An intrinsically disordered region mediates RNA-binding selectivity and cellular activities of LARP6

Domain: chemistry
Published: 2026-02-19
Editorial outcome: major_revision

Abstract
Intrinsically disordered regions (IDRs) are prevalent in RNA-binding proteins (RBPs), yet their roles in RNA interactions remain poorly defined. We examined RNA-binding regulation by structured and disordered regions of LARP6, an RBP with a diverse RNA-binding repertoire. Mass spectrometry-based RNA interaction mapping in living cells identified direct LARP6–RNA contacts within the structured La-module and its flanking IDRs. Mutagenesis and individual-nucleotide resolution UV-crosslinking and immunoprecipitation (iCLIP) revealed the La-module, but not the IDRs, as essential for LARP6 RNA binding. Deletion of the N-terminal IDR broadened LARP6 RNA footprints, uncovering a role in RNA-binding selectivity. This is achieved through a composite mechanism of restricting the conformational flexibility of the adjacent La-module, forming auxiliary contacts with the RNA, and modulating RNA access for binding. The IDR-mediated RNA-binding selectivity is critical for LARP6-mediated promotion of cancer cell viability and invasion. Our findings uncover a previously unrecognised critical function for IDRs in promoting selective RBP–RNA recognition, by affecting the binding specificity of their adjacent structured domains.

Introduction
RNA-binding proteins (RBPs) control all aspects of RNA regulation and are thought to engage with and regulate specific sets of transcripts in function1. Conventional RBPs have been traditionally defined by the context-specific manners, creating highly diverse yet specific post-presence of one or more structurally conserved RNA-binding domains transcriptional regulatory networks4,5. In addition to containing well-(RBDs), which mediate interactions with their target RNA molecules defined RBDs, most conventional RBPs also harbour intrinsically dis-through sequence- or structure-based RNA recognition2. The human ordered regions (IDRs) that are characterised by an ensemble of genome encodes hundreds of such RBPs, which can be grouped into interconverting conformations. Despite lacking defined structure, diverse super-families, characterised by the presence of specific sets of IDRs can play critical functions in various RBPs2. Indeed, the majority of RBDs3. Through combinatorial action of multiple RBDs, RBPs are germ-line mutations in RBPs that are associated with human Mendelian genetic disorders occur within the IDR-coding regions1. Interestingly, unbiased RNA–protein interaction site-mapping studies have revealed that many IDRs with diverse biochemical characteristics can directly engage with RNA in living cells6,7. However, the exact mechanisms through which these ‘non-conventional’ disordered RNA binding sites interact with RNA, and how they combine with tethered RBDs to shape the RNA-binding properties of RBPs remain largely uncharacterised.

The La-related protein 6 (LARP6) is an evolutionarily conserved RBP found in all multicellular eukaryotes. LARP6 is a member of the LARP superfamily, a group of ancient eukaryotic RBPs involved in various aspects of post-transcriptional gene regulation, including the synthesis, processing, maturation, localisation, stability, and translation of diverse RNA targets8. Similar to all LARPs, LARP6 is characterised by the presence of a conserved bipartite RBD, the La-module, which consists of a La-motif and an RNA Recognition Motif-1 (RRM1), connected by a short linker9. This La-module is N- and C-terminally flanked by IDRs. In addition, LARP6 possesses a SUZ-C motif in its C-terminal region, a structurally uncharacterised short motif that is known to mediate protein–protein interactions8. Functionally, LARP6 has been shown to control diverse cellular processes, including type-I collagen synthesis9,10, myogenesis11–13, oocyte development14, neural tube development15, as well as pollen tube guidance in plants16. Recently, we identified a role for LARP6 in regulating mRNA localisation, cell proliferation, and invasion, in highly invasive breast carcinoma cells that have undergone epithelial–mesenchymal transition (EMT)17. Transcriptome-wide iCLIP analysis revealed over five thousand mRNAs, spanning diverse functional gene categories, as direct binding targets of LARP6, highlighting a capability to engage with a broad spectrum of RNA targets17. Consistent with these results, an RNA-based high-throughput systematic evolution of ligands by exponential enrichment (HTR-SELEX) study demonstrated that LARP6 has a highly complex RNA-binding repertoire, capable of interacting with various linear and structured motifs18. The underlying mechanism by which LARP6 can selectively recognise such a diverse array of RNA targets remains unclear.

Here, we devised an unbiased mass spectrometry approach to map the regions of LARP6 that directly interact with RNA in living cells. Our results reveal that, in addition to the structured La-module, regions within the N- and C-terminal IDRs of LARP6 can directly contact the RNA. Using a doxycycline-inducible system to express full-length (FL) or various deletion mutants of LARP6, coupled with transcriptome-wide iCLIP analysis, we demonstrated that the La-module is essential for the RNA-binding activity of LARP6 in living cells. Removing the IDRs did not abrogate LARP6’s ability to interact with RNA. Instead, deletion of the N-terminal IDR broadened LARP6’s interaction footprints across the transcriptome, indicating that this IDR modulates the activity of the adjacent La-module by promoting selectivity in RNA binding. In vitro biophysical assessments corroborated our observations in living cells, revealing that the N-terminal IDR enhances RNA-binding selectivity via a composite mechanism that restricts the conformational dynamics of the La-module, forms additional direct contacts with the RNA, and modulates RNA access to the La-module in a competitive manner. Importantly, deletion of the N-terminal IDR compromised the function of LARP6 in promoting the viability and invasiveness of glioblastoma cells, suggesting that the IDR-mediated RNA-binding selectivity is important for LARP6 function. Together, our findings uncover a previously unknown yet critical mechanism for IDRs in promoting selective RNA–RBP interactions of their adjacent structured domains.

Results
LARP6 interacts with RNA through both ordered and disordered regions
To better understand the complexities of LARP6 RNA-binding activity, we aimed to define its regions of contact with RNA in living cells in an unbiased manner. For this purpose, we developed a mass spectrometry-based approach termed IP-OOPS (Immunoprecipitation coupled with Orthogonal Organic Phase Separation) (Fig. 1a). This approach combines the isolation of UV-C crosslinked RNA–protein adducts via OOPS19, with the ability to map protein regions that are attached to RNA by sequential Arg-C and trypsin digestions, as pioneered in the RBDmap method6. Briefly, GFP-trap beads were used to purify LARP6–RNA complexes from UV-crosslinked MDA-MB231 cells that stably expressed GFP-LARP617 (Supplementary Fig. 1a). The RNA-crosslinked LARP6 was then isolated using an initial OOPS, before partial digestion with Arg-C, which generated smaller segments, with or without RNA adducts. The RNA-bound segments were further purified from the unbound segments via a second OOPS, followed by trypsin digestion, releasing MS-detectable peptides that were adjacent to a crosslinked region (Fig. 1a). The crosslinked peptides themselves are undetectable in this approach, due to the addition of RNA mass. However, through identification of their adjacent peptides, the likely sites of crosslinking can be postulated as either N- or C-terminal tryptic regions flanking the identified peptides.

Using IP-OOPS, we identified three RNA-bound regions within LARP6 (Fig. 1b, c). These included a known RNA-binding area within the La-motif, as well as two previously unknown RNA-binding areas in the N- and C-terminal regions of the protein (Fig. 1b, c). As control, analysis of the non-crosslinked LARP6 from the organic phase revealed 21 peptides that were distributed across the full length of protein, and covering over 51% of the LARP6 sequence (Supplementary Fig. 1b), suggesting good coverage and a near uniform observability of different protein regions in our experiments. The C-terminal flanking candidate RNA-binding residues in the La-motif contains phenylalanine 135, one of six highly conserved residues in the RNA-binding pocket of LARP6, and shown by mutagenesis to be essential for RNA association9, providing further confidence in our methodology. The RNA-binding area in the C-terminal region (CTR) of the protein is adjacent to the SUZ-C motif, while the RNA-binding area in the N-terminal region (NTR) precedes the La-module (Fig. 1b, c). Computational prediction of disorder using IUPred2A20 suggested that both the NTR and CTR are likely intrinsically disordered (Fig. 1d). These results reveal that in addition to the folded La-module, LARP6 contains two previously unknown RNA-binding regions in its N- and C-terminal parts, which are likely to be IDRs.

iCLIP analysis reveals the La-module as essential for LARP6 binding to RNA
Next, we set out to study the RNA targets of each RNA-binding region of LARP6 in living cells. To reveal the full repertoire of LARP6 binding targets, we chose U-87 MG glioblastoma cells as our cell model, since LARP6 is highly expressed in gliomas (Supplementary Fig. 2a), with U-87 MG cells being among the highest LARP6-expressing established cell lines in wide use (Supplementary Fig. 2b). In fact, LARP6 protein expression levels in U-87 MG cells even surpass those of MDA-MB231 cells, which were previously used as a cell model for LARP6 function, making them a suitable cell model for investigating LARP6 function, particularly in the context of cancer (Supplementary Fig. 2c). To assess the contribution of each region of LARP6 to its RNA-binding activity, we used a doxycycline-inducible system to express FL and various deletion mutants of a myc-tagged LARP6, in a controlled manner (Supplementary Fig. 2d–g). These cells were then subjected to iCLIP analysis using beads conjugated to a monoclonal anti-myc tag antibody21 (Fig. 2a). The iCLIP experiment was performed in triplicate for each LARP6 variant, with parental U-87 MG cells serving as a negative control.

The resulting iCLIP reads, representing precise RNA–protein crosslink sites, were subsequently mapped to the human transcriptome. We then searched for clusters of reads across the transcriptome, which identified peaks that correspond to the likely LARP6 binding sites (Supplementary Data 1). A total of 14,334 peaks were detected for the FL LARP6, most of which were lost upon deletion of the La-module (Fig. 2b), demonstrating its crucial role for the RNA-binding activity of LARP6. In contrast, deletion of the NTR or CTR did not reduce the number of identified peaks; instead, the number of mapped peaks were increased in the ΔNTR and ΔCTR mutants (Fig. 2b, Supplementary Data 2, & Supplementary Data 3). Amongst the identified peaks that were conserved across FL, ΔNTR, and ΔCTR mutants, we detected the well-known binding sites of LARP6 in the 5′ UTR of Collagen-I mRNA10, and the 5′ TOP sequences of various ribosomal protein mRNAs (RP-mRNAs)17 (Fig. 2c). In agreement with our previous study17, mapping of the peaks to the different genomic regions revealed the vast majority to correspond to mRNAs, with the highest binding density occurring in the 3’ UTRs, a binding pattern that was largely unaffected by the NTR or CTR deletions (Fig. 2d).

We then assessed the functional categories of mRNAs that associate with LARP6. Annotation enrichment analysis of LARP6 targets revealed an overrepresentation of transcripts involved in ribosome biogenesis, cell adhesion and migration, intracellular trafficking, and RNA processing, amongst others (Fig. 2e). Importantly, this target repertoire was also unaffected by the NTR or CTR deletions (Fig. 2e). Together, these findings suggest that unlike the La-module, NTR and CTR are dispensable for the bulk of LARP6 RNA-binding activity in cells.

The NTR of LARP6 mediates RNA-binding selectivity in living cells
Next, we examined the underlying principles of RNA target recognition by LARP6. For this purpose, we used Pythia, a neural network-based tool designed to model RBP preferences from CLIP data22. Pythia utilises context-free grammars (CFG) to capture both sequence as well as structural determinants of RNA binding23–25. We used the identified iCLIP peaks as input to train models for FL, as well as ΔNTR and ΔCTR mutants. The data were divided into training (64%), tuning (16%), and validation (20%) subsets with non-overlapping chromosomes among the 3 data splits. High-quality models were successfully trained for each iCLIP dataset, with the ability to predict each LARP6 variant binding sites with high accuracy and precision (Supplementary Fig. 3a-c). We then evaluated the performance of each model for predicting the binding sites of the other variants, as an indicator of divergence in their RNA binding. Area under the precision-recall curve (auPRC) was calculated as the performance metric for each model. The ΔCTR model exhibited an auPRC value of 86%, when applied to its own validation dataset, but this performance was slightly reduced when the model was applied to the FL and ΔNTR datasets, with auPRC values dropping to 78% and 80%, respectively (Fig. 3a). The ΔNTR model exhibited a similar performance, with an auPRC value of 86% when applied to its own validation dataset, but the performance was slightly more compromised when the model was applied to the FL and ΔCTR datasets, with auPRC values dropping to 76% in both cases (Fig. 3b). These results suggest that both CTR and NTR affect target recognition by LARP6, with the impact of the NTR being slightly more prominent.

Next, we assessed the relative contributions of sequence and structure towards RNA recognition by each LARP6 variant. Consistent with previous SELEX findings18, FL LARP6 appeared to leverage on both sequence and structural information for identifying its target sites across the transcriptome, with a slight bias towards structure (Fig. 3c). A similar profile was detected for the ΔCTR mutant, but this balance was significantly disrupted when the NTR was deleted, with the binding activity becoming slightly more sequence-dependent (Fig. 3c). These analyses suggest that the NTR significantly affects how LARP6 recognises its contact sites with RNA, with sequence-based information becoming more prominent in selecting the binding sites.

To gain further insights into the consequences of IDR deletions on LARP6–RNA sites of interactions, we also conducted a metagene analysis of LARP6 crosslinking footprints across its mapped binding sites (i.e. peaks) in the transcriptome. The meta-profile of FL LARP6 crosslinks showed a highly narrow interaction footprint, which remained mostly unchanged upon CTR deletion (Fig. 3d). In contrast, deletion of the NTR led to a clear broadening of the interaction footprints around the main binding site (Fig. 3e), indicating that the NTR is important for enhancing the RNA-binding selectivity of LARP6 in the vicinity of main peaks. Based on these results, we conclude that the observed increase in sequence-dependent RNA-binding bias by Pythia in the ΔNTR mutant is likely reflective of this loss in RNA-binding selectivity, resulting in the emergence of weaker peripheral RNA-protein interactions, which are likely often devoid of any conserved structural RNA features.

Since Pythia analysis revealed a change in the usage of sequence-based information for target recognition by the ΔNTR mutant, we next looked for significant linear sequence motifs that were present in the vicinity of crosslinking sites for FL LARP6 and the ΔNTR mutant. Positionally enriched k-mer analysis (PEKA) was employed to identify significantly enriched linear motifs, using the default package settings26. We applied the motif analysis to both the full iCLIP dataset, as well as only the 3’ UTR regions, where the majority of LARP6 binding sites reside. The FL exhibited a significant enrichment for several relatively complex sequence motifs, an observation in line with the previously published SELEX findings18 (Fig. 3f & 3g). Loss of the NTR, however, transformed this pattern, with simpler pyrimidine-rich linear motifs dominating the binding profile (Fig. 3h & 3i). A minimal difference was observed between the full dataset and the 3’ UTRs, suggesting the observed changes are not restricted to a specific group of binding targets (Fig. 3f–i). Collectively, these results suggest that while the La-module is crucial for mediating RNA–LARP6 interactions, the NTR plays a role in fine-tuning the target selectivity of the La-module.

In vitro binding analysis validates a role for NTR in RNA-binding selectivity
To determine whether the impact of NTR on RNA-binding selectivity is an intrinsic property of this protein region, rather than a result of additional cellular factors, we next investigated LARP6 interactions with its RNA targets in vitro. A segment within the 3’ UTR of the CTNNA1 mRNA, which encodes for Catenin α1, a cytoskeletal protein that bridges cadherin molecules with actin filaments27, was selected as the representative target of LARP6 for in vitro analysis. This choice was due to the strong yet highly focused binding of FL LARP6 to this region in the form of two adjacent iCLIP peaks, alongside weaker interactions detected only with the NTR-deleted mutant (Fig. 4a), a pattern exemplifying our metagene analysis-based observation. We designed 25 nucleotide-long RNA oligonucleotides corresponding to the two primary peaks (P), as well as four additional surrounding peaks located upstream (U) or downstream (D) of the main binding sites (Fig. 4a). As a control, we used a poly C oligonucleotide, which is not expected to bind to LARP6 FL, but could potentially interact with the La-module in the absence of NTR, based on our iCLIP linear motif analysis (Fig. 3f–i). These RNA oligos were biotinylated for use in biolayer interferometry (BLI) analysis28. Biotinylated oligonucleotides were subsequently immobilised on streptavidin-coated biosensors to measure the association-and-dissociation kinetics with the purified La-module and NTD, obtained recombinantly from bacteria (Supplementary Fig. 4a & 4b). A control experiment without RNA loaded on the sensors ruled out non-specific protein binding (Supplementary Fig. 4c & 4d). Steady-state analysis was used to generate equilibrium binding curves for each oligo, by plotting the instrument response against protein concentration. The NTD exhibited varying affinities for the different oligonucleotides representing the CTNNA1 peaks, with low- or mid-nanomolar affinity (17.3–61 nM) towards the main peaks, but weaker binding mostly in the high nanomolar range (85–587 nM) to the peripheral upstream and downstream peaks (Fig. 4b & Table 1). In contrast, the La-module showed comparatively similar binding curves, with affinities in the low nanomolar range (0.9–14 nM) across the different CTNNA1 oligonucleotides (Fig. 4c & Table 1). As expected, virtually no binding was detected between the NTD and the poly C oligo, whereas binding to this oligo, albeit with considerably lower affinity, was measured for the La-module (Figs. 4b, 4c, & Table 1). We also assessed the binding of LARP6 NTR region alone to the oligo representing one of the main peaks, which was found to be ~1000 fold weaker than the La-module (Supplementary Fig. 4e, 4f, & Table 1), consistent with our iCLIP findings that in the absence of the La-module, the NTR IDR does not strongly associate with RNA. Microscale thermophoresis (MST) further validated our BLI measurements, confirming low-nanomolar, mid nanomolar, and micromolar affinities of the La-module, NTD, and NTR for P1 RNA, respectively (Supplementary Fig. 4g–l).

Next, we calculated the relative association constants (Ka) of the La-module and NTD to each RNA target. In agreement with our iCLIP results, the NTD exhibited a narrow RNA-binding profile, with the tightest affinity for the oligo corresponding to one of the main peaks, and lower affinities for the surrounding oligo peaks, suggestive of selective RNA binding (Fig. 4d). Conversely, the La-module exhibited a wider, less selective profile across the CTNNA1 peak oligos tested, indicative of its reduced binding discrimination in the absence of the NTR (Fig. 4e). Together, these results corroborate our iCLIP findings from living cells, suggesting that the NTR has an intrinsic role in enhancing the selectivity of the La-module.

The dynamic NTR is a gatekeeper for the La-module
To mechanistically understand how the NTR affects the RNA-binding selectivity of LARP6, we next performed a thorough molecular characterisation of the system. To validate the disordered nature of NTR, we first performed far-UV circular dichroism (CD). The CD spectrum of the La-module exhibited the expected profile of a folded protein while the NTR showed a minimum at ~200 nm and very low ellipticity at ~220 nm, indicative of intrinsic disorder29 (Fig. 5a). In contrast, the spectra of the NTD showed shapes and molar ellipticities compatible with the presence of both folded and unfolded regions (Fig. 5a). For residue-level information on the conformation and dynamics of the NTR, La-module and the NTD, we used NMR spectroscopy. This allowed us to identify folded domains, corresponding to the La-module, tethered to an unstructured flexible NTR. These features were manifested in the backbone amide chemical shift pattern in the 1H-15N transverse-relaxation optimised spectroscopy (TROSY) experiments, in that well-dispersed peaks correspond to those assigned in the La-module30, whereas those arising from the NTR cluster in 1H-frequencies between ~7.5 and 8.5 ppm (Fig. 5b & Supplementary Fig. 5a), typical of disordered regions. These were sequentially assigned (Supplementary Fig. 5b). The unstructured and dynamic nature of the NTR resonances was further corroborated by their low secondary structure content and R2 values (Supplementary Fig. 5c–d).

A closer inspection of the 1H-15N TROSY spectra of NTD versus La-module and NTR in isolation detected numerous chemical shift perturbations (CSPs) both in the resonances corresponding to the La-module and the NTR, reflecting changes of the chemical environment of these amide groups (Fig. 5b & 5c). This indicates direct contacts between the NTR and the La-module residues, as well as any accompanying conformational rearrangement in the tethered NTD fragment (Fig. 5c). Notably, the observed interaction between the two parts exhibits a transient and dynamic character, given the relatively small magnitude of the observed CSPs in the NTR resonances, as well as their retained ensemble features in the context of the NTD (Fig. 5b & 5c). A further examination by NMR backbone relaxation analysis, notably revealed enhanced R2 rates for selected clusters of NTR residues when tethered to the La-module (Fig. 5d), indicative of decreased molecular motion. The overlap of these regions with resonances showing larger CSPs in the NTD context led to the delineation of two segments (S1 and S2), centred around residues 34 and 52 respectively, as directly engaged in La-module contacts (Fig. 5d). Instead, the changes in dynamics and CSPs observed for a third segment (S3) at the end of NTR are likely attributable to its immediate proximity to the La-module junction, although additional points of interaction cannot be excluded.

To dissect further the relationship between the La-module and the NTR moieties, we turned to size exclusion chromatography small-angle X-ray scattering (SEC-SAXS), a sensitive technique for assessing the overall molecular shape and conformational transitions in solution, which is particularly well-adapted for the quantitative analysis of IDRs31,32. The NTR, the La-module and the NTD exhibited distinct profiles in their dimensionless Kratky plots31 (Fig. 5e). The NTR presented a major deviation from the typical bell-shaped curve expected for globular proteins, showing a quasi-monotonic increase to high qRg values (where q is scattering vector and Rg is the radius of gyration), a profile that is typical of proteins with intrinsic disorder31 (Fig. 5e & Supplementary Fig. 5e). The La-module data recapitulated the behaviour observed previously33, where the structurally independent domains forming the La-module (La-motif and RRM1) sample the conformational space and exist in discrete subsets of accessible populations in a dynamic equilibrium (Fig. 5e & Supplementary Fig. 5f). Interestingly, although the NTD showed an elongated scattering plot compared to the La-module—attributable to the additional tethered residues of the NTR—it also displayed a more pronounced bell-shaped profile, concomitantly with lower data point scattering, suggestive of an overall reduction in the protein dynamics (Fig. 5e & Supplementary Fig. 5g). These changes can be readily illustrated in the comparative analysis of the pairwise distance distribution function P(r), specifically an increase in the maximum dimension Dmax in the NTD, and a change in profile (which is a read-out of the macromolecule’s shape34) to a nearly monomodal distribution (Fig. 5f, Supplementary Fig. 5e–g). Overall, the SAXS profiles indicate a change in the geometry and dynamics of the La-module in the context of the NTD, whilst the NTR retains flexible features as evidenced by NMR experiments. Collectively, these data suggest that the NTR does not fold upon interaction with the La-module; nonetheless its transient interaction locks the La-motif and the RRM1 in a distinct population state, preventing or restricting their ability to sample the conformational space.

NTR promotes selective RNA binding through a composite molecular mechanism
Conformational selection and dynamics are known to play an important role in RNA substrate recognition for several modular RBPs, including LARPs35,36. Equipped with the description of the different conformations of the LARP6 segments in their apo state, we next asked whether the unveiled interplay between the NTR and the La-module may impact LARP6 association with RNA. We focussed on the CTNNA1 P1 RNA probe, which represents a high-score LARP6 iCLIP peak, and binds with high affinity to both the La-module and the NTD (Table 1). Upon establishing a 1:1 RNA–protein binding stoichiometry (Supplementary Fig. 6a), SEC-SAXS methodology was applied to the NTD and the La-module in complex with the RNA. For the La-module, the dimensionless Kratky plot revealed a drasticalteration upon CTNNA1 P1 binding (Fig. 6a & Supplementary Fig. 6b), with the curve becoming bell-shaped and its maximum shifting towards the Guinier–Kratky point (√3, 1.104)34, indicating a non-globular La-module in the apo state that becomes nearly globular in the presence of the P1 RNA. Such rearrangement was corroborated by the P(r) distribution curve of the La-module:P1 complex losing the bimodal character observed in the apo state (Fig. 6b, & Supplementary Fig. 6b), altogether indicating that binding to P1 RNA locks the La-motif and RRM1 in a discrete bound conformation. Notably, the extension of the overall size observed in the protein–RNA sample is compatible with the proposed La-module compaction, considering a possible overhang of the RNA oligo (25 nt long) in the complex (Fig. 6b).

In contrast to the La-module, only minor changes in the Kratky plots and P(r) distance distributions were demonstrated for NTD upon complex formation with the P1 RNA (Figs. 6c, 6d, & Supplementary Fig. 6c). Visual inspection of the data suggested a slightly diminished globularity of the complex, which could be at least in part attributable to the RNA. Collectively, the SAXS derived features of LARP6 in the apo and RNA bound forms support a model in which the La-motif and the RRM1 of the La-module are no longer able to undergo conformational rearrangement upon RNA interaction in the context of the NTD, with the globular discrete configuration populated in the NTD apo state being the one that readily engages with P1 RNA. In other words, the disordered NTR exerts a form of conformational selection onto its adjacent RNA-binding di-domain that tailors it to bind specific target RNAs.

To further dissect at residue-level the role of the NTR in regulation of LARP6 RNA binding, we also applied NMR spectroscopy to the LARP6 proteins in the presence of stoichiometric levels of RNA. 1H-15N TROSY NMR experiments of the NTD upon addition of CTNNA P1 RNA showed CSPs in the folded portion (La-module), evidence of its substantial engagement with the RNA, as well as in the NTR peaks (Fig. 6e–f & Supplementary Fig. 6d–e). Backbone relaxation analyses of the NTD:P1 RNA complex revealed that the segments S2 and S3 of the NTR do not exhibit large changes in R2 values compared to apo NTD, indicating negligible alterations in intrinsic motion upon RNA binding for these regions. On the contrary, a marked decrease in R2 values was observed for segment S1 resonances, suggesting that RNA binding to the NTD disrupts the transient association of this part of the NTR with the La-module, resulting in an enhanced dynamic behaviour (Fig. 6g). This interpretation is supported by the negatively charged nature of S1 (25 AEDVDELEDEEEGAETRGA 37) that can likely mimic the backbone charge of RNA, and the observation that several S1 resonances fully or partially revert to their chemical shift values held in the isolated NTR (Supplementary Fig. 6f & 6g). Notably, the CSP analysis of the NTD in the presence of RNA further revealed that residues belonging to S2 experience distinct perturbations shifting to new positions (Supplementary Fig. 6f & 6g). Intriguingly, this fragment (residues 45–58) overlaps with one of the IP-OOPS N-terminal regions identified as a potential direct site of crosslinking to RNA in living cells (residues 42–48, Fig. 1c), endorsing the hypothesis of a direct engagement with RNA for this segment of the NTR.

Finally, a comparison of the CSPs observed upon RNA titration revealed that the La-module in isolation undergoes perturbations of greater magnitude and coverage than when it is part of the NTD (Supplementary Fig. 6h). These larger CSPs reflect both direct RNA contacts and the domain–domain rearrangements identified in our SEC-SAXS analysis (Fig. 6a, b), for which the relative contribution cannot be resolved. Together, these results indicate that through locking the La-motif and the RRM1 in a defined conformation, the NTR prepares the La-module for selective engagement with RNA. Nonetheless, RNA binding selectivity imparted by the NTR could also in part derive from direct contacts with RNA substrates via the S2 segment, and through modulating RNA access to the La-module in a competitive manner via the S1 segment.

NTR-mediated selective RNA-binding is important for LARP6 function in cells
Having revealed the N-terminal IDR of LARP6 as a key mediator of RNA-binding selectivity, we next sought to determine whether this activity was important for LARP6 function in cells. To investigate this, we developed a knockdown-rescue system in which endogenous LARP6 could be selectively depleted using an siRNA oligonucleotide targeting its 3’ UTR, followed by rescue with our previously described doxycycline-inducible myc-tagged LARP6 expression system that is siRNA-resistant due to lacking the endogenous LARP6 3’ UTR (Supplementary Fig. 7a). Our previous work had demonstrated a role for LARP6 in localising RP-mRNAs to the protrusive fronts of invasive breast cancer cells, as well as supporting cancer cell viability, and promoting invasion17. We therefore assessed whether LARP6 played similar roles in U-87 MG cells. Using a microporous filter-based method for isolating protrusions and cell bodies coupled with RNA sequencing17, we first profiled RNA localisation to protrusions of U-87 MG cells in a global unbiased manner (Fig. 7a & Supplementary Data 4). As expected, RP-mRNAs were enriched in protrusions, but this localisation was significantly abrogated following LARP6 depletion (Fig. 7b & Supplementary Data 4). Notably, rescue of LARP6 expression with either FL or NTR-deleted mutant myc-LARP6 restored the localisation of RP-mRNAs to protrusions (Fig. 5b), demonstrating that this localisation does not significantly depend on the NTR.

Next, we assessed the role of NTR in the regulation of cell migration and invasion, using a 3-dimensional (3D) collagen-I invasion assay37 (Supplementary Fig. 7b). Depletion of LARP6 resulted in a strong reduction in the ability of parental U-87 MG cells to invade into the 3D collagen-I matrix (Fig. 7c & Supplementary Fig. 7c). The effect of LARP6 depletion was comparable to inhibition of Rho Kinase, a potent regulator of cell movement38 (Supplementary Fig. 7d & 7e), highlighting a key role for LARP6 in mediating U-87 MG cell invasion. Crucially, while rescuing LARP6 expression with FL myc-LARP6 could almost fully recover the invasiveness of U-87 MG cells, this rescue was significantly compromised with the NTR-deleted mutant (Fig. 7c & Supplementary Fig. 7c), suggesting that the NTR is required for the full functionality of LARP6 in the context of invasion promotion. We also assessed the effect of LARP6 depletion on the viability of U-87 MG cells. Knockdown of LARP6 resulted in a modest but significant reduction in cell viability, an effect that was rescued by the re-introduction of myc-LARP6 FL (Fig. 7d). The ΔNTR mutant, however, was not capable of rescuing this effect (Fig. 7d), suggesting a key role for the NTR in promoting LARP6-mediated cancer cell viability. Collectively, these depletion-rescue experiments reveal that while the NTR-mediated selectivity in RNA binding may be dispensable for some aspects of LARP6 function, it is likely to be important for the protein’s full activity in promoting viability and invasion.

Methods
Cell culture
U-87MG (ATCC–cat no. HTB-14) and HEK293-T (source: Prof. Chris Marshall’s lab, Institute of Cancer Research, London) cells were grown in DMEM media (Gibco) supplemented with 10% foetal bovine serum (FBS) and 1% penicillin/streptomycin. U-87MG myc-LARP6 inducible cell lines were grown as above, and myc-LARP6 expression was induced with either 60 ng/mL (iCLIP), or 30 ng/mL (all other experiments). MDA-MB231 cells stably expressing GFP-LARP6 cells were generated previously17, and were cultured as above. All cells were maintained in a humidified incubator at 37°C, 5% CO2. Cells were passaged consistently before reaching confluence with Trypsin-EDTA (Gibco), and tested regularly for mycoplasma, using the MycoAlert Mycoplasma Detection Kit (Lonza Bioscience).

Cell line generation
The human codon-optimised LARP6 FL sequence was cloned in the mammalian doxycycline-inducible lentiviral expression vector pCW57.1 using Gateway cloning (Thermo Fisher Scientific) and tagged at the N-terminus with a myc-tag. Deletion mutations were then introduced in the LARP6 FL sequence using Q5 site-directed mutagenesis (NEB) to generate the following deletion mutants: ΔNTR (N-terminal region, deletion of the 2–83 amino acid region), ΔNTD (N-terminal domain, 2–300 deletion), ΔLa-module (La-module, 84–300 deletion), and ΔCTR (C-terminal region, 403–491 deletion). All constructs were validated by Sanger sequencing. Subsequently, each construct was transfected into HEK293-T cells, alongside lentiviral packaging plasmids, using Lipofectamine 2000 (Thermo Fisher), according to the manufacturer’s instructions. The lentiviral particle-containing supernatant was collected after 48 h and used to transduce U-87 MG (ATCC) parental cells. The resulting transduced cells were subsequently expanded and underwent selection for ten days with 0.4 μg/mL puromycin, to generate stable doxycycline-inducible myc-LARP6 cell lines. Inducible myc-LARP6 expression was validated and optimised with western blotting and immunofluorescence.

Endogenous LARP6 knockdown
U-87MG cells were seeded in tissue culture plates 24 h before transfection. An siRNA selectively targeting the 3’ UTR of endogenous LARP6, but not the myc-LARP6 mutants, and a non-targeting siRNA control (scramble) were then transfected into the cells with lipofectamine RNAiMAX (Thermo Fisher), following the manufacturer’s protocol, using a final siRNA concentration of 40 nM. Cells were split or harvested 72 h post-transfection for downstream analyses. The knockdown efficiency was validated with western blotting.

Immunoprecipitation coupled with Orthogonal Organic Phase Separation (IP-OOPS)
Two replicates of 40 million cells were grown in 15 cm dishes and UV-C crosslinked on ice at 400 mJ/cm2 in a Hoefer Scientific UV crosslinker. Cells were then harvested by scraping in cold PBS, followed by centrifugation at 500 g for 10 min at 4°C to obtain cell pellets. Cell pellets were lysed in 500 μL cold RIPA buffer (10 mM Tris-HCl, pH 7.5, 150 mM NaCl, 5 mM EDTA, 0.1% SDS, 1% Triton X-100, 1% sodium deoxycholate, cOmplete protease inhibitor cocktail (Roche), 1 mM PMSF) and incubated on ice for 30 minutes with extensive pipetting on 10 min intervals. Cell lysates were then cleared by centrifugation at 15,000 g for 10 min at 4°C. GFP-LARP6 was immunoprecipitated using 30 μL of GFP-Trap beads (ChromoTek) for one hour at 4°C in a rotating wheel, followed by two washes in cold RIPA buffer. Samples were eluted from the beads by direct addition of 1 mL TRIzol (Thermo Fisher) and 5 min incubation at 65°C, shaking at 1100 rpm. Samples were then placed on a magnet and the eluate was collected. A first OOPS was then performed as described in ref. 19 to isolate the LARP6–RNA adducts. Briefly, phenol-chloroform phase separation was obtained by addition of 200 μL chloroform (SIGMA), extensive mixing, and 15 min centrifugation at 12,000 g, at 4°C. After centrifugation, three phases had formed: the upper aqueous phase containing free RNA, the lower organic phase containing free protein, and the interphase containing crosslinked LARP6–RNA adducts. The interphase was isolated and washed three times by addition of 1 mL TRIzol, 200 μL chloroform, mixing, and centrifugation as described above. Finally, 1 mL 100% methanol was added to the interphase to precipitate LARP6–RNA adducts, followed by 5-minute centrifugation at 12000 g, at 4°C, and isolation of the LARP6–RNA pellet. Partial protease digestion with Arg-C (Promega) protease was then performed according to manufacturer’s instructions to narrow down the protein regions involved in RNA binding. Briefly, each pellet was resuspended in 150 µL of Arg-C incubation buffer, before addition of the enzyme to the final concentration of 10 ng/µL. A volume of 16.7 µL of 10X Arg-C activation buffer was then added to each reaction before mixing and incubation overnight (ON) at 37°C with shaking at 1100 rpm in an Eppendorf ThermoMixer. A second OOPS was subsequently performed, but with some modifications. The samples were first brought to 250 μL by addition of water. 750 μL of TRIzol LS (Thermo Fisher) was then added to the mixture, with the subsequent phase extraction steps carried out as before. Pellets were then resuspended in 50 μL solubilisation buffer (100 mM Tris-HCl, pH 8, 8 M urea) and sonicated with a probe sonicator (SoniPrep 150, MSE, amplitude 10, 15 sec) to help pellet solubilisation. Samples were reduced by treatment with 10 mM DTT (Thermo Fisher) for 30 min at room temperature (RT), followed by alkylation with 55 mM iodoacetamide (G Biosciences) for 30 min at RT, while protected from light. The urea concentration was then diluted four folds by addition of 100 mM Tris-HCl pH 8, followed by the second ON digestion with 2 μg trypsin (SIGMA) in 200 µL of final reaction volume (10 ng/µL Trypsin final concentration) at RT, with shaking at 1100 rpm. The reaction was then stopped by addition of 2% TFA. We also collected the first and second organic phase fractions, precipitated them by the addition of 80% Acetone at −20°C ON, and subjected the protein pellets to Trypsin digestion as described above, in order to assess the coverage and peptide observability for LARP6 in our experiment.

LC-MS/MS mass spectrometry sample preparation, data acquisition, and analysis
The IP-OOPS samples were prepared for LC-MS/MS analysis by desalting following the StageTip procedure45. Samples were reconstituted in 7 μL buffer A* (2% acetonitrile, 0.1% TFA, 0.5% acetic acid, water), and 6 μL were injected into a Q Exactive Plus Orbitrap mass spectrometer coupled with a nanoflow Ultimate 3000 RSLC nano HPLC platform (Thermo Scientific). Mass spectrometry analysis was carried out as described before46. The MaxQuant (version 1.6.3.3)47 was used for all the peptide searches and quantifications. Raw data files were searched against a FASTA file of the human LARP6 protein sequence from Uniprot (https://rest.uniprot.org/uniprotkb/Q9BRS8.fasta). Enzyme specificity was set to Trypsin. False discovery rates (FDR) were calculated using a reversed database search approach and were set to 1%. Default MaxQuant parameters were used, except for the enabling of the “Match between runs” and “Re-quantify” options. The downstream data analysis was performed with the software Perseus (version 1.6.2.1)48. Contaminants were removed by filtering for “Only identified by site”, “Reverse”, and “Potential contaminants”. The remaining identified LARP6 peptides represented the protein regions adjacent to the ones directly involved in RNA binding.

Transcriptome-wide analysis of RNA localisation
Separation of protrusions and cell bodies was carried out as described before17,49. Briefly, 10 cm polycarbonate membrane transwell filters with 3 μm pores (Costar, catalogue number 3420) were coated on both the top and bottom side with collagen I (PureCol, 3 mg/mL) diluted in water 1:30. Coating was performed ON at 4°C, followed by complete transwell drying. Endogenous LARP6 was depleted as described above, and 10 million cells per condition were seeded on top of each 10 cm transwell. Media was added underneath the transwells and cells were incubated in the 37°C humidified incubator for 90 minutes for protrusion induction. The protrusions that formed on the bottom side of the filter were then separated from the cell bodies at the top of the filters and the two fractions were collected in 4% SDS buffer (100 mM Tris-HCl pH 7.5, 4% SDS, RNase-free). Each sample was split into three replicates and total RNA was extracted using TRIzol LS according to the manufacturer’s instructions. The total RNA concentration was measured with the Qubit RNA High-sensitivity assay (Invitrogen) on a Qubit 4 Fluorometer (Invitrogen). The quality of the RNA was validated with the Agilent High Sensitivity RNA ScreenTape assay at an Agilent TapeStation 4000 instrument, with all samples having a quality score RIN ≥ 9.1. Library preparation was performed with the Lexogen QuantSeq 3’ mRNA-Seq V2 Library Prep Kit FWD with Unique Dual Indices according to the manufacturer’s instructions. Each replicate was processed individually to avoid batch effects. 330 ng total RNA in 5 μL volume was used as input. The amplified libraries were quantified and validated with the Qubit dsDNA High-sensitivity and Agilent D1000 high sensitivity ScreenTape assays, pooled in an equimolar ratio, and deep sequenced on an Illumina NextSeq 2000 instrument, using a single-end 100 nt reverse complement workflow. Sequencing was performed at the Barts and The London Genome Centre. The demultiplexed fastq reads were uploaded on the Lexogen Data Analysis Solution, which allowed the automated pre-processing of the data. Adaptors were trimmed and low-quality reads removed using Cutadapt (V1.18) (software developed by Marcel Martin). Trimmed reads were aligned to the human genome (GRCh38, Ensembl release 107) with STAR (V2.6.1a)50. Gene counting was performed with FeatureCounts (V1.6.4)51 and only uniquely mapped reads were considered. The analysis of protrusions/cell bodies enrichment was performed using the Perseus software. The gene counts were first log2 transformed, and ratios were calculated by dividing the log2 counts for the protrusions over the log2 counts for the cell bodies (log2 ratio protrusions/bodies). The median of each column was then subtracted to normalise the data. Transcripts were then annotated with the KEGG database, and 2D annotation enrichment was performed on the averaged log2 ratios, as described in ref. 52, to identify categories that were significantly changing.

3D collagen I invasion assay
The invasion assay was performed as described37, with some modifications. μ-Plates 96-well (ibidi) were first coated with 0.2% BSA (diluted in PBS) for at least 30 min at 4°C. 200 μL of collagen I mix (18 parts PureCol 3 mg/mL (Advanced BioMatrix), 6.66 parts 5X DMEM (Gibco), 1 part 0.1 M sodium hydroxide (SIGMA)) was prepared on ice for each replicate and 20,000 cells were quickly resuspended in the mix and plated. The plates were always kept on ice after cell plating to prevent matrix solidification. At least technical quadruplicates were used in each experiment. After all samples were plated and before the matrix had set, the plates were centrifuged at 300 g for 5 min at 4°C to gather the cells at the bottom of the wells. The plates were then incubated in the 37°C humidified cell incubator for three hours to allow the matrix to solidify. 60 μL complete medium was then added to the top of each well, without touching the matrix, to stimulate cell invasion from the bottom of the well towards the top. 1 μM Rho kinase inhibitor 48 (ROCKi)38 diluted in DMSO was added to the negative control samples. Cells were incubated in the 37°C incubator for 24 h and allowed to invade into the matrix. After 24 h, cells were fixed by addition of 18.5% paraformaldehyde (diluted in PBS) to each well. Hoechst 33258 (1:250, Invitrogen) was also added simultaneously to stain the nuclei. Plates were incubated for four hours at RT, then stored at 4°C until imaging, which was performed within one week. Samples were imaged at a Nikon ECLIPSE Ti Spinning Disk confocal microscope with a plan apochromat VC 20X objective. Hoechst 33258 was excited with a LUN-V 405 nm laser (30% intensity, 300 ms exposure). Six z-stacks were acquired 10 μm apart starting from the bottom of the well where cells had gathered until the furthest distance reached by cells, for a total of 50 μm invasion distance. The following settings were used: 2×2 binning, 540 MHz readout rate, 12-bit and gain 4-bit depth, large image 2×2 fields with 15% overlap (blending). At least two separate images were acquired for each replicate. The nuclei present in each stack were then counted using the Fiji software53. First, each image was converted into binary format with the “threshold” command (default settings), then nuclei that were touching were separated with the “watershed” command. The “analyse particles” function was used to count the nuclei in each stack, with size set to 40-infinity and nuclei excluded from the edges. The bottom two stacks were considered the 0 μm distance, as the matrix was not completely flat in some points. Cells with nuclei in the bottom three stacks (≤ 10 μm distance) were considered non-invading, while cells with nuclei in the top three stacks (≥ 20 μm distance) were considered invading. The invasion capability of the cells was calculated as the invasion index, representative of the percentage of cells that were invading. To calculate the invasion index, the number of nuclei in each stack was first summed, then the percentage of cells that were invading and non-invading was calculated. The percentage of invading cells was then converted into an invasion index by setting the parental cell average as the invasion index = 100 and normalising the other samples accordingly.

Individual-nucleotide resolution UV crosslinking and immunoprecipitation (iCLIP)
iCLIP was performed on U-87 MG myc-LARP6 cells to identify the binding sites of LARP6 at nucleotide resolution, transcriptome-wide. The five myc-LARP6 mutants and the parental negative control were used in the experiment, in triplicates. iCLIP was performed as described before21,54, with specific myc-LARP6 optimisations. Briefly, 20 million cells per condition were grown in 15 cm dishes and myc-LARP6 mutants were induced with 60 ng/mL doxycycline for 24 h. Cells were crosslinked on ice at 150 mJ/cm2 at 254 nm in a Hoefer Scientific UV crosslinker to form covalent bonds between RBPs and RNA that were in direct contact, then scraped in PBS and pelleted. Cell pellets were lysed in iCLIP lysis buffer (50 mM Tris-HCl, pH 7.4, 100 mM NaCl, 1% Igepal CA-630, 0.1% SDS, 0.5% sodium deoxycholate, complete protease inhibitor cocktail (Roche), 1 mM PMSF), cleared, and diluted to 1 mg/mL in 1 mL volume. Samples were then treated with 0.2 units/mL lysate RNase I (Thermo Scientific, catalogue number EN0602) and 2 μL Turbo DNase (Ambion) for 3 min at 37°C to partially digest the RNA. 50 μL Dynabeads Protein G (Invitrogen) per sample were first conjugated with 4 μg (10 μL) mouse anti-myc-tag antibody (Cell Signalling, 9B11) for one hour at RT in a rotating wheel, then added to the samples to perform the immunoprecipitation (IP) for one hour at 4°C in a rotating wheel. After the IP, samples were stringently washed twice with high-salt wash buffer (50 mM Tris-HCl, pH 7.4, 1 M NaCl, 1 mM EDTA, 1% Igepal CA-630, 0.1% SDS, 0.5% sodium deoxycholate), then once with PNK wash buffer (20 mM Tris-HCl, pH 7.4, 10 mM MgCl2, 0.2% Tween-20). The RNA fragments were dephosphorylated at the 3’ end, followed by 3’ end ligation of different barcoded adaptors, to allow for downstream multiplexing of each replicate into one sample. The samples were then eluted from the beads, run on an SDS-PAGE gel, followed by isolation of the RNA fragments and subsequent library preparation as described previously. The amplified libraries were quantified and validated with the Qubit dsDNA High-sensitivity and Agilent D1000 high sensitivity ScreenTape assays, pooled in an equimolar ratio, and deep sequenced on an Illumina NextSeq 500 instrument, using a single-end 100 nt workflow. Sequencing was performed at the Barts and The London Genome Centre.

iCLIP data analysis
iCLIP data was analysed to identify the RNA-binding sites of LARP6 at nucleotide resolution. Raw fastq reads were first demultiplexed based on the experimental barcodes used, to obtain the data from each separate sample. Ultraplex (version 1.1.4)55 was used for the demultiplexing with default settings. The demultiplexed reads were then uploaded on the webserver iMAPS (imaps.goodwright.com) for primary iCLIP data analysis. The human genome GRCh38.p13 GENCODE V42 was used with the primary assembly comprehensive annotation. Reads were first trimmed with TrimGalore! (software developed by Felix Krueger), to remove remaining adapters and low-quality reads, then pre-mapped to rRNA and tRNA sequences with Bowtie256 and discarded. This step ensured that reads mapping to repetitive regions were not misaligned to mRNA. The remaining unmapped reads were then mapped to the genome with STAR50. PCR duplicates were removed with UMI-tools57 based on the presence of identical UMIs in reads mapping to the same position. The exact crosslink position was then identified as the first nucleotide after the experimental barcode, and this data was downloaded from the web server and processed further offline. The crosslink information was used to call the peaks, which represent the binding sites of LARP6, for each individual replicate. The peak caller Clippy (version 1.5.0)58 was used with the following settings: rolling mean 15; minimum counts per gene 3; minimum counts per peak 3; prominence 1 (default); peak threshold 0.4 (default). The peaks called for the individual replicates were then combined into one file per mutant by merging the peaks and summing their peak scores using bedtools (version 2.30.0)59, with the peak scores indicative of the binding strength. Background normalisation was performed by subtracting the peaks that were called in the parental negative control from each combined peak file, using bedtools. The normalised peaks were then annotated to the corresponding transcript and genomic region using a custom script. First, the genomic coordinates for the start and end of the peaks were averaged to obtain the centre of the peak, which was the nucleotide considered for the annotation. This choice was made because peaks overlapping different genomic regions would otherwise be misannotated. The following priorities were then set for the annotation in genomic regions: CDS > 5’ UTR > 3’ UTR > ncRNA > intron > intergenic > transcript > gene. These priorities ensured that the coding region and untranslated regions were prioritised over more general terms. Peaks in transcripts without a defined name were annotated as “Unknown”. Category enrichment analysis was performed using the Perseus software. The normalised peak scores (normalisation described below) were first batch corrected using ComBat60. Data was then annotated with the GO database and underwent a Fisher exact test with Benjamini-Hoechberg FDR cutoff of 0.02. The metagene analysis was performed in R (version 4.3.3) using the metagene2 package (version 1.18.0) (software developed by Eric Fournier, Charles Joly Beauparlant, Cedric Lippens, and Arnaud Droit). First, the nucleotide with the highest crosslink score within each peak, here termed “summit”, was identified by comparing each myc-LARP6 FL iCLIP peak (peak score > 3) with its corresponding crosslink signal. The myc-LARP6 FL summits were saved in .bed format and used as the regions of interest in metagene2, with a padding of 50 nt on each side (padding_size=50). Next, the individual crosslink files for each myc-LARP6 replicate were merged and converted to .bam files with bedtools and used as the alignment files in metagene2. Each dataset was normalised to 100% to obtain the normalised crosslink density for each nucleotide surrounding the summit, also accounting for crosslink score. Metagene2 was run with default parameters, with the exception of: strand_specific = TRUE, bin_count = 100, assay = “RNAseq”. Positional motif analysis was performed using PEKA (version 0.1.5)26 to identify LARP6 binding motifs. First, crosslinks from the three replicate files were merged and sorted by position using bedtools. Next, a genome-wide segmentation file that takes into account the different genomic regions was obtained from the “segment” function in iCount61. The human genome GRCh38.p13 GENCODE V42 was used in this analysis. The k-mer length was set to 5 (default).

Pythia analysis
Pythia is a deep twin-convolutional neural network22. One of the arms of the network is a regular trainable convolutional arm capturing sequence context (sequence arm). The other arm is an untrainable fixed dilated convolutional layer capturing base pairing among nucleotides at different distances (structure arm). Pythia integrates the embedding space of the sequence and structure arms to predict RBP binding. We trained Pythia to distinguish peaks that bind LARP6, and its deletion mutant variants, compared to shuffled sequences with a similar dinucleotide distribution. To quantify the structure versus sequence contribution of each peak, we used DeepLIFT62 to quantify the impact of permuting the input to the sequence and structure arms on the model. We computed the log ratio of the normalised sequencing arm DeepLIFT scores compared to the normalised structure arm DeepLIFT scores. Peaks with higher scores were considered to leverage more from the sequence preference of LARP6, while peaks with lower scores leverage more from the structural preference of LARP6.

Total RNA-Seq for iCLIP normalisation
Total RNA-Seq was performed on cells grown under the same conditions as the ones used in the iCLIP experiment to normalise the iCLIP results for transcript abundance. The normalisation was performed to ensure that what was observed in iCLIP was due to true differences in binding and not to differences in RNA abundance. Total RNA was extracted with TRIzol, quantified with the Qubit RNA High-sensitivity assay, and the quality was validated with the Agilent High Sensitivity RNA ScreenTape assay, with all samples having a RIN ≥ 9.3. The whole transcriptome RNAseq library preparation and sequencing was outsourced to Novogene. The obtained demultiplexed reads were then trimmed with TrimGalore! (version 0.6.10) to remove the remaining adaptor sequences and low-quality reads. Reads were then mapped to the human genome GRCh38.p13 GENCODE V42 with STAR (version 2.7.10b). Default parameters were used, and gene counts were generated directly from the mapping step by enabling the –quantMode GenerateCounts option. The gene counts from the RNAseq were used for iCLIP data normalisation. The iCLIP peak scores were normalised for transcript abundance according to the following formula: normalised peak score = (peak score / gene count) * 1000.

Generation of LARP6 bacterial expression constructs
The human LARP6 sequence was inserted in the bacterial expression vector pET28 using a cloning-by-PCR strategy, and was engineered to contain an N-terminal 6xHis-SUMO-tag in frame with a Tobacco Etch Virus (TEV) protease cleavage site. The LARP6 constructs generated were the following: FL (2–491), NTR (2–83), and NTD (2–300). The deletions were introduced in the LARP6 FL sequence using Q5 site-directed mutagenesis (NEB). Sequences were validated with Sanger sequencing. The La-module (70–300) construct was generated as described in ref. 9.

Recombinant protein expression and purification
The LARP6 recombinant proteins were produced in Escherichia coli Rosetta 2 cells cultured in Luria broth supplemented with antibiotics. Isotopic labelling was obtained by culturing the cells in M9 minimal media enriched with combinations of 15NH₄Cl and 13C-D-glucose, following previously described protocols63. Recombinant protein expression was induced with 1 mM isopropyl β-D-thiogalactoside (IPTG), and bacteria were cultured at 18°C ON in a shaking incubator. Protein purification was performed as described previously9. Briefly, bacterial pellets were first lysed in bacterial lysis buffer (50 mM Tris-HCl, pH 8, 300 mM NaCl, 10 mM imidazole, 5% glycerol, 5 µM lysozyme, complete protease inhibitor cocktail (Roche), 1 mM PMSF), sonicated with a probe sonicator (Fisherbrand) on ice, and cleared by centrifugation at 38,000 g at 4°C. Samples were initially purified on a Ni-immobilised affinity chromatography (Ni-IMAC) 5 mL His-Trap FF affinity column (Cytiva) previously equilibrated in 50 mM Tris-HCl pH 8, 300 mM NaCl, 10 mM imidazole, 5% glycerol. The proteins were eluted using a linear imidazole gradient from 10 to 500 mM. The tags were subsequently cleaved by ON incubation at 4°C with a 6xHis-TEV protease, and the untagged proteins were recovered with a reverse nickel affinity chromatography using the Super Ni-NTA affinity resin (Generon). Nucleic acid contaminants were removed by loading the samples on a 5 mL HiTrap Heparin HP affinity column (Cytiva, for LARP6 La-module, and NTD proteins) or a 5 mL HiTrap DEAE FF affinity column (Cytiva, for LARP6 NTR protein), eluting bound species with a linear KCl gradient from 0.1 to 1 M. The final purified products were dialysed in 20 mM Tris-HCl, pH 7.25, 100 mM KCl, 5 mM MgCl2, 1 mM DTT and concentrated to the desired concentration. The protein concentration was measured at 280 nm absorbance and corrected by the theoretical extinction coefficient derived from the ExPASy ProtParam tool64. Protein aliquots were snap frozen and stored at −80°C.

Circular dichroism (CD)
Recombinant proteins were first diluted in 20 mM Tris-HCl, pH 7.25, 100 mM KCl, 5 mM MgCl2, 1 mM DTT to a concentration of 0.2 mg/mL. UV and CD spectra were acquired on a Chirascan Plus spectrophotometer (Applied Photophysics) under constant nitrogen flush, as described before40. Suprasil rectangular cells of 10 mm and 0.5 mm path length (Starna Scientific) were used for the measurements. The experiments were run at 25°C with 1 nm spectral bandwidth, 1 nm data step-size, and 1.5 seconds time-per-data-point. First, UV spectra were acquired between 230–400 nm to validate the exact concentration of the recombinant proteins. Next, far-UV CD spectra were acquired between 195–260 nm. The UV spectra were corrected for the scattering and smoothened using Savitsky–Golay smoothing with a convolution width of 4 points. The far-UV CD data in millidegrees was then converted to mean residue ellipticity (Θ, deg*cm2*dmol-1), accounting for the exact concentration of each sample calculated from the UV spectra.

RNA oligo preparation
RNA oligos utilised in this study (Supplementary Table 1) were synthesised by Integrated DNA Technologies (IDT), Horizon Discovery and Merck, incorporating 5’ biotin (Bi) and 5’ 6-FAM (fluoresceine) modifications for interferometry and microscale thermophoresis experiments, respectively. When necessary, the samples were deprotected according to the sourcing companies’ protocols. Lyophilised RNA powders were resuspended in diethyl pyrocarbonate (DEPC)-treated water to create high-concentration stock solutions, which were diluted to working concentrations immediately before the experiments. The concentration of the RNA samples was adjusted using the extinction coefficient values calculated by the sourcing companies.

Biolayer interferometry (BLI)
BLI experiments were performed on an Octet R8 (Sartorius) instrument, using the Octet BLI Discovery software (12.2.2.20), and Octet BLI Analysis software (12.2.2.4). Recombinant protein concentrations were measured using a V-760 UV-Visible Spectrophotometer (JASCO). The 5’ biotinylated RNA oligos and recombinant proteins were diluted in BLI buffer (20 mM Tris-HCl pH 7.5, 100 mM KCl, 0.5 mM MgCl2, 1 mM TCEP, 0.05% Tween-20). The assays were carried out at 25°C, in 96-well plates (Greiner), with a sample volume of 200 μL and with 1000 rpm shaking. After hydration of the sensors for at least 20 minutes, the biotinylated RNAs were immobilised on streptavidin-coated biosensors (Octet® SA Biosensors, Sartorius) to a final concentration of 0.10–0.15 μg/mL and incubated with varying concentrations of LARP6 NTD, La-module, and NTR. The protein concentrations used ranged between 0–31.3 nM for the La-module protein, and 0–500 nM for the NTD and NTR proteins. Sensor regeneration in between technical repeats was performed by dipping the sensors in RNase-free 1 M NaCl for 30 s, followed by 30 s in BLI buffer, three times. Experiments were performed at least in triplicate, using freshly prepared protein solutions. Control experiments to assess non-specific protein interactions with the sensors were performed by repeating the assays with sensors with no RNA loaded. Equilibrium dissociation constants (KD) for the RNA-protein interactions were estimated by performing steady-state analysis and plotting the instrument response at equilibrium as a function of protein concentration. The data was fitted using the Octet BLI Analysis software assuming a 1:1 interaction and using non-linear least squares regression. Association constant values (Ka) were obtained from KD values using the formula Ka = 1 / KD.

Computational disorder predictions
The IUPred2A web server (iupred2a.elte.hu)20,65 was used to predict the likelihood of intrinsic disorder in LARP6 based on its amino acid sequence using an energy estimation approach. The IUPred2 algorithm was used to identify disordered protein regions. The prediction type default option of “long disorder” was used, to predict global structural disorder of at least 30 consecutive residues. A context-dependent prediction of disorder was performed with the ANCHOR2 algorithm, which identified disordered binding regions.

Size exclusion chromatography-small angle X-ray scattering (SEC-SAXS)
SEC-SAXS data were acquired on the B21 beamline at Diamond Light Source66, as detailed in (Supplementary Table 2). Samples were prepared at concentrations of 5 mg/mL in SEC-SAXS buffer (50 mM TRIS pH 7.25, 100 mM KCl, 2 mM EDTA, 5 mM MgCl2 and 1 mM DTT). For protein–RNA complexes RNA was freshly added achieving a final protein-to-RNA molar ratio of 1:2. The samples were loaded onto a KW 402.5 FPLC column (Shodex) equilibrated with SEC-SAXS buffer. These samples were then exposed to an X-ray beam with a wavelength of 0.9464 Å and energy of 13.1 keV, produced by a bending magnet source with a flux of 4×10¹² photons/sec and a Q range of 0.0045–0.34 Å⁻¹. The beam centres (X and Y) were located at 129.53 mm and 19.92 mm, respectively, with a size of 0.05×0.05 mm (FWHM) at the detector and 1×0.25 mm at the sample site. Data collection was performed using an Eiger X 4 M detector (Dectris) placed 3702.5 mm from the sample, with the experiment conducted at 15°C. A total of 600 frames were collected at a rate of one frame per second. Data reduction and analysis were carried out using ScÅtter IV67, following previously reported guidelines68. Briefly, frames corresponding to the species of interest were merged after buffer subtraction, including frames with similar radius-of-gyration (Rg) values. Scattering data were processed to minimise residual variation, ensuring Guinier fits did not exceed the qRg maximum limit of 1.3. Flexibility analysis was conducted using Porod–Debye, Kratky–Debye, and SYBILS plots, following established guidelines68. Dimensionless Kratky plots provided semi-quantitative insights into the macromolecule’s structural state, normalised for mass and concentration. Real-space representations were derived from SAXS curves in reciprocal space. The particle’s maximum dimension (Dmax) was modelled using Moore analysis to generate the P(r) distribution, which describes all intraparticle distances, including Dmax. The P(r) distributions were normalised to their respective integrated areas. The final P(r) distribution was accepted only when outliers constituted less than 5% of the data points.

Nuclear Magnetic Resonance (NMR)
NMR studies were performed using Bruker AVANCE III HD and AVANCE NEO spectrometers operating at 16.4 T, 18.8 T and 22.3 T. Transverse relaxation optimised spectroscopy (1H-15N TROSY)69 experiments were conducted at 293.15 K using 15N-labelled samples of LARP6 La-module, NTR, and NTD, at a final concentration of 100 µM, in a buffer containing 25 mM TRIS pH 7.25, 200 mM KCl, 0.2 mM EDTA, 5 mM MgCl2, 1 mM TCEP, 0.1% Tween-20, and 5% D2O (NMR buffer). NMR spectra were processed using TopSpin® (Bruker) and NMRPipe70, and analysed with CcpNmr V371 and NMRPipe70. T2 relaxation experiments were recorded using the approach of Yuwen and Skrynnikov, which permits more accurate measurement on IDRs72, and analysed with CcpNmr V371, by exponential least-squares fitting of peak volumes over the course of the data collection. Where overlap in the signals prevented accurate measurements of peak volume, residues were excluded. Average rates and standard deviations were estimated from 100 cycles of Monte Carlo simulation and refitting.

NMR Backbone Assignment
LARP6 NTR backbone resonance assignment was achieved using 13C-15N-labelled samples at a concentration of 400 µM in NMR buffer, through a combination of 2D 1H-15N HSQC73, and 3D HNCACB, CBCA(CO)NH, HNCO, HN(CA)CO, HBHA(CO)NH73,74. All 3D spectra were acquired at 22.3 T with 20%-40% non-uniform sampling (NUS) of the indirect dimensions. Spectra were processed with NMRPipe70 using SMILE75 for NUS reconstruction and visualised using TopSpin® (Bruker) and CcpNmr Analysis Version 371. Approximately 80% of amide groups were assigned confidently in a first round of automated (MARS) assignment76. Minor difficulties resulted from ambiguity in residues of two low-complexity regions of the NTR 29 DELEDEEE 36 and 59 EEEP 62, as well as attenuated NH signal intensities observed towards the N-terminus. These regions were resolved with two HN(C)N experiments77, with 1H and 15N frequency labelling for the indirectly detected amide acquired in separate spectra. A second round of automatic backbone assignment with MARS, with some additional manual curation, enabled essentially complete assignment of backbone resonances, excluding the N-terminal methionine and the amide group of Ala-2, which was absent in all amide-detected spectra, presumably due to rapid exchange with the solvent. The 5 proline residues were identified in the 2D CON heteronuclear correlation78 due to their separated 15N frequency and assigned via the 13C’ frequency of residue (i-1). Secondary structure propensities (SSP) were predicted with the SSP package (https://pound.med.utoronto.ca/JFKlab/index.php#SSP)76, using the CO, Cα, Cβ, Hα chemical shift deviation from expected random coil values.

Chemical shift perturbation (CSP) analyses
1H and 15N resonances of the La-module and NTD of LARP6 were assigned with reference to those of the NTR (this work), La-motif and RRM1 (BMRB entries 25159 and 2516030). CSPs were calculated using the following equation:
CSP = sqrt(δH^2 + 0.15 * δN^2) (1)
where δH and δN are the chemical shift differences in the 1H and 15N dimensions, respectively.

Protein–RNA interaction studies by NMR
For RNA interaction studies, protein–RNA complexes were prepared by mixing 15N-labelled LARP6 La-module and NTD and 13C-15N-labelled NTR samples (100 µM) with CTNNA1 P1 RNA in NMR buffer, to a protein-to-RNA molar ratio of 1:1.5. 1H-15N TROSY experiments were recorded. NMR spectra were processed using TopSpin® (Bruker) and NMRPipe70, and analysed with CcpNmr V371 and NMRPipe70. CSPs were calculated as for above.

Microscale thermophoresis (MST)
Microscale thermophoresis (MST) experiments were conducted using a Monolith NT.115 instrument (NanoTemper Technologies). Binding reactions were prepared in a buffer composed of 20 mM Tris pH 7.25, 100 mM KCl, 1 mM DTT, and 0.05% Tween-20, with a total reaction volume of 20 µL. Concentration ranges of 0.063–32 nM, 15–960 nM and 196–50,000 nM were tested for LARP6 La-module, NTD and NTR, respectively. After preparation, each protein solution was mixed with 5’ 6-FAM-labelled CTNNA1 P1 (Merck) at a final concentration of 25 nM. Samples were loaded into standard treated capillaries (NanoTemper) and MST experiments performed at 25°C, using 50% LED power and 20% MST power. All measurements were performed in four experimental replicates. Thermophoresis was recorded starting with a 5-second baseline measurement, followed by 30 s of irradiation, and a 5 s recovery period. Normalised fluorescence intensity (FNORM) and normalised dose responses were obtained with the MO.Affinity Analysis v2.2.4 software (NanoTemper). Dissociation constants (KD) were determined from fitting the normalised dose responses at different protein concentrations, with a nonlinear binding curve (modified Hill equation) with h=1.5 and Bmax < 1.5, using GraphPad Prism.

Size-exclusion chromatography with multi-angle light scattering (SEC-MALS)
The molar mass of LARP6 La-module and NTD in their apo and bound states with CTNNA1 P1 RNA was estimated by SEC-MALS experiments, using an Agilent HPLC 1260 Infinity II system in line with a DAWN MALS detector (Wyatt Technology™) and a differential refractive index (dRI) Optilab detector (Wyatt Technology™). Separations were carried out using a WTC-015S5 column (Wyatt Technology™) in isocratic mode in SEC-MALS buffer (50 mM Tris pH 7.25, 100 mM KCl, 5 mM MgCl2, and 1 mM DTT), at a flow rate of 0.8 mL/min. Bovine serum albumin (Thermo Fisher) was used to calibrate the system. A total of 100 µL of protein samples, prepared in SEC-MALS buffer at a concentration of 2 mg/mL, was injected, and separation was performed for 25 min. Protein–RNA complexes were prepared at a protein concentration of 2 mg/mL and a 100 µL final volume in SEC-MALS buffer, with a protein-to-RNA molar ratio of 1:1. All experiments were conducted in triplicate. Experimental data were recorded and processed using ASTRA OneClickMW™ using the theoretical extinction coefficient derived from the ExPASy ProtParam tool64.

Western blotting
Western blots were performed as described previously21. Briefly, cell pellets were lysed in SDS buffer (100 mM Tris-HCl pH 7.5, 4% SDS), sonicated with a probe sonicator (SoniPrep 150, MSE, amplitude 8, 10 sec), and cleared. Total protein concentration was quantified using the Pierce BCA Protein Assay Kit (Thermo Fisher). 10–15 µg total protein was prepared for western blotting by addition of 1X NuPAGE LDS Sample Buffer (Thermo Fisher) and 100 mM DTT (Thermo Fisher). Samples were denatured by boiling at 95°C for 5 minutes. Samples were then loaded on 4–12% NuPAGE Bis-Tris Midi protein gels (Thermo Fisher) and run in NuPAGE MOPS running buffer (Thermo Fisher) at 120 V for at least 90 minutes. Transfer was performed using Immobilion-P PVDF membranes (Millipore) in transfer buffer (1X Tris-glycine, 20% SDS) for two hours at 1 A, at 4°C. Membranes were then blocked in 5% milk (diluted in 0.05% PBS-Tween-20) for one hour at RT. Incubation with the primary antibody diluted in 5% milk was performed ON at 4°C, followed by three 10 min washes of the membranes with 0.05% PBS-Tween-20. HRP-conjugated secondary antibodies were then diluted in 5% milk and incubated for one hour at RT, followed by three 10 min washes with 0.05% PBS-Tween-20. Membranes were probed with SuperSignal West Pico PLUS chemiluminescence substrate (Thermo Fisher) and imaged on an Amersham Imager 600 (GE Healthcare). Band intensities were detected using Fiji.

Immunofluorescence
Western blots were performed as described previously17. Briefly, 46,000 cells were plated in glass coverslips placed in 12-well tissue culture plates and allowed to grow for 24 hours. Cells were then fixed in 4% paraformaldehyde (diluted in PBS) for 10 minutes and permeabilised in 0.2% Triton X-100 (diluted in PBS) for 15 minutes. Following three washes with PBS, cells were blocked in 4% BSA (diluted in PBS) for 30 minutes at RT. Primary antibodies were diluted in 4% BSA and incubated for one hour at RT, followed by three washes with PBS. Fluorophore-conjugated secondary antibodies and Hoechst 33258 (1:2000, Invitrogen) were diluted in 4% BSA and incubated for one hour at RT, followed by three washes with PBS. Coverslips were then washed in water and mounted on slides using ProLong Diamond Antifade Mountant (Invitrogen). Coverslips were imaged at a Nikon ECLIPSE Ti Spinning Disk confocal microscope with a plan apochromat λ 60X/1.40 oil objective. Fluorophores were excited with LUN-V 405 nm, 488 nm, and 640 nm lasers. Three z-stacks were acquired 10 μm apart. The following settings were used: 2×2 binning, 540 MHz readout rate, 12-bit and gain 4-bit depth. Five or more images were acquired for each replicate and analysed using Fiji.

Cell Viability assay
Cell viability was measured with the CTG 2.0 Luminescent Cell Viability assay (Promega). 5000 cells were seeded in 96-well plates at least in quadruplicates in 100 µL volume and allowed to grow for 72 h. The CTG reagent was diluted 1:2 in PBS and 100 µL of diluted CTG reagent were added to each well and mixed. The plate was then incubated on a shaker for 2 min, followed by 10 more minutes at RT, protected from light. Samples were then transferred from the tissue culture-grade 96-well plate to a white CELLSTAR 96-well plate (Greiner) suitable for luminescence measurements. Luminescence was measured at a FLUOstar Omega Microplate Reader (BMG Labtech). The background luminescence signal from a well containing media only was subtracted from each sample luminescence signal.

Statistical analysis
The statistical test applied to each experiment is indicated in the corresponding figure legend. Analysis of RNA localisation, invasion, colony formation, and CTG assays was performed in GraphPad Prism version 10. A p-value cutoff of 0.05 was used. Normality of the datasets were assessed using Prism’s normality test. If data distributions were determined to be normal, unpaired t-test was used for significance assessments. Otherwise, a Kolmogorov–Smirnov test was applied for statistical testing of non-normally distributed datasets.

Data analysis and display
Unless otherwise stated, all quantitative data were analysed and displayed using PyMOL Molecular Graphics System 2.0 (Schrödinger, LLC), Microsoft Excel, GraphPad Prism (Dotmatics), and Biorender.com. Individual data-points in each bar graph represent independent biological replicates.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript “an intrinsically disordered region mediates RNA-binding selectivity and pro-oncogenic activities of LARP6” by Capraro et al. describes a potential RNA-binding mechanism of LARP6 and how this mechanism influences its function in cancer cells. Using iCLIP and a mass-spectrometry based method to derive RNA specificity and identify the RNA binding region of LARP6, respectively, the authors speculate about the involvement of the IDR at the N-terminal region (NTR) in RNA specificity, as the data shows that deletion of the NTR decreases RNA specificity. They could demonstrate that this is true using BLI to derive affinities between protein constructs and a specific RNA 25-mer derived from one of the iCLIP hits. They already speculate here that the La-motif and the RRM (La-module) sample a large conformational space without the NTR and could therefore bind to more RNA sequences as compared to the full-length protein in which the NTR is thought to arrest the La-module in a certain conformation, which is specific for a certain RNA sequence. This they tried to validate with SAXS and NMR. Later they also attempted to show that a deletion of the NTR influences invasion and viability of cancer cells.\nDisclaimer: the iCLIP and mass spectrometry data look sound and are partly well-validated with the in vitro data. However, I have not much hands-on experience on these experiments and the necessary statistics needed and can therefore not comment on this part of the manuscript.\nWhile this story is well-written and appealing (and highly interesting, as there is still little known about RNA specificity beyond single classical RNA binding domains), the evidence for the presented mechanism is not convincing enough and it does not rule out other potential explanations (mechanisms) for the observations made. Before this manuscript can be considered at Nature Communications I recommend looking into the following major concerns I have:\n1. The mechanism, the authors presented, by which the NTR influences LARP6’s RNA binding specificity is hard to imagine and not fully backed up by the data. Or in other words, other explanations could not be ruled out sufficiently. The authors claim that the La-module (La-motif + RRM) achieves higher RNA sequence specificity through conformational dynamics restriction imposed by the NTR. While I agree that the data shows that the NTR is needed for RNA specificity (BLI data and iCLIP, mass-spec), I am not convinced that it reduces the conformational sampling of the La-module and thereby increases RNA sequence selectivity. For single-stranded RNA, being very dynamic (maybe not in a full-length 3’UTR scenario but surely within a 25-mer), why should a rigid La-module be more sequence-specific than a mobile La-module (imagining that the La-motif tumbles independently of the RRM1)? If it would be about binding ssRNA within a certain RNA structure, I could imagine this to be a mechanism (e.g. Hollmann et al. 2020, Cell Reports), but with a 25-mer in vitro I doubt that. Other possibilities: i) the NTR is involved in RNA binding directly and increases specificity, ii) the NTR partly obscures the RNA binding region of the La-module and thus allows only certain RNA sequences to stay long enough to outcompete transient interactions of the NTR with the La-module (e.g. Kang HS et al., 2020, PNAS), the authors claim that this interaction is transient, which it seems to be indeed if there is an interaction (see minor point below). The evidence from NMR and SAXS is not conclusive. Upon RNA binding, the La-module and the NTD (NTR + La-module) are compacted as evident from SAXS, so I would agree that RNA rigidifies the independent tumbling of the La-motif and the RRM domain, as shown also for many tandem RRM domain proteins by SAXS and NMR (plenty of references). The NTR has a similar influence on the Kratky plot on the La-module without RNA present but not to such an extent. Comparing SAXS (Kratky and P(r) of the La-module, NTR and NTD, it could be that the NTR binds transiently to the La-module, which would lead to a similar observation. Upon RNA binding, the NTR within the NTT could also bind to the RNA and thus increases compaction. The NMR data is also not conclusive. While the NTR is an IDR (the HetNOE data should be presented as a bar plot to show values between -1 and 1, HetNOE divided by reference, even without assignment, although assignment of the NTR should be straightforward, see below), the chemical shift perturbations (CSPs) between the NTR without La-module and with La-module are indeed very weak. The few CSPs could be in the connecting regions between NTR and La-module, which of course would shift when together in one construct compared to the separate ones (however, these shifts are likely larger). So why did the author not perform the backbone assignment of the NTR. This should be easily possible with a 250 µM sample and this high-quality HSQC spectrum. Then the HetNOE data could be fully analyzed and the interaction with the La-module could be resolved at residue resolution (see below, mutational analysis). Similar for the La-module. The assignment is already available (as shown in the RNA titration experiment), why not identifying the interacting residues on the La-module side? Then the authors could prepare point mutations on the NTR and La-module side to show that upon mutation the interaction between NTR and La-module is gone, and the RNA specificity should be also affected. Then the mechanism could be a competing one. This leaves the option of increasing RNA specificity by NTR binding to RNA. There is a chemical shift perturbation in the NTR upon RNA binding. Again, backbone assignment, so the authors know which residues shift and mutational analysis is possible.\n2. Figure 2: To me (as mentioned, not being an expert on this) all looks very similar and I have problems to be convinced about the differences in RNA binding specificity between the different constructs. There are no significance tests etc. in this figure. The BLI data is more convincing to me.\n3. Figure 7: I do not see a significant difference between FL and ΔNTR in the invasion for sure and not so much in the viability either (panels C and D). Interestingly, between these two a significance indicator is not shown. Is the Kolmogorov-Smirnov test the correct one for significance (in panel B they use the more common unpaired t-test)? So maybe the NTR doesn’t have a significant influence on function after all?\n4. The affinities determined by BLI are very low. Even the NTR alone shows 1.2 µM affinity, which would be in range of a single RRM domain, which would support a direct role of the NTR in RNA specificity. However, the NMR titration with RNA is not consistent with these affinity and if I understood it correctly, the same RNAs (25-mers) were used (P1). The NMR titration shows fast exchange (NTR, which would correspond to high micromolar affinity) and fast-to-intermediate exchange (La-module), which would correspond to mid-micromolar to low micromolar affinity (not low nanomolar). What is the problem here?\nMinor points (but important to clarify/improve)\n1. Figure 1 could be made clearer, which part in panel B is exactly the NTR, La-module, at this stage not clear if LaM means La-motif or La-module, the reader needs to find that out). So it would be good to improve panel B with adding domain boundary sequence numbers and possibly including information from panel C into this also.\n2. The identified motifs in panel C of the NTR are R,K-rich (positively charged, so could bind RNA directly…or involved in LLPS?)\n3. The authors mention an α/β-content estimation from CD data but this is not shown anywhere.\n4. What about the CTR which (according to the authors) also influences LARP6’s RNA binding specificity?", "reviewer_2": "Capraro, Abis, and colleagues present an original and thought-provoking body of work that provides deeper insights into LARP6 structure and function. Applying a thoughtful combination of omics and cell biology techniques, biophysical characterization, and computational prediction, they build a strong case for a previously unknown role of the intrinsically disordered N-terminal region of LARP6 in fine-tuning the specificity of La-RNA interactions through conformational restriction. I commend the authors on the rigorous execution of these studies and on the intuitive way in which they are presented. I support the publication of this manuscript, as both the biological insights and methodologies are valuable contributions to this research field.\nMajor Comments:\n• While the case for the NTR’s role in modulating LARP6 function is apparent, its specific relevance to LARP6’s role in mesenchymal cancer invasiveness and viability is less clearcut. Although LARP6 knockdown unambiguously perturbed invasive capacity of U87MG cells in the collagen assay, the differential between the FL and ΔNTR LARP6 siRNA rescue was marginal. Further studies would be required to draw a definitive conclusion that it is the NTR’s La-modulating function that drives this subtle rescue experiment difference, and not other effects of truncation on LARP6's localization, protein-protein interactions, etc. While I do not view this to be a barrier to publication, I encourage the authors to moderate their concluding statement in the Results section on the critical role of the LARP6 NTR in promoting cancer cell viability and invasion.\nMinor comments:\n• IP-OOPS methods: Please add specific details on proteolytic digest conditions, e.g. sample volumes, input protein concentrations (if known), protease:protein ratios, etc.\n• LC-MS/MS methods: Possible typo for instrument model (Ultimate 3000 RSL nano HPLC -> Ultimate 3000 RSLC nano HPLC).\n• IP-OOPS results: Consider including some brief commentary on whether there are any biases in proteolytic sites (and therefore peptide observability) between different regions of LARP6 that may influence the interpretation. Any knowledge on GFP-LARP6 peptide observability in the absence of UV-crosslinking may be helpful in this regard.\n• Table 2: Recommend reformatting the table so that the KD values for La-module vs. NTD are side by side for each respective RNA oligo.\n• ProteomeXchange/PRIDE deposition: Please add the protein FASTA used for the MaxQuant data processing to PXD064029, so that the precise LARP6 sequence used is archived.", "reviewer_3": "In this manuscript, Capraro et al show that the disordered N-terminal domain of the RNA-binding protein LARP6 fine-tunes RNA-binding specificity by limiting the conformational flexibility of the main RNA-binding domain, the La module. That IDRs tune the specificity and affinity of RNA-binding has been previously shown (PMID: 39353735) but the underlying molecular mechanism has not been investigated, to the best of my knowledge. Thus, this manuscript adds an important layer of information to the modulatory role of IDRs in RNA-binding. The function of RNA-binding by the IDR per se remains, however, unclear and the biological consequences of lacking an IDR for LARP6 seem subtle.\nSpecific comments:\n1) The authors find that, in addition to binding RNA through the La module, LARP6 contacts RNA through the disordered N- and C- terminal regions. However, the role of RNA-binding through these additional regions in modulating the RNA-binding properties of LARP6 has not been investigated. The authors use complete deletions of the N-terminal IRD (up until the La motif), which is a region much broader than the concrete peptides that support RNA-binding (which in addition have not been precisely delineated). These large deletions have been useful to uncover a role of the N-terminal IDR in restricting the conformation of the La module, but they say little about the role of RNA binding by the IRD itself. This reviewer has the impression that similar conclusions could have been reached in this manuscript without the IP-OOPS data used to infer the RNA-binding regions of LARP6.\n2) Does any IDR adjacent to an RBD have the same effect? Could, for example, the disordered region adjacent to the La module at the C-term, which does not bind RNA, have a similar effect than the N-terminal IDR in restricting RNA-binding selectivity? Please, notice that I am not referring to the newly identified RNA-binding region close to the SUZ-C domain, but to the region adjacent to the La module which has not been approached by deletion analysis.\n3) Fine tuning of RNA-binding by the NTR does not seem to have a major biological impact in the in vitro cellular assays that the authors have chosen. The authors claim a difference in migration between FL and  NTR (Fig 7C and lanes 1084-1086 of the main text), but the difference is not statistically significant. The authors should be careful not to overstate their findings. The only significant slight difference seems to rely on cell viability. Would injection of these cells in an animal model (e.g. mouse xenografts) results in a larger difference, for example in tumor growth? Such experiments would support the statement in the title, referring to 'pro-oncogenic activities of LARP6' which currently, in my opinion, are not sufficiently supported.\n4) It is noticeable that the La module alone binds with higher affinity than the whole NTD. In other words, while the N-terminal IDR increases RNA-binding specificity, it also lowers the affinity of the La module for RNA. This should be discussed.\n5) How do the RNA-binding properties of FL with  NTR compare in vitro?\n6) The work of Zigdon et al (PMID: 39353735) should be mentioned.\nOther comments:\n- Please, show the browser images for Figs 2C and 4A.\n- Please, show a gel with the recombinant proteins used in Fig 4."}, "author_response": "Capraro et al., Rebuttal\nReply to reviewers\nWe thank the reviewers for the thorough and insightful review of the manuscript. We\nbelieve we have now addressed their concerns and implemented their suggestions to\nthe best of our ability, as detailed below in our point-by-point rebuttal. Please note that\nfor the ease of assessing the revisions, we have tracked the changes to the revised\nmanuscript text in red.\nReviewer #1\nThe manuscript “an intrinsically disordered region mediates RNA-binding selectivity\nand pro-oncogenic activities of LARP6” by Capraro et al. describes a potential RNA-\nbinding mechanism of LARP6 and how this mechanism influences its function in\ncancer cells. Using iCLIP and a mass-spectrometry based method to derive RNA\nspecificity and identify the RNA binding region of LARP6, respectively, the authors\nspeculate about the involvement of the IDR at the N-terminal region (NTR) in RNA\nspecificity, as the data shows that deletion of the NTR decreases RNA specificity. They\ncould demonstrate that this is true using BLI to derive affinities between protein\nconstructs and a specific RNA 25-mer derived from one of the iCLIP hits. They already\nspeculate here that the La-motif and the RRM (La-module) sample a large\nconformational space without the NTR and could therefore bind to more RNA\nsequences as compared to the full-length protein in which the NTR is thought to\narrest the La-module in a certain conformation, which is specific for a certain RNA sequence.\nThis they tried to validate with SAXS and NMR. Later they also attempted to show that\na deletion of the NTR influences invasion and viability of cancer cells.\nDisclaimer: the iCLIP and mass spectrometry data look sound and are partly well-\nvalidated with the in vitro data. However, I have not much hands-on experience on\nthese experiments and the necessary statistics needed and can therefore not\ncomment on this part of the manuscript.\nWhile this story is well-written and appealing (and highly interesting, as there is still\nlittle known about RNA specificity beyond single classical RNA binding domains), the\nevidence for the presented mechanism is not convincing enough and it does not rule\nout other potential explanations (mechanisms) for the observations made. Before this\nmanuscript can be considered at Nature Communications I recommend looking into\nthe following major concerns I have:\nMajor concerns:\n(Note: Point 1 contained several comments, so we split our replies to each part\naccordingly)\n1- The mechanism, the authors presented, by which the NTR influences LARP6’s RNA\nbinding specificity is hard to imagine and not fully backed up by the data. Or in other\nwords, other explanations could not be ruled out sufficiently. The authors claim that\nthe La-module (La-motif + RRM) achieves higher RNA sequence specificity through\nconformational dynamics restriction imposed by the NTR. While I agree that the data\nshows that the NTR is needed for RNA specificity (BLI data and iCLIP, mass-spec), I\nam not convinced that it reduces the conformational sampling of the La-module and\nthereby increases RNA sequence selectivity.\nCapraro et al., Rebuttal\n> The reduction of the dynamics of the La-module in the presence of the NTR is one\nof the clearest evidence supported by our SEC-SAXS data (Figure 5e in revised\nmanuscript, also reported below as Rebuttal Fig. 1), as shown by the overall reduction\nof the data points scattering of the NTD compared to the La-module in the Kratky plot\nanalysis (recorded at the same synchrotron, in the same buffer, pH, temperature and\nprotein concentration). As the La-module is formed by two structured domains, and in\nagreement with our previous published work (Lizarrondo et al, RNA biol. 20211), the\nSAXS Kratky plot of the La-module displays relative domain-domain dynamics that\ndecrease when tethered to the NTR in the context of the NTD.\nPlease note that a later statement of the reviewer seems to agree with our\ninterpretation: “I would agree that RNA rigidifies the independent tumbling of the La-\nmotif and the RRM domain, as shown also for many tandem RRM domain proteins by\nSAXS and NMR […] The NTR has a similar influence on the Kratky plot on the La-\nmodule without RNA present but not to such an extent. Comparing SAXS (Kratky and\nP(r) of the La-module, NTR and NTD, it could be that the NTR binds transiently to the\nLa-module, which would lead to a similar observation.”\nRebuttal Figure 1: SEC-SAXS Kratky plot of NTD, NTR and La-module.\nFor single-stranded RNA, being very dynamic (maybe not in a full-length 3’UTR\nscenario but surely within a 25-mer), why should a rigid La-module be more sequence-\nspecific than a mobile La-module (imagining that the La-motif tumbles independently\nof the RRM1)? If it would be about binding ssRNA within a certain RNA structure, I\ncould imagine this to be a mechanism (e.g. Hollmann et al. 2020, Cell Reports), but\nwith a 25-mer in vitro I doubt that.\n> We respectfully disagree on this point with the reviewer. There are several published\nexamples where a tandem domain becomes rigid upon ssRNA binding and this\ncorrelates with binding affinity/selectivity . One of such examples is an excellent study\nby Kang at al PNAS 2020 that the reviewer also kindly directed us to2, where on page\nCapraro et al., Rebuttal\n7144 the authors write: “Overall dimensions and compactness of the U2AF2 RRM1,2\ndomains and their complexes with strong and weak Py-tract RNAs approximately\ncorrelate with their binding affinities, such that a more compact conformation is\nassociated with a higher binding affinity (lower K ; Fig. 2b).”. We would like to highlight\nD\nthat the RNA oligos studied in this paper are also single stranded.\nAnother example, and closer to the system studied here, is the La-module of La: The\nLaM and RRM1 are independent in solution in the apo state and become rigid upon\nsingle stranded 3’oligoU interaction (Alfano et al., NSMB 2004; Kotik-Kogan Structure\n2008; Lizarrondo RNA biol 20211,3,4).\n[…] Other possibilities: i) the NTR is involved in RNA binding directly and increases\nspecificity, ii) the NTR partly obscures the RNA binding region of the La-module and\nthus allows only certain RNA sequences to stay long enough to outcompete transient\ninteractions of the NTR with the La-module (e.g. Kang HS et al., 2020, PNAS), the\nauthors claim that this interaction is transient, which it seems to be indeed if there is\nan interaction (see minor point below). The evidence from NMR and SAXS is not\nconclusive. Upon RNA binding, the La-module and the NTD (NTR + La-module) are\ncompacted as evident from SAXS, so I would agree that RNA rigidifies the\nindependent tumbling of the La-motif and the RRM domain, as shown also for many\ntandem RRM domain proteins by SAXS and NMR (plenty of references). The NTR\nhas a similar influence on the Kratky plot on the La-module without RNA present but\nnot to such an extent. Comparing SAXS (Kratky and P(r) of the La-module, NTR and\nNTD, it could be that the NTR binds transiently to the La-module, which would lead to\na similar observation. Upon RNA binding, the NTR within the NTD could also bind to\nthe RNA and thus increases compaction. The NMR data is also not conclusive. While\nthe NTR is an IDR (the HetNOE data should be presented as a bar plot to show values\nbetween -1 and 1, HetNOE divided by reference, even without assignment, although\nassignment of the NTR should be straightforward, see below), the chemical shift\nperturbations (CSPs) between the NTR without La-module and with La-module are\nindeed very weak. The few CSPs could be in the connecting regions between NTR\nand La-module, which of course would shift when together in one construct compared\nto the separate ones (however, these shifts are likely larger). So why did the author\nnot perform the backbone assignment of the NTR. This should be easily possible with\na 250 µM sample and this high-quality HSQC spectrum. Then the HetNOE data could\nbe fully analyzed and the interaction with the La-module could be resolved at residue\nresolution (see below, mutational analysis). Similar for the La-module. The assignment\nis already available (as shown in the RNA titration experiment), why not identifying the\ninteracting residues on the La-module side?\n> In this section the reviewer asks us to better characterise the interaction between\nthe NTR and the La-module to support the proposed molecular mechanism. In\nparticular, the reviewer’s concern is that our data, while supporting a conformational\nrestriction mechanism, do not exclude additional mechanisms. Specifically, two other\npossible contributing mechanisms are proposed: 1- NTR and La-module bind RNA\ncooperatively, thus increasing selectivity, and/or 2- NTR is partially occupying the RNA\nbinding region of the La-module and thus competing off certain unwanted RNA\nsequences.\nCapraro et al., Rebuttal\nWe agree that this part needed further work and are grateful to the reviewer for\nhighlighting the possibility of alternative mechanisms also at play. We followed the\nreviewer’s suggestions to investigate this possibility in great detail, as detailed below:\n• First, we obtained the NMR backbone assignment of the NTR which is now included\nin the new version of the manuscript. The assignment was performed on the NTR in\nisolation that gives high-quality NMR spectra and then transferred to the NTR in the\ncontext of the NTD (methods and Supplementary Figure 5 in the revised manuscript).\n• We also repeated the entire NMR analysis at a higher field (950 MHz) and with the\nexpert support of the MRC biomedical Centre at the Francis Crick institute, London.\nThis led to a considerable improvement of the spectral quality, compared to the\npreviously presented spectra of the NTD recorded at 800 MHz (Rebuttal Figure 2).\nRebuttal Figure 2: Comparison of data at 800 MHz reported in the original manuscript versus the data\nrecorded at 950 MHz NMR, which is now included in the revised manuscript.\n• Equipped with this information we can now perform an NTR-La module interaction\nanalysis at residue resolution, following the reviewer’s very useful suggestion. This\nenabled us to address the reviewer’s comment of the CSPs that could have in principle\ncome only from the connecting regions between NTR and La-module when tethered.\nAs indicated in Rebuttal Figure 3 below (and Figure 5d in the revised manuscript), this\nCapraro et al., Rebuttal\ndoes not appear to be the case, as the large CSPs could be found in the regions\napproximately spanning residues 25-43 (termed S1) and 45-58 (termed S2), in\naddition to residues 77-83, which form the connecting region to the La-module (termed\nS3).\nRebuttal Figure 3: Chemical shift perturbation (CPS) values of the residues of the NTR in isolation vs.\nin the context of the NTD. R2 relaxation of the residues of the NTR in isolation (green) vs. in the context\nof the NTD (black). This figure is now reported as Figure 5d in the revised manuscript.\nThe CSPs are overall weak, and this is perfectly in agreement with transient fuzzy\ninteraction with multiple averaged conformations co-existing at any time. To capture\nsite-specific dynamic and transient behaviour of the NTR both in isolation and when\ntethered to the La-module, we performed R relaxation analysis, which is better suited\n2\nthan the 15N-1H Het-NOE analysis we previously presented (Khan et al. Biophys J\n20155). This shows an agreement with the CSPs, identifying regions that do interact\nwith the tethered La-module, for which the relaxation rate is increased compared with\nthat of the NTR alone (Rebuttal Fig. 3). This analysis has been included in the revised\nmanuscript (Figure 5d).\n• Having addressed these sets of the reviewer’s comments, we then analysed by NMR\nthe behaviour of the La-module and NTD in complex with RNA. These experiments\nwere performed at 950 MHz at the Crick Institute. The R relaxation experiments were\n2\nperformed in the presence of CTNNA1 P1 RNA to compare the dynamic properties of\nthe NTR-in-the-NTD RNA-bound state versus apo. This revealed that the S2 and S3\nregions do not experience large changes upon RNA binding, whilst R2 values in S1\nexhibited a considerable decrease consistent with increased intrinsic motion (Rebuttal\nFigure 4, which is Figure 6g in the revised manuscript). We reasoned that RNA binding\nwould decrease the association of this part of the NTR with the La-module—and this\nis consistent with the negatively charged nature of residues comprising S1.\nCapraro et al., Rebuttal\nRebuttal Figure 4: Changes in R2 rates of NTR residues in isolation, in the context of NTD, or upon\nNTD-P1 RNA association, showing different dynamics behaviour of S1 and S2 segments. This figure is\nnow reported as Figure 6g in the revised manuscript.\nThis interpretation is further supported by the CSP analysis comparing NTD in apo\nand P1 RNA bound state, as several residues in segment S1 revert (fully or partially)\nto their chemical shift values observed in the NTR in isolation, suggesting (at least\npartial) loss of interaction with La-module upon RNA binding (Rebuttal Figure 5 which\nis now Supplementary Figure 6f in the revised manuscript). Interestingly, the CSP\nanalysis also shows that residues in the S2 segment experience distinctive\nperturbations, shifting to new positions. This may reflect either direct contacts with\nRNA, or conformational changes induced as a result of RNA binding. As this region\noverlaps with the IP-OOPS-identified potential RNA binding segment of NTR (residues\n42-48; see Figure 1b of the revised manuscript), suggestive of the direct crosslinking\nto the RNA in living cells, the hypothesis of a direct RNA engagement is indeed most\nlikely. The S2 segment does not have a particularly positively charged character, but\ndoes still contain an Arginine residue which may contribute to electrostatic interactions\nwith the RNA backbone. It also contains a few aromatic residues that could contribute\nto association with RNA bases. This analysis has now been included in the revised\nmanuscript (supplementary Figure 6f of the revised).\nRebuttal Figure 5: Delta CSP values between NTD/NTR and NTD/NTD+P1RNA in relation to R2\nrelaxation rates (see text). The segment 2 (A45–E58) overlaps with the downstream region of the NTR\nIP-OOPS peptide (Fig 1b). This figure is now reported as Supplementary Figure 6f in the revised\nmanuscript.\nCapraro et al., Rebuttal\nIn conclusion, we are very grateful to the reviewer for their constructive suggestions,\nwhich have enabled us to refine the proposed mechanism by which the NTR\nmodulates RNA binding selectivity in LARP6. Our findings now support a\ncomposite mechanism, wherein RNA binding selectivity imparted by the NTR\nlikely arises not only from reduced conformational sampling of the La-module\nbut also from direct contacts of the NTR—specifically segment S2—with the\nRNA (a finding that also confirms our IP-OOPS data), and through modulating\naccess to the La-module by segment S1. This has now been incorporated into the\nrevised manuscript's Results and Discussion sections (see manuscript lines 1081-\n1144).\nPlease note that having now performed an in-depth NMR analysis with the NTR\nassignment and with the entire NTD, we see that the data in the original Figures 6g,\nand 6h was indeed inconclusive as the reviewer pointed out, and we have therefore\nmodified this part of the manuscript accordingly (see lines 1102-1110).\nThen the authors could prepare point mutations on the NTR and La-module side to\nshow that upon mutation the interaction between NTR and La-module is gone, and the\nRNA specificity should be also affected. Then the mechanism could be a competing\none. This leaves the option of increasing RNA specificity by NTR binding to RNA.\nThere is a chemical shift perturbation in the NTR upon RNA binding. Again, backbone\nassignment, so the authors know which residues shift and mutational analysis is\npossible.\n> Whilst further point mutations to dissect the detailed contribution of the different sub-\nregions of the NTR towards its promotion of selective RNA binding is an exciting\nproposition, we believe this to be beyond the scope of our current manuscript, which\naims to establish the domain/region-level mechanisms at play. The current version of\nthis manuscript already integrates an extensive collection of data—spanning in vivo\nand in vitro systems—that together establishes our main findings regarding a novel\nrole for NTR in promoting selective RNA binding by the La-module. These include (i)\nmass spectrometry-based mapping of LARP6–RNA interaction sites in living cells; (ii)\nextensive deletion mutagenesis combined with transcriptome-wide iCLIP to define the\ncontributions of distinct LARP6 regions to RNA binding in living cells; (iii) computational\n(Pythia) as well as in vitro biophysical validation of the NTR’s effect on promoting\nselective RNA binding; (iv) detailed NMR and SAXS-based analyses revealing the\nNTR mechanisms of action; and (v) functional assessment of NTR contribution\ntowards cellular activities of LARP6, showing a significant role for this IDR region in\nmediating key activities of LARP6 in Glioblastoma cells . Notably, our NMR results\nalready suggest sub-regional segments within the NTR that mediate RNA binding\nselectivity through different molecular mechanisms (i.e. S1 and S2), with our IP-OOPS\ndata converging on the same S2 region as a further independent validation of its\nproposed function, setting the scene for future more focused studies onto these sub-\nregions.\nIn conclusion, while we fully agree that systematic mutational analysis of regions or\nindividual residues (e.g. within S1 vs. S2) is the next logical step for further analyses,\nsuch work is not trivial and would require a considerable amount of time and resources\nCapraro et al., Rebuttal\n(including rigorous benchmarking of mutant proteins to rule out indirect confounding\neffects). We therefore believe that such work warrants a dedicated follow-up study,\nand respectfully suggest that the scope of the present manuscript remains focused on\ndiscovering, validating, and characterising the role of NTR in its entirety in modulating\nthe RNA binding selectivity of LARP6.\n2. Figure 2: To me (as mentioned, not being an expert on this) all looks very similar\nand I have problems to be convinced about the differences in RNA binding specificity\nbetween the different constructs. There are no significance tests etc. in this figure. The\nBLI data is more convincing to me.\n> This is correct. Figure 2 shows that deletion of the NTR or CTR does not alter the\noverall repertoire of transcripts that interact with LARP6 in living cells (Figure 2e). The\ndifferences we report—shown later in Figure 3 (in vivo) and Figure 4 (in vitro)—occur\nat the binding-site level, where the NTR deletion leads to broader and less selective\nbinding footprints on the targeted RNAs (e.g. Figures 3e, 4a, 4d, and 4e). This is\nbecause the La-module primarily drives RNA recognition (Figure 2b), while the NTR\nfine-tunes the local binding site selectivity.\n3. Figure 7: I do not see a significant difference between FL and ΔNTR in the invasion\nfor sure and not so much in the viability either (panels C and D). Interestingly, between\nthese two a significance indicator is not shown. Is the Kolmogorov-Smirnov test the\ncorrect one for significance (in panel B they use the more common unpaired t-test)?\nSo maybe the NTR doesn’t have a significant influence on function after all?\n> We are grateful for this comment. We have now done multiple repeats of this\nexperiment and clearly see a significant difference between FL and ΔNTR in their\nability to rescue invasion upon loss of endogenous LARP6 (see new Figure 7c).\nRegarding the statistical test, we were originally using the Kolmogorov-Smirnov test\ndue to the fact that the original smaller datasets did not pass normality test (meaning\ndata distribution could not be assumed to be normal). However, with the additional\nreplicates, the datasets pass the normality test, so a common unpaired t-test is now\nused for significance calculation (see new manuscript Figure 7c).\nWith regards to cell viability, although the impact of endogenous LARP6 depletion on\nthe viability of U87 cells is relatively mild (only a ~25% decrease after 72hrs of\ndepletion, compared to ~50% decrease we reported previously using MDA-MB231\nbreast cancer cell – see Dermit et al., 20206), the FL construct, but not the ΔNTR can\nstill rescue this effect, meaning that the NTR is needed for LARP6 function in this\ncontext as well.\n4. The affinities determined by BLI are very low. Even the NTR alone shows 1.2 µM\naffinity, which would be in range of a single RRM domain, which would support a direct\nrole of the NTR in RNA specificity. However, the NMR titration with RNA is not\nconsistent with these affinity and if I understood it correctly, the same RNAs (25-mers)\nwere used (P1). The NMR titration shows fast exchange (NTR, which would\ncorrespond to high micromolar affinity) and fast-to-intermediate exchange (La-\nmodule), which would correspond to mid-micromolar to low micromolar affinity (not low\nnanomolar). What is the problem here?\nCapraro et al., Rebuttal\n> We agree with the reviewer that the behaviours observed in NMR experiments do\nnot always align with thermodynamic parameters obtained with other biophysical\ntechniques. This discrepancy has been observed by us and others in several systems\nand is likely attributable to aggregation effects at the concentrations typically employed\nin NMR experiments, altering thermodynamics and kinetic behaviours. In light of this,\nand in agreement with the reviewer’s concerns, we conducted an orthogonal binding\nassay that independently confirms the findings from the BLI analysis (MST). These\nnew data have been incorporated into the revised manuscript and are presented in\nSupplementary Figure 4g-l (see manuscript lines 910-913).\nMinor points (but important to clarify/improve)\n1. Figure 1 could be made clearer, which part in panel B is exactly the NTR, La-module,\nat this stage not clear if LaM means La-motif or La-module, the reader needs to find\nthat out). So it would be good to improve panel B with adding domain boundary\nsequence numbers and possibly including information from panel C into this also.\n> Great suggestion! We agree and have rectified this (residue numbers are now added\nto both Figure 1 panels b and c, and the abbreviations are also described in the\nassociated figure legend).\n2. The identified motifs in panel c of the NTR are R,K-rich (positively charged, so could\nbind RNA directly…or involved in LLPS?)\n> We have addressed this in the analysis above. Based on our new NMR analysis,\nwe believe the key region here is C-terminal of the identified crosslink-adjacent NTR\npeptide (see manuscript lines 1081-1100).\n3. The authors mention an α/β-content estimation from CD data but this is not shown\nanywhere.\n> We thank the reviewer for noting this. The α/β-content estimation comparing CD and\nNMR data for the structured La-module was originally included as another table in an\nearlier version of the manuscript, but later removed, as deemed of no particular added\nvalue. However, the text referring to the secondary structure estimation was\ninadvertently left in. We have now corrected this.\nPlease note that in the revised manuscript, we have included an estimation of the\nsecondary structure propensity of the NTR using NMR (see revised Supplementary\nFig. 5c-d and manuscript lines 965-967), which is most relevant to this story.\n4. What about the CTR which (according to the authors) also influences LARP6’s RNA\nbinding specificity?\n> We are currently working on the CTR as part of a different ongoing project, which\ninvestigates both its RNA-dependent and independent roles, so this will be the focus\nof our next work!\nCapraro et al., Rebuttal\nReviewer #2 (Remarks to the Author)\nCapraro, Abis, and colleagues present an original and thought-provoking body of work\nthat provides deeper insights into LARP6 structure and function. Applying a thoughtful\ncombination of omics and cell biology techniques, biophysical characterization, and\ncomputational prediction, they build a strong case for a previously unknown role of the\nintrinsically disordered N-terminal region of LARP6 in fine-tuning the specificity of La-\nRNA interactions through conformational restriction. I commend the authors on the\nrigorous execution of these studies and on the intuitive way in which they are\npresented. I support the publication of this manuscript, as both the biological insights\nand methodologies are valuable contributions to this research field.\nMajor Comments:\n• While the case for the NTR’s role in modulating LARP6 function is apparent, its\nspecific relevance to LARP6’s role in mesenchymal cancer invasiveness and viability\nis less clearcut. Although LARP6 knockdown unambiguously perturbed invasive\ncapacity of U87MG cells in the collagen assay, the differential between the FL and\nΔNTR LARP6 siRNA rescue was marginal. Further studies would be required to draw\na definitive conclusion that it is the NTR’s La-modulating function that drives this subtle\nrescue experiment difference, and not other effects of truncation on LARP6's\nlocalization, protein-protein interactions, etc. While I do not view this to be a barrier to\npublication, I encourage the authors to moderate their concluding statement in the\nResults section on the critical role of the LARP6 NTR in promoting cancer cell viability\nand invasion.\n> We thank the reviewer for this comment. We have now performed additional repeats\nof the 3D invasion experiment, which now shows a clear and significant effect for the\nNTR (revised Figure 7c; see also response to the comment 3 of the reviewer #1). We\ndo, however, agree that moderating the tone of the concluding statements is a good\nidea. This has now been done (see manuscript lines 1165 and 1189). We have also\nchanged the title of our manuscript as per a related comment from reviewer #3, to\navoid overextending our findings with regards to in vivo tumourigenesis.\nMinor comments:\n• IP-OOPS methods: Please add specific details on proteolytic digest conditions, e.g.\nsample volumes, input protein concentrations (if known), protease:protein ratios, etc.\n> Done (see manuscript lines 172-189).\n• LC-MS/MS methods: Possible typo for instrument model (Ultimate 3000 RSL nano\nHPLC -> Ultimate 3000 RSLC nano HPLC).\n> Thank you for spotting the typo. This is now corrected (see manuscript line 195).\nCapraro et al., Rebuttal\n• IP-OOPS results: Consider including some brief commentary on whether there are\nany biases in proteolytic sites (and therefore peptide observability) between different\nregions of LARP6 that may influence the interpretation. Any knowledge on GFP-\nLARP6 peptide observability in the absence of UV-crosslinking may be helpful in this\nregard.\n> Great suggestion! We had data on this but this was not originally included. We have\nnow added this to the revised manuscript (see new Supplementary Figure 1b, and\nmanuscript lines 682-686).\n• Table 2: Recommend reformatting the table so that the KD values for La-module vs.\nNTD are side by side for each respective RNA oligo.\n> Done (we now have rearranged the values so that they are sorted by oligo).\n• ProteomeXchange/PRIDE deposition: Please add the protein FASTA used for the\nMaxQuant data processing to PXD064029, so that the precise LARP6 sequence used\nis archived.\n> Unfortunately, we have not been able to modify our PRIDE entry but have instead\nprovided a link to the FASTA sequence in our methods section (see manuscript line\n199).\nReviewer #3 (Remarks to the Author):\nIn this manuscript, Capraro et al show that the disordered N-terminal domain of the\nRNA-binding protein LARP6 fine-tunes RNA-binding specificity by limiting the\nconformational flexibility of the main RNA-binding domain, the La module. That IDRs\ntune the specificity and affinity of RNA-binding has been previously shown (PMID:\n39353735) but the underlying molecular mechanism has not been investigated, to the\nbest of my knowledge. Thus, this manuscript adds an important layer of information to\nthe modulatory role of IDRs in RNA-binding. The function of RNA-binding by the IDR\nper se remains, however, unclear and the biological consequences of lacking an IDR\nfor LARP6 seem subtle.\nSpecific comments:\n1) The authors find that, in addition to binding RNA through the La module, LARP6\ncontacts RNA through the disordered N- and C- terminal regions. However, the role of\nRNA-binding through these additional regions in modulating the RNA-binding\nproperties of LARP6 has not been investigated. The authors use complete deletions\nof the N-terminal IRD (up until the La motif), which is a region much broader than the\nconcrete peptides that support RNA-binding (which in addition have not been precisely\ndelineated). These large deletions have been useful to uncover a role of the N-terminal\nIDR in restricting the conformation of the La module, but they say little about the role\nof RNA binding by the IRD itself. This reviewer has the impression that similar\nconclusions could have been reached in this manuscript without the IP-OOPS data\nused to infer the RNA-binding regions of LARP6.\nCapraro et al., Rebuttal\n> This is a fair criticism which we have now addressed in the revised manuscript. Our\nnew NMR data now shows that the S2 segment of NTR (which nicely overlaps with\nour candidate IP-OOPS mapped crosslinking site) directly engages with the RNA. This\noccurs in addition to conformational restriction of the La-module, and likely further\ncontributes to RNA selection. Accordingly, we now propose that the mechanism of\nNTR is one that is composite, involving also a direct cooperative binding to RNA (see\nmanuscript lines 1081-1144; see also response to reviewer #1).\n2) Does any IDR adjacent to an RBD have the same effect? Could, for example, the\ndisordered region adjacent to the La module at the C-term, which does not bind RNA,\nhave a similar effect than the N-terminal IDR in restricting RNA-binding selectivity?\nPlease, notice that I am not referring to the newly identified RNA-binding region close\nto the SUZ-C domain, but to the region adjacent to the La module which has not been\napproached by deletion analysis.\n> At the moment, we have no data on the C-term adjacent region of the La-module so\ncannot comment on this. Our focus on the NTR region was guided by our initial IP-\nOOPS experiment and the subsequent iCLIP datasets. Of course more work can be\ndone on other regions of LARP6, but this will have to be the focus of future studies.\n3) Fine tuning of RNA-binding by the NTR does not seem to have a major biological\nimpact in the in vitro cellular assays that the authors have chosen. The authors claim\na difference in migration between FL and DNTR (Fig 7C and lanes 1084-1086 of the\nmain text), but the difference is not statistically significant. The authors should be\ncareful not to overstate their findings. The only significant slight difference seems to\nrely on cell viability. Would injection of these cells in an animal model (e.g. mouse\nxenografts) results in a larger difference, for example in tumor growth? Such\nexperiments would support the statement in the title, referring to 'pro-oncogenic\nactivities of LARP6' which currently, in my opinion, are not sufficiently supported.\n> As discussed in our response to reviewers #1 and #2, We have now done multiple\nadditional repeats of our invasion assay experiment, and now clearly see a significant\ndifference between FL and ΔNTR in their ability to rescue 3D invasion (see new Figure\n7c). Hence, both pro-invasion and pro-proliferation effects of LARP6 require the\nfunction of NTR. However, we agree with the reviewer in moderating the tone of our\nconcluding statements regarding these cell-based assays. This has now been done\nas outlined in response to reviewer #2. In addition, as per reviewer’s suggestion, we\nhave now also revised our manuscript title, removing the word ‘pro-oncogenic’, in order\nnot to imply an overextension of our findings to in vivo tumourigenesis (see manuscript\nline 2).\n4) It is noticeable that the La module alone binds with higher affinity than the whole\nNTD. In other words, while the N-terminal IDR increases RNA-binding specificity, it\nalso lowers the affinity of the La module for RNA. This should be discussed.\n> We thank the reviewer for this excellent suggestion. The additional NMR data that\nwe now report in the revised manuscript clearly shows that the acidic segment of NTR\n(S1) binds to the La-module and needs to be displaced upon RNA binding (new Figure\n6g; see also response to comment 1 of reviewer #1), thus explaining the observed\nCapraro et al., Rebuttal\nreduction in affinity of the NTD in comparison to La-module alone. We now discuss\nthis in the revised manuscript (see manuscript lines 1081-1110 and 1236-1238).\n5) How do the RNA-binding properties of FL with ΔNTR compare in vitro?\n> A side-by-side in vitro comparison of full-length (FL) and the ΔNTR LARP6 mutant\nwould have been conceptually ideal, but in practice, FL proved incompatible with our\nBLI assays, with significant aggregation preventing reliable kinetic/thermodynamic\nmeasurements. NMR is likewise not tractable at this size. We therefore had to focus\non the biochemically tractable NTD, which isolates the La-module and its adjacent\nNTR, the two regions that our iCLIP results revealed as key to the RNA binding activity\nof LARP6. Importantly, we believe that the parallels we observe between our in vivo\niCLIP and in vitro BLI results justifies this choice and support our conclusions without\noverextending them. For example, our BLI measurement on La-module vs. NTD show\nthe same selectivity trends as in our iCLIP data with FL and ΔNTR (i.e. peak widening\neffects), indicating that the NTR-dependent tuning observed in our in vitro experiments\nis likely to be intrinsic to the NTD.\nRebuttal References\n1. Lizarrondo, J., Dock-Bregeon, A.C., Martino, L. & Conte, M.R. Structural dynamics in the\nLa-module of La-related proteins. RNA Biol 18, 194-206 (2021).\n2. Kang, H.S. et al. An autoinhibitory intramolecular interaction proof-reads RNA recognition\nby the essential splicing factor U2AF2. Proc Natl Acad Sci U S A 117, 7140-7149 (2020).\n3. Alfano, C. et al. Structural analysis of cooperative RNA binding by the La motif and central\nRRM domain of human La protein. Nat Struct Mol Biol 11, 323-9 (2004).\n4. Kotik-Kogan, O., Valentine, E.R., Sanfelice, D., Conte, M.R. & Curry, S. Structural analysis\nreveals conformational plasticity in the recognition of RNA 3' ends by the human La\nprotein. Structure 16, 852-62 (2008).\n5. Khan, S.N. et al. Distribution of Pico- and Nanosecond Motions in Disordered Proteins\nfrom Nuclear Spin Relaxation. Biophys J 109, 988-99 (2015).\n6. Dermit, M. et al. Subcellular mRNA Localization Regulates Ribosome Biogenesis in\nMigrating Cells. Dev Cell 55, 298-313 e10 (2020).\nReply to reviewers\nWe are pleased to hear that the reviewers are satisfied with our revisions, and we\nthank them for their thorough and insightful suggestions that significantly improved our\nstudy. Reviewers #2 and #3 had no further comments, and we have here\naddressed the last two remaining minor comments of reviewer #1:\nReviewer #1\n…….However, I think two things are necessary for acceptance:\n1. Currently it sounds that the La-module rigidification is mostly responsible for RNA\nselectivity. This needs to be toned down. (it could actually be that this is not at all\nresponsible for RNA specificity)\n We respectfully disagree with the notion that our manuscript places more\nweight on the rigidification mechanism. In fact, in our abstract, results, figure\nlegends, and discussion sections, we clearly and repeatedly state that a\ncomposite mechanism involving all three processes (rigidification, making\nadditional contacts with RNA, and gating the RNA access to the La-\nmodule) is likely mediating he enhanced selectivity. Please see revised\nmanuscript lines 38-41, 100-103, 359, 415-419, 503-506, and 1488-1489.\nWe believe that all of these mechanisms are likely responsible so should be\nequally mentioned and highlighted.\n2. Addition of a “limitation of the study” section in which my points from above are\naddressed. This should list all the options of RNA specificity increase in an unbiased\nway and possible future experiments to decouple this (mutational analysis and testing\ndifferent RNAs).\n Thank you for this suggestion. We have now added a sentence to our\ndiscussion section highlighting this point. Please see revised manuscript\nlines 487-488."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The additional NMR data (CSPs and relaxation) have really improved the manuscript, as they clearly show that the NTR interacts with the La-module with three sites on the NTR. And that this interaction is likely the reason of the rigidification of the La-module indicative from the SAXS data (to which I agree and I apologize for my confusion regarding this, possibly due to my initial confusion about what is what regarding the names of the constructs: LaM, La-Module, NTR, NTD…I think Figure 1 could still be improved)\nHowever, in my opinion the reason for increased apparent RNA selectivity is still open for debate. The authors themselves have now added the following sentence in their discussion:\n“Further to this, the disordered NTR may also contribute to the increased RNA binding selectivity by participating in direct contacts with RNA substrates, as well as modulating access to the La-module.”\nWhat the data shows:\n1. NTR rigidifies the La-module\n2. NTR has direct interactions to the La-module and interacting sites on NTR are identified\n3. NTR alone also binds RNA\n4. Region S1 of NTR seems to be released from La-module upon RNA binding, but not S2 and S3\nHow I see it (hoping that I don’t miss anything) is that how much each of the events contribute to RNA specificity is not clear.\nThe following things can contribute to RNA selectivity:\n1. Rigidification of the La-module upon NTR binding\n2. NTR contributes with direct RNA contacts to RNA specificity\n3. Blocking of an RNA binding region on RRM and LaM by S1 (which would deselect weaker less-specific RNA targets)\nThey could all be responsible for increased RNA selectivity alone or altogether in any combination and weighting. To my understanding this has not been made clear by this work.\nTo 1., to show that this is an important contribution to RNA selectivity, the authors would need to know the cognate motif of the RRM and the LaM and then put different long spacers between both motif and measure affinity. Rigidified La-module would only bind strong to a certain motif-spaced RNA, while the flexible La-module could bind rather equally strong to differently motif-spaced RNAs. To my knowledge, all RNAs tested were 25 nts long and the separate cognate motifs of LaM and RRM are not known?\nTo 2., direct contacts are there (8 µM or so affinity for NTR alone). I haven’t found any CSPs for NTR to RNA (why not? Now easy to do?).\nIf NTR-RNA CSPs show which residues bind to RNA directly and if they are different from S1 then the three points could be nicely decoupled by mutational analysis and using different RNA lengths (although for the latter the motifs for RRM and LaM should be known).\nI can agree to a certain extend that a mutational analysis can be difficult with such a complex system, especially if RNA binding and La-module binding by NTR cannot be nicely decoupled because of overlap (same residues on S1 bind RNA and La-module). So, I don’t think it is necessary to do it for acceptance of this manuscript, but it would be great if the authors could unravel this in later work.\nHowever, I think two things are necessary for acceptance:\n1. Currently it sounds that the La-module rigidification is mostly responsible for RNA selectivity. This needs to be toned down. (it could actually be that this is not at all responsible for RNA specificity)\n2. Addition of a “limitation of the study” section in which my points from above are addressed. This should list all the options of RNA specificity increase in an unbiased way and possible future experiments to decouple this (mutational analysis and testing different RNAs).\nI hope I didn’t miss anything and if so, I apologize in advance for the extra work and the delay this could have caused.", "reviewer_2": "Thank you to the authors for their thoughtful responses, manuscript adjustments, and additional data inclusions. The revised manuscript addresses all of my comments associated with the original submission, and I am supportive of the work's publication.", "reviewer_3": "The authors have convincingly addressed my concerns. The manuscript is an important contribution to the mechanisms by which disordered regions modulate RNA-binding selectivity."}, "author_response": ""}]

Decision letter