Bioinformatic Application of Fluorescence-Based In Vivo RNA Regional Accessibility Data to Identify Novel sRNA Targets

Innovative Strategies to Enhance mRNA Vaccine Delivery and Effectiveness: Mechanisms and Future Outlook

The creation of mRNA vaccines has transformed the area of vaccination and allowed for the production of COVID-19 vaccines with previously unheard-of speed and effectiveness. The development of novel strategies to enhance the delivery and efficiency of mRNA vaccines has been motivated by the ongoing constraints of the present mRNA vaccine delivery systems. In this context, intriguing methods to get beyond these restrictions include lipid nanoparticles, self-amplifying RNA, electroporation, microneedles, and cell-targeted administration. These innovative methods could increase the effectiveness, safety, and use of mRNA vaccines, making them more efficient, effective, and broadly available. Additionally, mRNA technology may have numerous and far-reaching uses in the field of medicine, opening up fresh avenues for the diagnosis and treatment of disease. This paper gives an overview of the existing drawbacks of mRNA vaccine delivery techniques, the creative solutions created to address these drawbacks, and their prospective public health implications. The development of mRNA vaccines for illnesses other than infectious diseases and creating scalable and affordable manufacturing processes are some of the future directions for research in this area that are covered in this paper.

Uncovering Transcriptional Regulators and Targets of sRNAs Using an Integrative Data-Mining Approach: H-NS-Regulated RseX as a Case Study

Bacterial small RNAs (sRNAs) play a vital role in pathogenesis by enabling rapid, efficient networks of gene attenuation during infection. In recent decades, there has been a surge in the number of proposed and biochemically-confirmed sRNAs in both Gram-positive and Gram-negative pathogens. However, limited homology, network complexity, and condition specificity of sRNA has stunted complete characterization of the activity and regulation of these RNA regulators. To streamline the discovery of the expression of sRNAs, and their post-transcriptional activities, we propose an integrative in vivo data-mining approach that couples DNA protein occupancy, RNA-seq, and RNA accessibility data with motif identification and target prediction algorithms. We benchmark the approach against a subset of well-characterized E. coli sRNAs for which a degree of in vivo transcriptional regulation and post-transcriptional activity has been previously reported, finding support for known regulation in a large proportion of this sRNA set. We showcase the abilities of our method to expand understanding of sRNA RseX, a known envelope stress-linked sRNA for which a cellular role has been elusive due to a lack of native expression detection. Using the presented approach, we identify a small set of putative RseX regulators and targets for experimental investigation. These findings have allowed us to confirm native RseX expression under conditions that eliminate H-NS repression as well as uncover a post-transcriptional role of RseX in fimbrial regulation. Beyond RseX, we uncover 163 putative regulatory DNA-binding protein sites, corresponding to regulation of 62 sRNAs, that could lead to new understanding of sRNA transcription regulation. For 32 sRNAs, we also propose a subset of top targets filtered by engagement of regions that exhibit binding site accessibility behavior in vivo. We broadly anticipate that the proposed approach will be useful for sRNA-reliant network characterization in bacteria. Such investigations under pathogenesis-relevant environmental conditions will enable us to deduce complex rapid-regulation schemes that support infection.

Translational control of enzyme scavenger expression with toxin-induced micro RNA switches

Biological computation requires in vivo control of molecular behavior to progress development of autonomous devices. miRNA switches represent excellent, easily engineerable synthetic biology tools to achieve user-defined gene regulation. Here we present the construction of a synthetic network to implement detoxification functionality. We employed a modular design strategy by engineering toxin-induced control of an enzyme scavenger. Our miRNA switch results show moderate synthetic expression control over a biologically active detoxification enzyme molecule, using an established design protocol. However, following a new design approach, we demonstrated an evolutionarily designed miRNA switch to more effectively activate enzyme activity than synthetically designed versions, allowing markedly improved extrinsic user-defined control with a toxin as inducer. Our straightforward new design approach is simple to implement and uses easily accessible web-based databases and prediction tools. The ability to exert control of toxicity demonstrates potential for modular detoxification systems that provide a pathway to new therapeutic and biocomputing applications.