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

Bowman, Emily K.; Mihailovic, Mia K.; Li, Bridget; Contreras, Lydia M.

doi:10.1007/978-1-0716-0278-2_5

Cited by 3 publications

(7 citation statements)

References 30 publications

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“…Engineering signal-responsive RNA circuits and switches has gained significant interest recently following the successful reprogramming of translation in yeast exploiting a mechanism termed − 1 programmed ribosomal frameshifting (− 1 PRF) 43 , which resulted in advances in synthetic RNA-based logic computation in HeLa cells 7,44 . Previously, aptamer-based biosensors have been coupled to enzymes to regulate gene expression 11,12 , but implementation in mammalian cells has been limited compared to applications of riboswitchbased sensors in prokaryotes [45][46][47][48][49] . Our results demonstrate that post-transcriptional gene regulation by miRNA switches can encode a detoxification function, which is dependent on an intracellular biosensing event.…”

Section: Discussionmentioning

confidence: 99%

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

Pollak

Cooper-White

Macdonald

2021

Sci Rep

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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.

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Section: Discussionmentioning

confidence: 99%

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

Pollak

Cooper-White

Macdonald

2021

Sci Rep

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“…Importantly, only the most favorable interaction between a sRNA and each mRNA sequence was considered for downstream processing. Predictions corresponding to each sRNA were subject to exclusion criteria based on thermodynamically-predicted (most favorable) interaction reliance on the likely-functional region, as previously described ( Bowman et al., 2020 ). Briefly, the engagement of at least 80% of the likely-functional region in the predicted interaction was required.…”

Section: Methodsmentioning

confidence: 99%

“…Binding assays were performed as previously described ( Bowman et al., 2020 ). Briefly, DNA corresponding to RseX and representative mRNA sequences (observed 5’ start from previously published RNA expression data ( Sowa et al., 2017 ) to at least 30 nts downstream of proposed interaction site) were amplified from genomic K-12 MG1655 DNA with an overhanging forward primer to enable in vitro transcription (IVT) via T7 MegaSCRIPT kit (Thermo Fisher) ( Supplementary Table 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…In the post-transcriptional node of the ID-sRnA pipeline, we integrate omics-enabled regional (9-16 nt) RNA accessibility data, previously collected for a large pool of E. coli sRNAs, (Mihailovic et al, 2018) with computational target predictions to compile an accessibility-informed, filtered set of top-5 (arbitrary cutoff for rank comparison purposes) putative trans targets. The method of informing computational predictions with in vivo information, i.e., extremely accessible sRNA regions, was previously shown to increase positive predictive value for a subset of E. coli sRNA targets (Mihailovic et al, 2018;Bowman et al, 2020). It is important to note that our selection of likely functional regions in this approach differs from previous efforts; FIGURE 1 | An integrative top-down datamining approach utilizes publicly-available omics datasets to understand cellular regulation of and by any sRNA of interest.…”

Section: Development Of Integrative Data-mining Approach To Uncover Regulators and Targets Of Srnasmentioning

confidence: 99%

“…For sRNAs with known Hfq dependencies, reduced accessibility of 5 putative regulatory sites in a kanR-cured isogenic Dhfq strain (Methods) lent further confidence to region selection (Supplementary Data 1) given the accepted role of Hfq in rearranging sRNA structure for optimal target base-pairing (Santiago-Frangos Andrew, 2018) that has previously been captured by regional accessibility studies (Mihailovic et al, 2018). These 41 sites were used as filters for IntaRNA predictions to rank all predictions from highest to lowest likelihood of being true sRNA targets, as previously described (Bowman et al, 2020). Briefly, predicted target mRNAs were reranked under the constraint that 80% of the proposed sRNA seed region was involved in predicted mRNA binding.…”

Section: Development Of Integrative Data-mining Approach To Uncover Regulators and Targets Of Srnasmentioning

confidence: 99%

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

Mihailovic

Ekdahl

Chen

et al. 2021

Front. Cell. Infect. Microbiol.

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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.

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

Verma,

Awasthi

2024

CPD

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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.

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

Cited by 3 publications

References 30 publications

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

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

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

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

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