Biolayer Interferometry: Protein-RNA Interactions.

RNA-binding proteins often contain multiple RNA-binding domains connected by short flexible linkers. This domain arrangement allows the protein to bind the RNA with greater affinity and specificity than would be possible with individual domains and sometimes to remodel its structure. It is therefore important to understand how multiple modules interact with RNA because it is the modular nature of these proteins which specifies their biological function. This chapter is concerned with the use of biolayer interferometry to study protein-RNA interactions

The structure of the RbBP5 β-propeller domain reveals a surface with potential nucleic acid binding sites

The multi-protein complex WRAD, formed by WDR5, RbBP5, Ash2L and Dpy30, binds to the MLL SET domain to stabilize the catalytically active conformation required for histone H3K4 methylation. In addition, the WRAD complex contributes to the targeting of the activated complex to specific sites on chromatin. RbBP5 is central to MLL catalytic activation, by making critical contacts with the other members of the complex. Interestingly its only major structural domain, a canonical WD40 repeat -propeller, is not implicated in this function. Here, we present the structure of the RbBP5 -propeller domain revealing a distinct, feature rich surface, dominated by clusters of Arginine residues. Our nuclear magnetic resonance binding data supports the hypothesis that in addition to the role of RbBP5 in catalytic activation, its -propeller domain is a platform for the recruitment of the MLL complexes to chromatin targets through its direct interaction with nucleic acids

The distinct RNA-interaction modes of a small ZnF domain underlay TUT4(7) diverse action in miRNA regulation

TUT4 and the closely related TUT7 are non-templated poly(U) polymerases required at different stages of development, and their mis-regulation or mutation has been linked to important cancer pathologies. While TUT4(7) interaction with its pre-miRNA targets has been characterized in detail, the molecular bases of the broader target recognition process are unclear. Here, we examine RNA binding by the ZnF domains of the protein. We show that TUT4(7) ZnF2 contains two distinct RNA binding surfaces that are used in the interaction with different RNA nucleobases in different targets, i.e that this small domain encodes diversity in TUT4(7) selectivity and molecular function. Interestingly and unlike other well-characterized CCHC ZnFs, ZnF2 is not physically coupled to the flanking ZnF3 and acts independently in miRNA recognition, while the remaining CCHC ZnF of TUT4(7), ZnF1, has lost its intrinsic RNA binding capability. Together, our data suggest that the ZnFs of TUT4(7) are independent units for RNA and, possibly, protein-protein interactions that underlay the protein’s functional flexibility and are likely to play an important role in building its interaction network

KH domains with impaired nucleic acid binding as a tool for functional analysis

In eukaryotes, RNA-binding proteins that contain multiple K homology (KH) domains play a key role in coordinating the different steps of RNA synthesis, metabolism and localization. Understanding how the different KH modules participate in the recognition of the RNA targets is necessary to dissect the way these proteins operate. We have designed a KH mutant with impaired RNA-binding capability for general use in exploring the role of individual KH domains in the combinatorial functional recognition of RNA targets. A double mutation in the hallmark GxxG loop (GxxG-to-GDDG) impairs nucleic acid binding without compromising the stability of the domain. We analysed the impact of the GDDG mutations in individual KH domains on the functional properties of KSRP as a prototype of multiple KH domain-containing proteins. We show how the GDDG mutant can be used to directly link biophysical information on the sequence specificity of the different KH domains of KSRP and their role in mRNA recognition and decay. This work defines a general molecular biology tool for the investigation of the function of individual KH domains in nucleic acid binding proteins

Joint machine learning analysis of muon spectroscopy data from different materials

Machine learning (ML) methods have proved to be a very successful tool in physical sciences, especially when applied to experimental data analysis. Artificial intelligence is particularly good at recognizing patterns in high dimensional data, where it usually outperforms humans. Here we applied a simple ML tool called principal component analysis (PCA) to study data from muon spectroscopy. The measured quantity from this experiment is an asymmetry function, which holds the information about the average intrinsic magnetic field of the sample. A change in the asymmetry function might indicate a phase transition; however, these changes can be very subtle, and existing methods of analyzing the data require knowledge about the specific physics of the material. PCA is an unsupervised ML tool, which means that no assumption about the input data is required, yet we found that it still can be successfully applied to asymmetry curves, and the indications of phase transitions can be recovered. The method was applied to a range of magnetic materials with different underlying physics. We discovered that performing PCA on all those materials simultaneously can have a positive effect on the clarity of phase transition indicators and can also improve the detection of the most important variations of asymmetry functions. For this joint PCA we introduce a simple way to track the contributions from different materials for a more meaningful analysis

Molecular basis of FIR-mediated c-myc transcriptional control

The far upstream element (FUSE) regulatory system promotes a peak in the concentration of c-Myc during cell cycle. First, the FBP transcriptional activator binds to the FUSE DNA element upstream of the c-myc promoter. Then, FBP recruits its specific repressor (FIR), which acts as an on/off transcriptional switch. Here we describe the molecular basis of FIR recruitment, showing that the tandem RNA recognition motifs of FIR provide a platform for independent FUSE DNA and FBP protein binding and explaining the structural basis of the reversibility of the FBP-FIR interaction. We also show that the physical coupling between FBP and FIR is modulated by a flexible linker positioned sequentially to the recruiting element. Our data explain how the FUSE system precisely regulates c-myc transcription and suggest that a small change in FBP-FIR affinity leads to a substantial effect on c-Myc concentration.MRC Grant-in-aid U11757455

Persistence of anticancer activity in berry extracts after simulated gastrointestinal digestion and colonic fermentation

Fruit and vegetable consumption is associated at the population level with a protective effect against colorectal cancer. Phenolic compounds, especially abundant in berries, are of interest due to their putative anticancer activity. After consumption, however, phenolic compounds are subject to digestive conditions within the gastrointestinal tract that alter their structures and potentially their function. However, the majority of phenolic compounds are not efficiently absorbed in the small intestine and a substantial portion pass into the colon. We characterized berry extracts (raspberries, strawberries, blackcurrants) produced by in vitro-simulated upper intestinal tract digestion and subsequent fecal fermentation. These extracts and selected individual colonic metabolites were then evaluated for their putative anticancer activities using in vitro models of colorectal cancer, representing the key stages of initiation, promotion and invasion. Over a physiologically-relevant dose range (0–50 µg/ml gallic acid equivalents), the digested and fermented extracts demonstrated significant anti-genotoxic, anti-mutagenic and anti-invasive activity on colonocytes. This work indicates that phenolic compounds from berries undergo considerable structural modifications during their passage through the gastrointestinal tract but their breakdown products and metabolites retain biological activity and can modulate cellular processes associated with colon cancer

IMP1 KH1 and KH2 domains create a structural platform with unique RNA recognition and re-modelling properties

IGF2 mRNA-binding protein 1 (IMP1) is a key regulator of messenger RNA (mRNA) metabolism and transport in organismal development and, in cancer, its mis-regulation is an important component of tumour metastasis. IMP1 function relies on the recognition of a diverse set of mRNA targets that is mediated by the combinatorial action of multiple RNA-binding domains. Here, we dissect the structure and RNA-binding properties of two key RNA-binding domains of IMP1, KH1 and KH2, and we build a kinetic model for the recognition of RNA targets. Our data and model explain how the two domains are organized as an intermolecular pseudo-dimer and that the important role they play in mRNA target recognition is underpinned by the high RNA-binding affinity and fast kinetics of this KH1KH2-RNA recognition unit. Importantly, the high-affinity RNA-binding by KH1KH2 is achieved by an inter-domain coupling 50-fold stronger than that existing in a second pseudo-dimer in the protein, KH3KH4. The presence of this strong coupling supports a role of RNA re-modelling in IMP1 recognition of known cancer targets