Abstract

RNA is one of the most important and versatile groups of biomolecules, acting both as a messenger and a catalyst. Understanding RNA dynamics, localization, and expression in living cells is essential for decoding cellular function. Current RNA imaging methods often require cell fixation or extensive genetic modifications and are limited in detecting low abundance RNAs, due to low signal to noise ratio. Here, we present RNA detection through Targeted RNA Activated Phase Separation (TRAPS). TRAPS is a novel, modular method for in vivo RNA detection using catalytically inactive Cas13 fused to GFP-tagged scaffold domains. With TRAPS, fluorescent condensates form upon multivalent binding of the target RNA by Cas13, allowing easy detection and flexible modification. Our system enables real-time detection of endogenous RNAs, advancing the toolbox to detect RNA in lower abundance and shorter lifetime. As a proof-of-concept, we target mCherry mRNA in S. cerevisiae. Coupled with our software SEASTAR (Site-Effect Aware Sequence Targeting & Ranking) for optimal target site selection, TRAPS provides an easily accessible and versatile platform for studying RNA in living cells, a suitable tool for every scientist and future iGEM teams.

Introduction

For the understanding of cellular function, it is crucial to comprehend the dynamics, localization, and expression patterns of RNA molecules within living cells. The roles RNA has in a cell reach far beyond its original discovery as just an intermediate molecule between DNA and protein.

coding RNA

messenger RNA (mRNA)

The earliest discoveries hinting at this were the existence of messenger RNA (mRNA), transcribed from only a small fraction of the full genome and responsible for translation (Brenner et al., 1961; Gros et al., 1961).

non-coding RNA (ncRNA)

Housekeeping ncRNA

Non-coding RNA (ncRNA) such as ribosomal RNA (rRNA) and transfer RNA (tRNA) that are essential for protein synthesis. Or small nuclear RNA (snRNA) and small nucleolar RNA (snoRNA) that are involved in RNA processing.(Zhang et al., 2019)

Regulatory ncRNA

There are also many types of ncRNA that are capable of regulating gene expression, i.e. like long-non-coding RNA(lncRNA) small interfering (siRNA) and microRNA (miRNA) (Fu, 2014; Strobel & Cochrane, 2007).

Unsurprisingly, the versatility of RNA form and function leads RNA to play a crucial role in most cellular processes. Consequently, RNA research has been and will continue to be crucial for a better understanding of biological processes such as development, stress response and more (Muñoz-Velasco et al., o. J.). The scientific impact of RNA is reflected in several Nobel Prizes awarded for landmark discoveries since 1965 1,2:

Example 1

1965: Francois Jacob, Jacques Monod and André Lwoff

for their discoveries concerning genetic control of enzyme and virus synthesis.

Example 2

1968: Robert W. Holley, Har Gobind Khorana and Marshall W. Nirenberg

for their interpretation of the genetic code and its function in protein synthesis

Example 3

2006: Andrew Z. Fire and Craig C. Mello

for their discovery of RNA interference - gene silencing by double-stranded RNA

Example 4

2023: Katalin Karikó and Drew Weissman

for their discoveries concerning nucleoside base modifications that enabled the development of effective mRNA vaccines against COVID-19

Example 3

2024: Victor Ambros and Gary Ruvkun

for the discovery of microRNA and its role in post-transcriptional gene regulation

The latest Nobel Prizes highlight how fundamental RNA research continues to open new avenues in therapeutics, diagnostics, and biotechnology, making RNA one of the most versatile and influential classes of biomolecules today (Barta & Jantsch, 2017; Chatterjee et al., 2023; Zhang et al., 2023).

Background information

There are several established methods to detect and visualize RNA. Each of these methods has its own strengths and limitations.

Reverse-Transcription PCR

Description

The most widely used method for RNA detection is reverse transcription polymerase chain reaction (RT-PCR) (Mackay, 2004). RT-PCR is a two-step process where RNA is first transcribed into complementary DNA (cDNA) using reverse transcriptase. The cDNA is then amplified using PCR with specific primers to detect the presence of the target RNA sequence.

Limitations

Although RT-PCR technique is very sensitive and provides fast results, it requires the cell to be lysed prior to analysis, making RT-PCR unsuitable for real-time expression studies (Afzal, 2020; Sullivan et al., 2023).

Fluorescence in situ hybridization

Description

FISH utilizes fluorescently labelled oligonucleotides that hybridize with the targeted RNA (Singer & Ward, 1982). The presence and location of the target RNA in cells can then be observed using fluorescence microscopy.

Limitations

However, FISH generally requires heavy tissue preparation and fixing cells with formaldehyde (Eltoum et al., 2001), limiting its applicability to study RNA dynamics in vivo.

Molecular Beacons

Description

Molecular beacons (MB) are oligonucleotides with an antisense stem-loop that binds the target RNA. A fluorophore is added to one end of the loop and a quencher on the other end. The stem-loop ensures that the fluorophore and quencher remain in close proximity, suppressing fluorescence. The MB unfolds upon hybridization with the target RNA, separating the quencher and the fluorophore, resulting in a fluorescent signal (Marras, 2002).

Limitations

A limitation of MBs is the transport into the cells by protein carriers, making it prone to false positives due to nucleic acid degradation (Chen et al., 2007).

MS2/MCP

Description

MS2/MCP is a system that utilizes the high-affinity interaction between the MS2 bacteriophage coat protein (MCP) and its RNA binding site (MBS) (Bertrand et al., 1998). The MBS is inserted into the RNA of interest, which is then bound by MCP fused to a fluorescent protein, allowing visualization of the RNA.

Limitations

A limitation of the MS2/MCP system is the need for genetic modification of the target RNA to include MBS sequences, which requires heavy engineering and can potentially alter the RNA's natural function and localization (Fusco et al., 2003).

Pumby

Description

Pumilio-based assembly (Pumby) modules are single-nucleotide RNA-binding pockets which can be used to build sequence-specific RNA-binding proteins. The pumbys were first described by Adamala et al. (2016) and are derived from the human Pumilio homology domain (PumHD). The PumHD is a domain part of many Puf proteins, a family of RNA-binding proteins conserved across many eukaryotic species (Zamore et. al., 1997). These domains usually consist of eight RNA-binding pockets and therefore bind an 8-nt RNA sequence (Wang et al., 2002).

PumHD schematic
Figure 1: Crystal structure of a RNA-bound PumHD. RNA is depicted in cyan, PumHD in green, and a single RNA binding pocket in magenta (Wang et al., 2002).

Adamala et al. described how to engineer the pocket with the highest affinity to bind to the four different RNA nucleotides (A, U, C, G). In addition, they showed it was possible to create functional RNA-binding proteins, Pumbys, of variable length (4-18 pockets) by concatenating this high affinity pocket, and that longer constructs can target larger RNA sequences.

Limitations

Pumbys are limited to use cases for relatively short RNA target sequences and for investigating a specific RNA sequence. The highly repetitive sequence, especially for longer target sequences, makes it difficult to synthesize the DNA sequence. Furthermore, each target sequence requires a different Pumby, which is impractical for high-throughput RNA sequence investigations.

Catalytic inactive dCas13

Description

Catalytically inactive Cas13 (dCas13) is a RNA-targeting CRISPR effector that can be programmed with guide RNAs to bind specific RNA sequences (Abudayyeh et al., 2017). By fusing dCas13 to a fluorescent protein, it can be used to visualize endogenous RNAs in living cells.

Limitations

Optimal performance is achieved at higher RNA concentrations, since limited target availability produces only minor fluorescence and a poor signal-to-noise ratio (SNR).

Liquid-Liquid Phase Seperation

Liquid-liquid phase separation (LLPS) of biomolecules, like proteins and nuclear acid polymers leads to the formation of at least two coexisting phases with different compositions, usually appearing as droplets in a larger phase, and are used for a diverse set of cellular functions (Banani et al., 2017). The spontaneous mixing in multicomponent systems is driven by entropy, during phase separation an enthalpic contribution to the free energy, originating from molecular interactions can win over, causing the formation of separate phases. Biological condensate systems tend to use multivalent scaffold molecules, as having many binding sites lowers the critical concentration and increases the critical temperature, allowing bio-molecules to phase separate easier (Banani et al., 2017). Mechanistically having multiple binding domains causes cooperative binding dynamics and local clustering of the target RNA and the probes, facilitating stronger interactions among each other at lower concentrations. It should also be noted that very strong specific interactions are commonly related to the assembly of networks, while weaker less specific interactions in greater numbers (high valency macromolecules and intrinsically disorder domains) are suggested to play a major role in condensates maintaining their liquid like properties (Banani et al., 2017).

Our Solution TRAPS

Therefore we propose a new condensate-based RNA sensory platform. It builds on a synthetic condensate engineered by Heidenreich et al. (2020). Crucial for controlling condensation in this system is the toxin-antitoxin interaction with intermediate affinity. We adapted their design to our TRAPS system. Once again we used the tetramerization domain as scaffold but this time we connected the RNA Binding Protein, the dCas13 with the toxin-antitoxin interaction. The toxin E9 is fused to the tetramerization domain and green fluorescent protein GFP, forming a fluorescent tetramer. The dCas13 is fused to the antitoxin Im2, connecting it to the tetrameric unit. Since the toxin-antitoxin interaction continuously bind and unbind, they drive LLPS. We are introducing multiple gRNAs to again target different sites of the RNA. If the RNA of interest is present, it will bind to the RBP and start connecting different TRAPS units. This process forms a network , leading to concentration of GFP fluorescence. Furthermore, including these toxin-antitoxin binding dynamics into the network also facilitates liquid-liquid phase separation. As mentioned we want to use these effects to sense the presence of the target RNA. The signal will be increased and clear because of the condensate as readout. TRAPS presents an exciting RNA binding platform not only because of the flexibility due the gRNAs but also allows to study dynamics of the cellular processes related to RNA.

Our Software SEASTAR

Finding the best binding sites on the target RNA can be difficult, due to possible offtargets in the transcriptome and the secondary structure of the RNA itself. That's why our team developed a software tool called SEASTAR (Site-Effect Aware Sequence TArgeting & Ranking) that allows you to identify certain sequences in the RNA of interest you can address to get the best result for your study. This software compares sequence data of a target RNA and a transcriptome to evaluate which binding sites on the target (= queries) have the lowest probability for undesirable binding interactions with the transcriptome (reference library). It is designed with sequence based probes (e.g. sgRNA of Cas13 or Pumilio RBPs) in mind, allowing to rank the specificity (= dissimilarity with the reference library) of single queries, or query groups (when using multiple probes simultaneously to minimize overlapping side effects).

Degradation process GIF
Figure 5: The RNA is split into all possible query sequences and then compared to the transcriptome. A score is calculated for each match and subsequently ranked. The lower the score, the lower the probability of binding elsewhere, indicating a good, specific binding site.

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