Intrinsically disordered interaction network in an RNA chaperone revealed by native mass spectrometry

Energy Resolved Mass Spectrometry Data from Surfaced Induced Dissociation Improves Prediction of Protein Complex Structure

Native Mass Spectrometry (nMS) is a versatile technique for elucidating protein structure. Surface-Induced Dissociation (SID) is an activation method in tandem MS predominantly employed for determining protein complex stoichiometry alongside information about interface strengths. SID-nMS data can be collected over a range of acceleration energies, yielding Energy Resolved Mass Spectrometry (ERMS) data. Previous work demonstrated that the onset and appearance energy from SID-nMS can be used in integrative computational and experimental modeling to guide multimeric structure determination in some cases. However, the appearance energy is a single data point, while the ERMS data provide a full pattern of interface breakage. We hypothesized that incorporation of ERMS data into multimeric protein structure prediction would significantly outperform appearance energy. To test this hypothesis, we generated models of 20 protein complexes with RosettaDock using subunits generated from AlphaFold2. We simulated the ERMS data for each predicted model and rescored based on its agreement to experimental ERMS data. We demonstrated that more accurately predicted models exhibited simulated ERMS data in better agreement with the experimental data. As part of our ERMS-based rescoring, we matched or improved the RMSD of the best scoring model compared to Rosetta in 16 out of 20 cases, with 4 out of 20 cases improving to become a highly accurate (below 5 Å) structure. Finally, we benchmarked our method against our previously published appearance energy-based rescoring and showed improvement in 14 out of 20 cases, with 6 out of 20 becoming a highly accurate (below 5 Å) model. Our method is freely available through Rosetta Commons, with a usage tutorial and test files provided in the Supporting Information.

ECD functions as a novel RNA-binding protein to regulate mRNA splicing

The human ecdysoneless protein (ECD) plays an essential role in the regulation of cell cycle and cell survival. ECD has been implicated in RNA splicing through its association with the protein components of splicing complex. Here, using electrophoretic mobility shift assay and mutational analysis, we demonstrate that ECD directly binds to RNA through its N-terminal region, specifically using amino acids 135-148. Using enhanced CLIP-seq analyses in human cells, we identified a large repertoire of mRNAs bound to ECD. RNA-seq analyses revealed that ECD depletion in cells leads to widespread RNA splicing aberrations associated with alterations in gene expression. Significantly, we demonstrate that ECD mediates mRNA splicing by directly binding to RNA sequences located near splicing sites. Mechanistically, we demonstrate that ECD directly binds to U5 small nuclear RNA (snRNA), and this interaction is critical for maintaining the expression of key protein components of U5 small nuclear protein (snRNP) complex. Notably, RNA binding defective mutant of ECD fails to rescue downregulated levels of U5 snRNP components or cell proliferation block induced by ECD knockout. Collectively, we provide compelling evidence that ECD regulates RNA splicing by directly associating with RNAs, and the RNA binding activity of ECD is essential for its function.

Direct prediction of intrinsically disordered protein conformational properties from sequence

Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well described by a stable three-dimensional structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means that IDRs are largely absent from the Protein Data Bank, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations and deep learning to develop ALBATROSS, a deep-learning model for predicting ensemble dimensions of IDRs, including the radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences at a proteome-wide scale. ALBATROSS is lightweight, easy to use and accessible as both a locally installable software package and a point-and-click-style interface via Google Colab notebooks. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize the sequence-specific biophysical behavior of IDRs within and between proteomes.

Models of Hfq interactions with small non-coding RNA in Gram-negative and Gram-positive bacteria

Hfq is required by many Gram-negative bacteria to chaperone the interaction between small non-coding RNA (sRNA) and mRNA to facilitate annealing. Conversely and despite the presence of Hfq in many Gram-positive bacteria, sRNAs in Gram-positive bacteria bind the mRNA target independent of Hfq. Details provided by the Hfq structures from both Gram-negative and Gram-positive bacteria have demonstrated that despite a conserved global structure of the protein, variations of residues on the binding surfaces of Hfq results in the recognition of different RNA sequences as well as the ability of Hfq to facilitate the annealing of the sRNA to the mRNA target. Additionally, a subset of Gram-negative bacteria has an extended C-terminal Domain (CTD) that has been shown to affect the stability of the Hfq hexamer and increase the rate of release of the annealed sRNA-mRNA product. Here we review the structures of Hfq and biochemical data that have defined the interactions of the Gram-negative and Gram-positive homologues to highlight the similarities and differences in the interactions with RNA. These interactions provided a deeper understanding of the how Hfq functions to facilitate the annealing of sRNA-mRNA, the selectivity of the interactions with RNA, and the role of the CTD of Hfq in the interactions with sRNA.

Hfq C-terminal region forms a β-rich amyloid-like motif without perturbing the N-terminal Sm-like structure

Hfq is a pleitropic actor that serves as stress response and virulence factor in the bacterial cell. To execute its multiple functions, Hfq assembles into symmetric torus-shaped hexamers. Extending outward from the hexameric core, Hfq presents a C-terminal region, described as intrinsically disordered in solution. Many aspects of the role and the structure of this region remain unclear. For instance, in its truncated form it can promote amyloid-like filament assembly. Here, we show that a minimal 11-residue motif at the C-terminal end of Hfq assembles into filaments with amyloid characteristics. Our data suggest that the full-length Hfq in its filamentous state contains a similar molecular fingerprint than that of the short β-strand peptide, and that the Sm-core structure is not affected by filament formation. Hfq proteins might thus co-exist in two forms in vivo, either as isolated, soluble hexamers or as self-assembled hexamers through amyloid-reminiscent interactions, modulating Hfq cellular functions.

Spatial arrangement of functional domains in OxyS stress response sRNA

Small noncoding RNAs are an important class of regulatory RNAs in bacteria, often regulating responses to changes in environmental conditions. OxyS is a 110 nt, stable, trans-encoded small RNA found in Escherichia coli and is induced by an increased concentration of hydrogen peroxide. OxyS has an important regulatory role in cell stress response, affecting the expression of multiple genes. In this work, we investigated the structure of OxyS and the interaction with fhlA mRNA using nuclear magnetic resonance spectroscopy, small-angle X-ray scattering, and unbiased molecular dynamics simulations. We determined the secondary structures of isolated stem-loops and confirmed their structural integrity in OxyS. Unexpectedly, stem-loop SL4 was identified in the region that was predicted to be unstructured. Three-dimensional models of OxyS demonstrate that OxyS adopts an extended structure with four solvent-exposed stem-loops, which are available for interaction with other RNAs and proteins. Furthermore, we provide evidence of base-pairing between OxyS and fhlA mRNA.

Dissecting the structural heterogeneity of proteins by native mass spectrometry

A single gene yields many forms of proteins via combinations of posttranscriptional/posttranslational modifications. Proteins also fold into higher-order structures and interact with other molecules. The combined molecular diversity leads to the heterogeneity of proteins that manifests as distinct phenotypes. Structural biology has generated vast amounts of data, effectively enabling accurate structural prediction by computational methods. However, structures are often obtained heterologously under homogeneous states in vitro. The lack of native heterogeneity under cellular context creates challenges in precisely connecting the structural data to phenotypes. Mass spectrometry (MS) based proteomics methods can profile proteome composition of complex biological samples. Most MS methods follow the "bottom-up" approach, which denatures and digests proteins into short peptide fragments for ease of detection. Coupled with chemical biology approaches, higher-order structures can be probed via incorporation of covalent labels on native proteins that are maintained at the peptide level. Alternatively, native MS follows the "top-down" approach and directly analyzes intact proteins under nondenaturing conditions. Various tandem MS activation methods can dissect the intact proteins for in-depth structural elucidation. Herein, we review recent native MS applications for characterizing heterogeneous samples, including proteins binding to mixtures of ligands, homo/hetero-complexes with varying stoichiometry, intrinsically disordered proteins with dynamic conformations, glycoprotein complexes with mixed modification states, and active membrane protein complexes in near-native membrane environments. We summarize the benefits, challenges, and ongoing developments in native MS, with the hope to demonstrate an emerging technology that complements other tools by filling the knowledge gaps in understanding the molecular heterogeneity of proteins.

Intrinsically disordered interaction network in an RNA chaperone revealed by native mass spectrometry

RNA-binding proteins contain intrinsically disordered regions whose functions in RNA recognition are poorly understood. The RNA chaperone Hfq is a homohexamer that contains six flexible C-terminal domains (CTDs). The effect of the CTDs on Hfq's integrity and RNA binding has been challenging to study because of their sequence identity and inherent disorder. We used native mass spectrometry coupled with surface-induced dissociation and molecular dynamics simulations to disentangle the arrangement of the CTDs and their impact on the stability of Escherichia coli Hfq with and without RNA. The results show that the CTDs stabilize the Hfq hexamer through multiple interactions with the core and between CTDs. RNA binding perturbs this network of CTD interactions, destabilizing the Hfq ring. This destabilization is partially compensated by binding of RNAs that contact multiple surfaces of Hfq. By contrast, binding of short RNAs that only contact one or two subunits results in net destabilization of the complex. Together, the results show that a network of intrinsically disordered interactions integrate RNA contacts with the six subunits of Hfq. We propose that this CTD network raises the selectivity of RNA binding.