Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches

High-content tailoring strategy to improve the multifunctionality of functional nucleic acids

Functional nucleic acids (FNAs) have attracted increasing attention in recent years due to their diverse physiological functions. The understanding of their conformational recognition mechanisms has advanced through nucleic acid tailoring strategies and sequence optimization. With the development of the FNA tailoring techniques, they have become a methodological guide for nucleic acid repurposing. Therefore, it is necessary to systematize the relationship between FNA tailoring strategies and the development of nucleic acid multifunctionality. This review systematically categorizes eight types of FNA multifunctionality, and introduces the traditional FNA tailoring strategy from five aspects, including deletion, substitution, splitting, fusion and elongation. Based on the current state of FNA modification, a new generation of FNA tailoring strategy, called the high-content tailoring strategy, was unprecedentedly proposed to improve FNA multifunctionality. In addition, the multiple applications of rational tailoring-driven FNA performance enhancement in various fields were comprehensively summarized. The limitations and potential of FNA tailoring and repurposing in the future are also explored in this review. In summary, this review introduces a novel tailoring theory, systematically summarizes eight FNA performance enhancements, and provides a systematic overview of tailoring applications across all categories of FNAs. The high-content tailoring strategy is expected to expand the application scenarios of FNAs in biosensing, biomedicine and materials science, thus promoting the synergistic development of various fields.

Cell-free riboswitches

The emerging community of cell-free synthetic biology aspires to build complex biochemical and genetic systems with functions that mimic or even exceed those in living cells. To achieve such functions, cell-free systems must be able to sense and respond to the complex chemical signals within and outside the system. Cell-free riboswitches can detect chemical signals via RNA-ligand interaction and respond by regulating protein synthesis in cell-free protein synthesis systems. In this article, we review synthetic cell-free riboswitches that function in both prokaryotic and eukaryotic cell-free systems reported to date to provide a current perspective on the state of cell-free riboswitch technologies and their limitations.

RNAxplorer: Harnessing the Power of Guiding Potentials to Sample RNA Landscapes

Motivation

Predicting the folding dynamics of RNAs is a computationally difficult problem, first and foremost due to the combinatorial explosion of alternative structures in the folding space. Abstractions are therefore needed to simplify downstream analyses, and thus make them computationally tractable. This can be achieved by various structure sampling algorithms. However, current sampling methods are still time consuming and frequently fail to represent key elements of the folding space.

Method

We introduce RNAxplorer, a novel adaptive sampling method to efficiently explore the structure space of RNAs. RNAxplorer uses dynamic programming to perform an efficient Boltzmann sampling in the presence of guiding potentials, which are accumulated into pseudo-energy terms and reflect similarity to already well-sampled structures. This way, we effectively steer sampling toward underrepresented or unexplored regions of the structure space.

Results

We developed and applied different measures to benchmark our sampling methods against its competitors. Most of the measures show that RNAxplorer produces more diverse structure samples, yields rare conformations that may be inaccessible to other sampling methods and is better at finding the most relevant kinetic traps in the landscape. Thus, it produces a more representative coarse graining of the landscape, which is well suited to subsequently compute better approximations of RNA folding kinetics.

Availabilityand implementation

https://github.com/ViennaRNA/RNAxplorer/.

Supplementary information

Supplementary data are available at Bioinformatics online.