Determining structures of individual RNA conformers using atomic force microscopy images and deep neural networks.

The vast percentage of the human genome is transcribed into RNA, many of which contain various structural elements and are important for functions. RNA molecules are conformationally heterogeneous and functionally dyanmics1, even when they are structured and well-folded2, which limit the applicability of methods such as NMR, crystallography, or cryo-EM. Moreover, because of the lack of a large structure RNA database, and no clear correlation between sequence and structure, approaches like AlphaFold3 for protein structure prediction, do not apply to RNA. Therefore determining the structures of heterogeneous RNA is an unmet challenge. Here we report a novel method of determining RNA three-dimensional topological structures using deep neural networks and atomic force microscopy (AFM) images of individual RNA molecules in solution. Owing to the high signal-to-noise ratio of AFM, our method is ideal for capturing structures of individual conformationally heterogeneous RNA. We show that our method can determine 3D topological structures of any large folded RNA conformers, from ~ 200 to ~ 420 residues, the size range that most functional RNA structures or structural elements fall into. Thus our method addresses one of the major challenges in frontier RNA structural biology and may impact our fundamental understanding of RNA structure.

Transcription factor expression repertoire basis for epigenetic and transcriptional subtypes of colorectal cancers.

Colorectal cancers (CRCs) form a heterogenous group classified into epigenetic and transcriptional subtypes. The basis for the epigenetic subtypes, exemplified by varying degrees of promoter DNA hypermethylation, and its relation to the transcriptional subtypes is not well understood. We link cancer-specific transcription factor (TF) expression alterations to methylation alterations near TF-binding sites at promoter and enhancer regions in CRCs and their premalignant precursor lesions to provide mechanistic insights into the origins and evolution of the CRC molecular subtypes. A gradient of TF expression changes forms a basis for the subtypes of abnormal DNA methylation, termed CpG-island promoter DNA methylation phenotypes (CIMPs), in CRCs and other cancers. CIMP is tightly correlated with cancer-specific hypermethylation at enhancers, which we term CpG-enhancer methylation phenotype (CEMP). Coordinated promoter and enhancer methylation appears to be driven by downregulation of TFs with common binding sites at the hypermethylated enhancers and promoters. The altered expression of TFs related to hypermethylator subtypes occurs early during CRC development, detectable in premalignant adenomas. TF-based profiling further identifies patients with worse overall survival. Importantly, altered expression of these TFs discriminates the transcriptome-based consensus molecular subtypes (CMS), thus providing a common basis for CIMP and CMS subtypes.

Synchronous RNA conformational changes trigger ordered phase transitions in crystals.

Time-resolved studies of biomacromolecular crystals have been limited to systems involving only minute conformational changes within the same lattice. Ligand-induced changes greater than several angstroms, however, are likely to result in solid-solid phase transitions, which require a detailed understanding of the mechanistic interplay between conformational and lattice transitions. Here we report the synchronous behavior of the adenine riboswitch aptamer RNA in crystal during ligand-triggered isothermal phase transitions. Direct visualization using polarized video microscopy and atomic force microscopy shows that the RNA molecules undergo cooperative rearrangements that maintain lattice order, whose cell parameters change distinctly as a function of time. The bulk lattice order throughout the transition is further supported by time-resolved diffraction data from crystals using an X-ray free electron laser. The synchronous molecular rearrangements in crystal provide the physical basis for studying large conformational changes using time-resolved crystallography and micro/nanocrystals.

Aging-like Spontaneous Epigenetic Silencing Facilitates Wnt Activation, Stemness, and BrafV600E-Induced Tumorigenesis.

We addressed the precursor role of aging-like spontaneous promoter DNA hypermethylation in initiating tumorigenesis. Using mouse colon-derived organoids, we show that promoter hypermethylation spontaneously arises in cells mimicking the human aging-like phenotype. The silenced genes activate the Wnt pathway, causing a stem-like state and differentiation defects. These changes render aged organoids profoundly more sensitive than young ones to transformation by BrafV600E, producing the typical human proximal BRAFV600E-driven colon adenocarcinomas characterized by extensive, abnormal gene-promoter CpG-island methylation, or the methylator phenotype (CIMP). Conversely, CRISPR-mediated simultaneous inactivation of a panel of the silenced genes markedly sensitizes to BrafV600E-induced transformation. Our studies tightly link aging-like epigenetic abnormalities to intestinal cell fate changes and predisposition to oncogene-driven colon tumorigenesis.

Topological Structure Determination of RNA Using Small-Angle X-Ray Scattering.

Knowledge of RNA three-dimensional topological structures provides important insight into the relationship between RNA structural components and function. It is often likely that near-complete sets of biochemical and biophysical data containing structural restraints are not available, but one still wants to obtain knowledge about approximate topological folding of RNA. In this regard, general methods for determining such topological structures with minimum readily available restraints are lacking. Naked RNAs are difficult to crystallize and NMR spectroscopy is generally limited to small RNA fragments. By nature, sequence determines structure and all interactions that drive folding are self-contained within sequence. Nevertheless, there is little apparent correlation between primary sequences and three-dimensional folding unless supplemented with experimental or phylogenetic data. Thus, there is an acute need for a robust high-throughput method that can rapidly determine topological structures of RNAs guided by some experimental data. We present here a novel method (RS3D) that can assimilate the RNA secondary structure information, small-angle X-ray scattering data, and any readily available tertiary contact information to determine the topological fold of RNA. Conformations are firstly sampled at glob level where each glob represents a nucleotide. Best-ranked glob models can be further refined against solvent accessibility data, if available, and then converted to explicit all-atom coordinates for refinement against SAXS data using the Xplor-NIH program. RS3D is widely applicable to a variety of RNA folding architectures currently present in the structure database. Furthermore, we demonstrate applicability and feasibility of the program to derive low-resolution topological structures of relatively large multi-domain RNAs.

Real-time crystallographic studies of the adenine riboswitch using an X-ray free-electron laser.

Structures of the four reaction states of the adenine riboswitch aptamer domain, including a transient intermediate state were solved by serial femtosecond crystallography. The structures not only demonstrate the use of X-ray free-electron lasers for RNA crystallography but have also proven that transient states can be determined in real time by mix-and-inject crystallography. These results illustrate the structural basis for the ligand-induced conformational changes associated with the molecular 'switch'.

Cooperative structural transitions in amyloid-like aggregation.

Amyloid fibril aggregation is associated with several horrific diseases such as Alzheimer's, Creutzfeld-Jacob, diabetes, Parkinson's, and others. Although proteins that undergo aggregation vary widely in their primary structure, they all produce a cross-ß motif with the proteins in ß-strand conformations perpendicular to the fibril axis. The process of amyloid aggregation involves forming myriad different metastable intermediate aggregates. To better understand the molecular basis of the protein structural transitions and aggregation, we report on molecular dynamics (MD) computational studies on the formation of amyloid protofibrillar structures in the small model protein ccß, which undergoes many of the structural transitions of the larger, naturally occurring amyloid forming proteins. Two different structural transition processes involving hydrogen bonds are observed for aggregation into fibrils: the breaking of intrachain hydrogen bonds to allow ß-hairpin proteins to straighten, and the subsequent formation of interchain H-bonds during aggregation into amyloid fibrils. For our MD simulations, we found that the temperature dependence of these two different structural transition processes results in the existence of a temperature window that the ccß protein experiences during the process of forming protofibrillar structures. This temperature dependence allows us to investigate the dynamics on a molecular level. We report on the thermodynamics and cooperativity of the transformations. The structural transitions that occurred in a specific temperature window for ccß in our investigations may also occur in other amyloid forming proteins but with biochemical parameters controlling the dynamics rather than temperature.

Modeling RNA topological structures using small angle X-ray scattering.

Detailed understanding of the structure and function relationship of RNA requires knowledge about RNA three-dimensional (3D) topological folding. However, there are very few unique RNA entries in structure databases. This is due to challenges in determining 3D structures of RNA using conventional methods, such as X-ray crystallography and NMR spectroscopy, despite significant advances in both of these technologies. Computational methods have come a long way in accurately predicting the 3D structures of small (<50nt) RNAs to within a few angstroms compared to their native folds. However, lack of an apparent correlation between an RNA primary sequence and its 3D fold ultimately limits the success of purely computational approaches. In this context, small angle X-ray scattering (SAXS) serves as a valuable tool by providing global shape information of RNA. In this article, we review the progress in determining RNA 3D topological structures, including a new method that combines secondary structural information and SAXS data to sample conformations generated through hierarchical moves of commonly observed RNA motifs.

Small-angle X-ray scattering: a bridge between RNA secondary structures and three-dimensional topological structures.

Whereas the structures of small to medium-sized well folded RNA molecules often can be determined by either X-ray crystallography or NMR spectroscopy, obtaining structural information for large RNAs using experimental, computational, or combined approaches remains a major interest and challenge. RNA is very sensitive to small-angle X-ray scattering (SAXS) due to high electron density along phosphate-sugar backbones, whose scattering contribution dominates SAXS intensity. For this reason, SAXS is particularly useful in obtaining global RNA structural information that outlines backbone topologies and, therefore, molecular envelopes. Such information is extremely valuable in bridging the gap between the secondary structures and three-dimensional topological structures of RNA molecules, particularly those that have proven difficult to study using other structure-determination methods. Here we review published results of RNA topological structures derived from SAXS data or in combination with other experimental data, as well as details on RNA sample preparation for SAXS experiments.

Molecular dynamics investigations of the α-helix to ß-barrel conformational transformation in the RfaH transcription factor.

The C-terminal domain (CTD) of the transcription antiterminator RfaH folds to an α-helix bundle when it interacts with its N-terminal domain (NTD) but it undergoes an all-α to all-ß conformational transformation when it does not interact with the NTD. The RfaH-CTD in the all-α topology is involved in regulating transcription whereas in the all-ß topology it is involved in stimulating translation by recruiting a ribosome to an mRNA. Because the conformational transformation in RfaH-CTD gives it a different function, it is labeled as a transformer protein, a class that may eventually include many other functional proteins. The structure and function of RfaH is of interest for its own sake, as well as for the value it may serve as a model system for investigating structural transformations in general. We used replica exchange molecular dynamics simulations with implicit solvent to investigate the α-helix to ß-structure transformation of RfaH-CTD, followed by structural relaxation with detailed all atom simulations for the best replica. The importance of interfacial interactions between the two domains of RfaH is highlighted by the compromised structural integrity of the helical form of the CTD in the absence NTD. Calculations of free-energy landscape and transfer entropy elucidate the details of the RfaH-CTD transformation process.

Exploring the diffusion of molecular oxygen in the red fluorescent protein mCherry using explicit oxygen molecular dynamics simulations.

The development of fluorescent proteins (FPs) has revolutionized cell biology research. The monomeric variants of red fluorescent proteins (RFPs), known as mFruits, have been especially valuable for tagging and tracking cellular processes in vivo. Determining oxygen diffusion pathways in FPs can be important for improving photostability and for understanding maturation of the chromophore. We use molecular dynamics (MD) calculations to investigate the diffusion of molecular oxygen in one of the most useful monomeric RFPs, mCherry. We describe a pathway that allows oxygen molecules to enter from the solvent and travel through the protein barrel to the chromophore. We calculate the free-energy of an oxygen molecule at points along the path. The pathway contains several oxygen hosting pockets, which are identified by the amino acid residues that form the pocket. We also investigate an RFP variant known to be significantly less photostable than mCherry and find much easier oxygen access in this variant. The results provide a better understanding of the mechanism of molecular oxygen access into the fully folded mCherry protein barrel and provide insight into the photobleaching process in these proteins.

Structural propensities and entropy effects in peptide helix-coil transitions.

The helix-coil transition in peptides is a critical structural transition leading to functioning proteins. Peptide chains have a large number of possible configurations that must be accounted for in statistical mechanical investigations. Using hydrogen bond and local helix propensity interaction terms, we develop a method for obtaining and incorporating the degeneracy factor that allows the exact calculation of the partition function for a peptide as a function of chain length. The partition function is used in calculations for engineered peptide chains of various lengths that allow comparison with a variety of different types of experimentally measured quantities, such as fraction of helicity as a function of both temperature and chain length, heat capacity, and denaturation studies. When experimental sensitivity in helicity measurements is properly accounted for in the calculations, the calculated curves fit well with the experimental curves. We determine values of interaction energies for comparison with known biochemical interactions, as well as quantify the difference in the number of configurations available to an amino acid in a random coil configuration compared to a helical configuration.

Lattice model simulations of the effects of the position of a peptide trigger segment on helix folding and dimerization.

The folding and dimerization of proteins is greatly facilitated by the presence of a trigger site, a segment of amino acids that has a higher propensity for forming α-helix structure as compared to the rest of the chain. In addition to the helical propensity of each chain, dimerization can also be facilitated by interhelical interactions such as saltbridges, and interfacial contacts of different strengths. In this work, we are interested in understanding the interplay of these interactions in a model peptide system. We investigate how these different interactions influence the kinetics of dimer formation and the stability of the fully formed dimer. We use lattice model computer simulations to investigate how the effectiveness of the trigger segment and its saltbridges depends on the location along the protein primary sequence. For different positions of the trigger segment, heat capacity and free energy of unfolded and folded configurations are calculated to study the thermodynamics of folding and dimerization. The kinetics of the process is investigated by calculating characteristic folding times. The thermodynamic and kinetic data from the simulations combine to show that the dimerization process of the model system is faster when the segment with high helical propensity is located near either end of the peptide, as compared to the middle of the chain. The dependence of the stability of the dimer on the trigger segment's position is also studied. The stability can play a role in the ability of the dimer to perform a biological function that involves partial unzipping. The results on folding and dimer stability provide important insights for designing proteins that involve trigger sites.

Free-energy landscapes and thermodynamic parameters of complex molecules from nonequilibrium simulation trajectories.

Thermodynamic parameters such as free energies and heat capacities are important quantities for understanding processes involving structural transitions in complex molecules such as proteins. Computational investigations provide simulated data that can be used for calculating thermodynamic parameters. However, calculations give accurate results only if the simulations sample all of configuration space with the appropriate temperature-dependent Boltzmann equilibrium probabilities. For many systems, truly comprehensive sampling of configuration space is not computationally feasible. We present an approximation technique for the calculations that will give accurate values for thermodynamic parameters when the data is incomplete. Our work is applicable to systems in which there are two distinct, important regions of configuration space that must be sampled. Importantly, the results are also valid when the system is more complex than two-state systems. Transition pathways that involve intermediate configurations between two stable regions are allowed in this treatment, and therefore the results are valid for multistate systems.