Biology subjects

Rondon, J. J.

Publications and source records attributed to Rondon, J. J..

3 recordsLinked to original sources

bioRxiv2026

Evolution of allostery without shape shifting: Internal dynamics drives functional diversification of a transcriptional repressor superfamily

Allostery enables proteins to couple environmental signals to functional outputs, yet how allosteric mechanisms diversify during evolution remains poorly understood. Here, we address this question in the ubiquitous and functionally diverse arsenic repressor (ArsR) superfamily by integrating information-theoretic bioinformatics, structural characterization of DNA recognition and NMR measurements of fast internal dynamics. We identify conserved residues that define the structural scaffold of ArsR proteins and subfamily-specific positions that encode inducer and DNA specificity. In the persulfide sensor SqrR, the crystal structure of the DNA-bound complex reveals how operator specificity is encoded by a limited set of residues, consistent with sequence-derived predictions functionally validated by in vitro transcription assays across divergent ArsR regulators. We further show that allosteric inhibition of DNA binding in SqrR occurs without large-scale conformational rearrangements and is instead associated with changes in internal dynamics, as previously observed for the zinc sensor CzrA. Together, these results support a model in which conformational entropy preserves allosteric connectivity while relaxing sequence constraints, thereby enabling functional diversification within a protein superfamily.

biochemistry↗

bioRxiv2026

Functional diversity across families of bacterial metalloregulators: what can we learn about specificity from sequence similarity?

The exponential growth of sequence databases, driven by large-scale genome sequencing, has created a major challenge for the functional annotation of proteins, particularly within highly divergent families such as bacterial metal-responsive transcription factors. In these systems, low sequence identity places many proteins within the so-called "twilight zone" of the proteome, where homology inference and functional assignment become unreliable. Here, we integrate sequence similarity networks (SSNs) with structural approaches to explore the functional diversity of twelve metalloregulatory families. Using SSNs, we partition each family into putative isofunctional clusters and map available experimental annotations onto network topology, revealing substantial heterogeneity in both sequence diversity and functional characterization across families. While some families, such as ArsR and CsoR, display relatively well-defined functional landscapes, others, including LysR, TetR, and GntR, remain largely unexplored despite their large sequence space. Structural comparisons further show that, despite extensive sequence divergence, conserved architectural features underpin DNA recognition and regulatory mechanisms across families. Focusing on the MerR and Fur families, we identify conserved residues associated with inducer binding and DNA recognition, and uncover distinct functional subgroups, including metal-specific sensors and regulators with alternative signaling mechanisms. Finally, we demonstrate that cluster-derived HMM profiles enable sensitive detection of candidate regulators in non-model genomes, revealing lineage-specific expansions and diversification of metal-sensing repertoires. Together, our results provide a framework for mapping functional diversity in highly divergent protein families and highlight the potential of combining SSNs and structural information to guide the discovery of novel transcriptional sensors.

bioinformatics↗

bioRxiv2026

In vitro evolution of DNA operators enables multivalency protein-DNA interactions: towards programmable transcription factor regulation

In vitro transcription (IVT) systems regulated by allosteric transcription factors (aTFs) are central to emerging cell-free biosensing and synthetic biology platforms, yet their performance is often limited by suboptimal protein-DNA interactions and the need for well-characterized regulatory elements. Here, we report an in vitro evolution strategy to engineer DNA operator sequences that enables tunable aTF-DNA interactions without requiring prior detailed knowledge of the native operator or regulatory mechanism. Using a SELEX-based approach with integrated positive and counter-selection steps, we evolved non-natural operators for the sulfane sulfur-responsive transcriptional repressor SqrR. The selected sequences preserve ligand-responsive allostery, with some sequences exhibiting enhanced binding affinity and reducing transcriptional leakage. Notably, we identify operator with binding behaviors consistent with cooperative recruitment of multiple SqrR dimers, suggesting that sequence architecture can modulate aTF-DNA interactions beyond affinity alone. Incorporation of these operators into IVT circuits improves transcriptional control and dynamic range, enabling the development of ROSALIND-based sensors for sulfane sulfur species, achieving sensitive and selective detection in a fully cell-free format. More broadly, this work establishes operator evolution as a programmable strategy to optimize transcription factor-DNA interactions and expand the design space of transcription-based biosensors, including for systems lacking well-characterized genetic components.

synthetic biology↗