Biology subjects

Goldbach, L.

Publications and source records attributed to Goldbach, L..

3 recordsLinked to original sources

bioRxiv2024

The adaptive landscapes of three global Escherichia coli transcriptional regulators

The evolution of gene regulation is a major source of evolutionary adaptation and innovation, particularly when organisms encounter new or changing environments. Central to this process is the emergence of new transcription factor binding sites (TFBSs). Adaptive landscapes provide a powerful framework to study such emergence by linking regulatory DNA sequences to their transcriptional outputs. Although several landscapes have been characterized for DNA, RNA, and proteins, large-scale in vivo adaptive landscapes for bacterial TFBSs remain scarce. Here, we address this gap by experimentally mapping the first comprehensive in vivo regulatory landscapes for three global transcription factors in Escherichia coli: CRP, Fis, and IHF. Using a massively parallel reporter assay, we quantify the regulation strength of more than 30,000 TFBS variants for each factor and reconstruct their adaptive landscapes. All three landscapes are highly rugged and exhibit pervasive epistasis, with thousands of local peaks distributed broadly across sequence space. This ruggedness contrasts sharply with the much smoother TFBS landscapes of eukaryotes. It suggests greater constraints on the evolution of prokaryotic gene regulation. Nonetheless, evolutionary simulations show that [~]10% of evolving populations can reach a peak of strong regulation, a proportion that is significantly greater than in comparable random landscapes. Adaptive evolution starting from the same DNA sequence can attain different high peaks, and some peaks are reached more frequently than others. Together, our results show that de novo adaptive evolution of new gene regulation in bacteria is feasible, but subject to a blend of chance, historical contingency, and evolutionary biases.

evolutionary biology↗

bioRxiv2024

Entangled adaptive landscapes facilitate the evolution of gene regulation by exaptation

Exaptation, the co-option of existing traits for new functions, is a central process in Darwinian evolution. However, the molecular changes leading to exaptations remain unclear. We investigated the potential of bacterial transcription factor binding sites (TFBSs) to evolve exaptively for the three global E. coli transcription factors (TFs) CRP, Fis, and IHF. Using a massively parallel reporter assay, we mapped three combinatorially complete adaptive landscapes, encompassing all intermediate sequences between three pairs of strong TFBSs for each TF. Our results revealed that these landscapes are smooth and navigable, with a monotonic relationship between mutations and their impact on gene regulation. Starting from a strong TFBS for one of our TFs, Darwinian evolution can create a strong TFBS for another TF through a small number of individually adaptive mutations. Notably, most intermediate genotypes are prone to transcriptional crosstalk - gene regulation mediated by both TFs. Because our landscapes are smooth, Darwinian evolution can also easily create TFBSs that show such crosstalk whenever it is adaptive. We also present evidence of exaptive evolution and crosstalk from an analysis of bacterial genomes. Our study presents the first in vivo evidence that new TFBSs can evolve exaptively through multiple small and adaptive mutational steps. It also highlights the importance of regulatory crosstalk for the diversification of gene regulation.

evolutionary biology↗

bioRxiv2023

The highly rugged yet navigable regulatory landscape of the bacterial transcription factor TetR

Transcription factor binding sites (TFBSs) are important sources of evolutionary innovations. Understanding how evolution navigates the sequence space of such sites can be achieved by mapping TFBS adaptive landscapes. In such a landscape, an individual location corresponds to a TFBS bound by a transcription factor. The elevation at that location corresponds to the strength of transcriptional regulation conveyed by the sequence. We developed an in vivo massively parallel reporter assay to map the landscape of bacterial TFBSs. We applied this assay to the TetR repressor, for which few TFBSs are known. We quantify the strength of transcriptional repression for 17,765 TFBSs and show that the resulting landscape is highly rugged, with 2,092 peaks. Only a few peaks convey stronger repression than the wild type. Non-additive (epistatic) interactions between mutations are frequent. Despite these hallmarks of ruggedness, most high peaks are evolutionarily accessible. They have large basins of attraction and are reached by around 20% of populations evolving on the landscape. Which high peak is reached during evolution is unpredictable and contingent on the mutational path taken. This first in-depth analysis of a prokaryotic gene regulator reveals a landscape that is navigable but much more rugged than the landscapes of eukaryotic regulators. SignificanceUnderstanding how evolution explores the vast space of genotypic possibilities is a fundamental question in evolutionary biology. The mapping of genotypes to quantitative traits (such as phenotypes and fitness) allows us to delineate adaptive landscapes and their topological properties, shedding light on how evolution can navigate such vast spaces. In this study, we focused on mapping a transcription factor binding site (TFBS) landscape to gene expression levels, as changes in gene expression patterns play a crucial role in biological innovation. We developed a massively parallel reporter assay and mapped the first comprehensive in vivo gene regulatory landscape for a bacterial transcriptional regulator, TetR. Surprisingly, this landscape is way more rugged than those observed in eukaryotic regulators. Despite its ruggedness, the landscape remains highly navigable through adaptive evolution. Our study presents the first high-resolution landscape for a bacterial TFBS, offering valuable insights into the evolution of TFBS in vivo. Moreover, it holds promise as a framework for discovering new genetic components for synthetic biological systems.

evolutionary biology↗