High-throughput biochemistry in RNA sequence space: predicting structure and function

Structure-Based Prediction of lncRNA-Protein Interactions by Deep Learning

The interactions between long noncoding RNA (lncRNA) and protein play crucial roles in various biological processes. Computational methods are essential for predicting lncRNA-protein interactions and deciphering their mechanisms. In this chapter, we aim to introduce the fundamental framework for predicting lncRNA-protein interactions based on three-dimensional structure information. With the increasing availability of lncRNA and protein molecular tertiary structures, the feasibility of using deep learning methods for automatic representation and learning has become evident. This chapter outlines the key steps in predicting lncRNA-protein interactions using deep learning, including three common non-Euclidean data representations for lncRNA and proteins, as well as neural networks tailored to these specific data characteristics. We also highlight the advantages and challenges of structure-based prediction of lncRNA-protein interactions with geometric deep learning methods.

m6A-modified cenRNA stabilizes CENPA to ensure centromere integrity in cancer cells

m6A modification is best known for its critical role in controlling multiple post-transcriptional processes of the mRNAs. Here, we discovered elevated levels of m6A modification on centromeric RNA (cenRNA) in cancerous cells compared with non-cancerous cells. We then identified CENPA, an H3 variant, as an m6A reader of cenRNA. CENPA is localized at centromeres and is essential in preserving centromere integrity and function during mitosis. The m6A-modified cenRNA stabilizes centromeric localization of CENPA in cancer cells during the S phase of the cell cycle. Mutations of CENPA at the Leu61 and the Arg63 or removal of cenRNA m6A modification lead to loss of centromere-bound CENPA during S phase. This in turn results in compromised centromere integrity and abnormal chromosome separation and hinders cancer cell proliferation and tumor growth. Our findings unveil an m6A reading mechanism by CENPA that epigenetically governs centromere integrity in cancer cells, providing potential targets for cancer therapy.

Massively parallel analysis of single-molecule dynamics on next-generation sequencing chips

Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe multiplexed single-molecule characterization at the library scale (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profiled the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding-rewinding dynamics. The ability to explore a large sequence space for Cas9 allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes.

Single-molecule structural and kinetic studies across sequence space

At the core of molecular biology lies the intricate interplay between sequence, structure, and function. Single-molecule techniques provide in-depth dynamic insights into structure and function, but laborious assays impede functional screening of large sequence libraries. We introduce high-throughput Single-molecule Parallel Analysis for Rapid eXploration of Sequence space (SPARXS), integrating single-molecule fluorescence with next-generation sequencing. We applied SPARXS to study the sequence-dependent kinetics of the Holliday junction, a critical intermediate in homologous recombination. By examining the dynamics of millions of Holliday junctions, covering thousands of distinct sequences, we demonstrated the ability of SPARXS to uncover sequence patterns, evaluate sequence motifs, and construct thermodynamic models. SPARXS emerges as a versatile tool for untangling the mechanisms that underlie sequence-specific processes at the molecular scale.

Chemical Synthesis of Modified RNA

Ribonucleic acids (RNAs) play a vital role in living organisms. Many of their cellular functions depend critically on chemical modification. Methods to modify RNA in a controlled manner-both in vitro and in vivo-are thus essential to evaluate and understand RNA biology at the molecular and mechanistic levels. The diversity of modifications, combined with the size and uniformity of RNA (made up of only 4 nucleotides) makes its site-specific modification a challenging task that needs to be addressed by complementary approaches. One such approach is solid-phase RNA synthesis. We discuss recent developments in this field, starting with new protection concepts in the ongoing effort to overcome current size limitations. We continue with selected modifications that have posed significant challenges for their incorporation into RNA. These include deazapurine bases required for atomic mutagenesis to elucidate mechanistic aspects of catalytic RNAs, and RNA containing xanthosine, N4-acetylcytidine, 5-hydroxymethylcytidine, 3-methylcytidine, 2'-OCF3, and 2'-N3 ribose modifications. We also discuss the all-chemical synthesis of 5'-capped mRNAs and the enzymatic ligation of chemically synthesized oligoribonucleotides to obtain long RNA with multiple distinct modifications, such as those needed for single-molecule FRET studies. Finally, we highlight promising developments in RNA-catalyzed RNA modification using cofactors that transfer bioorthogonal functionalities.

Exploring the conformational dynamics of the SARS-CoV-2 SL4 hairpin by combining optical tweezers and base analogues

The parasitic nature of the SARS-CoV-2 virus demands selective packaging of its RNA genome (gRNA) from the abundance of other nucleic acids present in infected cells. Despite increasing evidence that stem-loop 4 (SL4) of the gRNA 5' UTR is involved in the initiation of this process by binding the nucleocapsid (N) protein, little is known about its conformational dynamics. Here, we unravel the stability, dynamics and (un)folding pathways of SL4 using optical tweezers and a base analogue, tCO, that provides a local and subtle increase in base stacking without perturbing hydrogen bonding. We find that SL4 (un)folds mainly in a single step or through an intermediate, encompassing nucleotides from the central U bulge to the hairpin loop. Due to an upper-stem CU mismatch, SL4 is prone to misfold, the extent of which can be tuned by incorporating tCO at different positions. Our study contributes to a better understanding of SARS-CoV-2 packaging and the design of drugs targeting SL4. We also highlight the generalizability of using base analogues in optical tweezers experiments for probing intramolecular states and conformational transitions of various nucleic acids at the level of single molecules and with base-pair resolution.

Systematic analysis of cotranscriptional RNA folding using transcription elongation complex display

RNA can fold into structures that mediate diverse cellular functions. Understanding how RNA primary sequence directs the formation of functional structures requires methods that can comprehensively assess how changes in an RNA sequence affect its structure and function. Here we have developed a platform for performing high-throughput cotranscriptional RNA biochemical assays, called Transcription Elongation Complex display (TECdisplay). TECdisplay measures RNA function by fractionating a TEC library based on the activity of cotranscriptionally displayed nascent RNA. In this way, RNA function is measured as the distribution of template DNA molecules between fractions of the transcription reaction. This approach circumvents typical RNA sequencing library preparation steps that can cause technical bias. We used TECdisplay to characterize the transcription antitermination activity of 32,768 variants of the Clostridium beijerinckii pfl ZTP riboswitch designed to perturb steps within its cotranscriptional folding pathway. Our findings establish TECdisplay as an accessible platform for high-throughput RNA biochemical assays.

tRNA renovatio: Rebirth through fragmentation

tRNA function is based on unique structures that enable mRNA decoding using anticodon trinucleotides. These structures interact with specific aminoacyl-tRNA synthetases and ribosomes using 3D shape and sequence signatures. Beyond translation, tRNAs serve as versatile signaling molecules interacting with other RNAs and proteins. Through evolutionary processes, tRNA fragmentation emerges as not merely random degradation but an act of recreation, generating specific shorter molecules called tRNA-derived small RNAs (tsRNAs). These tsRNAs exploit their linear sequences and newly arranged 3D structures for unexpected biological functions, epitomizing the tRNA "renovatio" (from Latin, meaning renewal, renovation, and rebirth). Emerging methods to uncover full tRNA/tsRNA sequences and modifications, combined with techniques to study RNA structures and to integrate AI-powered predictions, will enable comprehensive investigations of tRNA fragmentation products and new interaction potentials in relation to their biological functions. We anticipate that these directions will herald a new era for understanding biological complexity and advancing pharmaceutical engineering.