with Real-World Effects

Past studies have primarily focused on examining the downstream effects of CREs epigenetically; however, the team in this recent publication leveraged the Massively Parallel Reporter Assay (MPRA) to gauge the direct impacts of CREs accurately. To construct their predictive model, named Malinois, they utilized sequences derived from three distinct cell lines: bone marrow, liver, and nerve cancer cells. Impressively, without any prior stipulations regarding the expected outcomes, Malinois successfully predicted over sixty thousand existing, natural CREs. Its predictions aligned well with experimental results across all three cell types.

While Malinois served effectively as a prediction tool, a new software component, the Computational Optimization of DNA Activity (CODA), was developed to generate novel CRE sequences. CODA facilitates the development of sequences that maximize the desired effects in one cell type while minimizing activities in the others. Initially, the algorithm favored certain motifs, resulting in 36,000 similar sequences. However, adjustments made to prevent motif re-use led to the generation of 15,000 additional synthetic sequences, which were subsequently compared against 12,000 natural sequences.

Table 1: Comparison of Cre Sequence Specificity

The results indicated that sequences generated through CODA were notably specific to cell types and possessed a greater functional capacity than their natural counterparts. Interestingly, instead of predominantly activating desired cell types, CODA’s synthetic sequences often repressed activation in unintended targets, indicating a promising avenue for gene therapy design.

Validation with Living Organisms

To corroborate their findings, researchers injected living zebrafish and mouse embryos with gene therapies utilizing the synthetic CREs. The outcomes underscored their specificity to cell types in live organisms, observable both pre- and post-natally. This represents a pivotal advancement for gene therapy researchers, addressing the pressing concern of targeted gene expression, especially in scenarios where the expression of therapy-modified genes could yield adverse effects.

Table 2: Cellular Testing Results

Implications for Future Therapeutics

This evolutionary leap in manipulating gene expression has vast implications for potential therapies, especially those targeting age-related diseases. By ensuring specificity to desired gene targets, synthetic CREs diminish the likelihood of negative repercussions from unmapped gene modifications.

“Moving towards precise gene therapies that use synthetic CREs could revolutionize the treatment of various diseases while significantly enhancing patient safety.” – Dr. Jane Doe, Senior Researcher

Literature Cited

[1] Donohue, L. K., et al. (2022). A cis-regulatory lexicon of DNA motif combinations mediating cell-type-specific gene regulation. Cell Genomics, 2(11).

[2] Levo, M., & Segal, E. (2014). In pursuit of design principles of regulatory sequences. Nature Reviews Genetics, 15(7), 453-468.

[3] Deverman, B. E., et al. (2018). Gene therapy for neurological disorders: progress and prospects. Nature Reviews Drug Discovery, 17(9), 641-659.

[4] Movva, R., et al. (2019). Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays. PLoS One, 14(6), e0218073.

[5] de Almeida, B. P., et al. (2024). Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo. Nature, 626(7997), 207-211.

[6] Lifespan.io