Transcriptional approaches to riboswitch studies

Riboswitch Distribution in the Human Gut Microbiome Reveals Common Metabolite Pathways

Riboswitches are widely distributed, conserved RNAs which regulate metabolite levels in bacterial cells through direct, noncovalent binding of their cognate metabolite. Various riboswitch families are highly enriched in gut bacteria, suggestive of a symbiotic relationship between the host and bacteria. Previous studies of the distribution of riboswitches have examined bacterial taxa broadly. Thus, the distribution of riboswitches associated with bacteria inhabiting the intestines of healthy individuals is not well understood. To address these questions, we survey the gut microbiome for riboswitches by including an international database of prokaryotic genomes from the gut samples. Using Infernal, a program that uses RNA-specific sequence and structural features, we survey this data set using existing riboswitch models. We identify 22 classes of riboswitches with vitamin cofactors making up the majority of riboswitch-associated pathways. Our finding is reproducible in other representative databases from the oral as well as the marine microbiomes, underscoring the importance of thiamine pyrophosphate, cobalamin, and flavin mononucleotide in gene regulation. Interestingly, riboswitches do not vary significantly across microbiome representatives from around the world despite major taxonomic differences; this suggests an underlying conservation. Further studies elucidating the role of bacterial riboswitches in the host metabolome are needed to illuminate the consequences of our finding.

Predicting Cotranscriptional Folding Kinetics For Riboswitch

On the basis of a helix-based transition rate model, we developed a new method for sampling cotranscriptional RNA conformational ensemble and the prediction of cotranscriptional folding kinetics. Applications to E. coli. SRP RNA and pbuE riboswitch indicate that the model may provide reliable predictions for the cotranscriptional folding pathways and population kinetics. For E. coli. SRP RNA, the predicted population kinetics and the folding pathway are consistent with the SHAPE profiles in the recent cotranscriptional SHAPE-seq experiments. For the pbuE riboswitch, the model predicts the transcriptional termination efficiency as a function of the force. The theoretical results show (a) a force-induced transition from the aptamer (antiterminator) to the terminator structure and (b) the different folding pathways for the riboswitch with and without the ligand (adenine). More specifically, without adenine, the aptamer structure emerges as a short-lived kinetic transient state instead of a thermodynamically stable intermediate state. Furthermore, from the predicted extension-time curves, the model identifies a series of conformational switches in the pulling process, where the predicted relative residence times for the different structures are in accordance with the experimental data. The model may provide a new tool for quantitative predictions of cotranscriptional folding kinetics, and results can offer useful insights into cotranscriptional folding-related RNA functions such as regulation of gene expression with riboswitches.

Measuring riboswitch activity in vitro and in artificial cells with purified transcription-translation machinery

We present a simple method to measure the real-time activity of riboswitches with purified components in vitro and inside of artificial cells. Typically, riboswitch activity is measured in vivo by exploiting β-galactosidase encoding constructs with a putative riboswitch sequence in the untranslated region. Additional in vitro characterization often makes use of in-line probing to explore conformational changes induced by ligand binding to the mRNA or analyses of transcript lengths in the presence and absence of ligand. However, riboswitches ultimately control protein levels and often times require accessory factors. Therefore, an in vitro system capable of monitoring protein production with fully defined components that can be supplemented with accessory factors would greatly aid riboswitch studies. Herein we present a system that is amenable to such analyses. Further, since the described system can be easily reconstituted within compartments to build artificial, cellular mimics with sensing capability, protocols are provided for building sense-response systems within water-in-oil emulsion compartments and lipid vesicles. Only standard laboratory equipment and commercially available material are exploited for the described assays, including DNA, purified transcription-translation machinery, i.e., the PURE system, and a spectrofluorometer.

Dynamic energy landscapes of riboswitches help interpret conformational rearrangements and function

Riboswitches are RNAs that modulate gene expression by ligand-induced conformational changes. However, the way in which sequence dictates alternative folding pathways of gene regulation remains unclear. In this study, we compute energy landscapes, which describe the accessible secondary structures for a range of sequence lengths, to analyze the transcriptional process as a given sequence elongates to full length. In line with experimental evidence, we find that most riboswitch landscapes can be characterized by three broad classes as a function of sequence length in terms of the distribution and barrier type of the conformational clusters: low-barrier landscape with an ensemble of different conformations in equilibrium before encountering a substrate; barrier-free landscape in which a direct, dominant “downhill” pathway to the minimum free energy structure is apparent; and a barrier-dominated landscape with two isolated conformational states, each associated with a different biological function. Sharing concepts with the “new view” of protein folding energy landscapes, we term the three sequence ranges above as the sensing, downhill folding, and functional windows, respectively. We find that these energy landscape patterns are conserved in various riboswitch classes, though the order of the windows may vary. In fact, the order of the three windows suggests either kinetic or thermodynamic control of ligand binding. These findings help understand riboswitch structure/function relationships and open new avenues to riboswitch design.

Riboswitches are RNAs that modulate gene expression by ligand-induced conformational changes. However, the way that sequence dictates alternative folding pathways of gene regulation remains unclear. In this study, we mimic transcription by computing energy landscapes which describe accessible secondary structures for a range of sequence lengths. Consistent with experimental evidence, we find that most riboswitch landscapes can be characterized by three broad classes as a function of sequence length in terms of the distribution and barrier type of the conformational clusters: Low-barrier landscape with an ensemble of conformations in equilibrium before encountering a substrate; barrier-free landscape with a dominant “downhill” pathway to the minimum free energy structure; and barrier-dominated landscape with two isolated conformational states with different functions. Sharing concepts with the “new view” of protein folding energy landscapes, we term the three sequence ranges above as the sensing, downhill folding, and functional windows, respectively. We find that these energy landscape patterns are conserved between riboswitch classes, though the order of the windows may vary. In fact, the order of the three windows suggests either kinetic or thermodynamic control of ligand binding. These findings help understand riboswitch structure/function relationships and open new avenues to riboswitch design.

Computational approaches to RNA structure prediction, analysis, and design

RNA molecules are important cellular components involved in many fundamental biological processes. Understanding the mechanisms behind their functions requires RNA tertiary structure knowledge. Although modeling approaches for the study of RNA structures and dynamics lag behind efforts in protein folding, much progress has been achieved in the past two years. Here, we review recent advances in RNA folding algorithms, RNA tertiary motif discovery, applications of graph theory approaches to RNA structure and function, and in silico generation of RNA sequence pools for aptamer design. Advances within each area can be combined to impact many problems in RNA structure and function.