Structural biology of heterogeneous RNAs
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Cellular dsRNA interactome captured by K1 antibody reveals the regulatory map of exogenous RNA sensing
RNA-binding proteins (RBPs) provide a critical post-transcriptional regulatory layer in determining RNA fate. Currently, UV crosslinking followed by oligo-dT pull-down is the gold standard in identifying the RBP repertoire of poly-adenylated RNAs, but such method is ineffective in capturing RBPs that recognize double-stranded RNAs (dsRNAs). Here, we utilize anti-dsRNA K1 antibody immunoprecipitation followed by quantitative mass spectrometry to comprehensively identify RBPs bound to cellular dsRNAs without external stimulus. Notably, our dsRNA interactome contains proteins involved in sensing N6-methyladenosine RNAs and stress granule components. We further perform targeted CRISPR-Cas9 knockout functional screening and discover proteins that can regulate the interferon (IFN) response during exogenous RNA sensing. Interestingly, most dsRBPs promote IFN-β secretion in response to dsRNA stimulation and act as antiviral factors during HCoV-OC43 infection. Our dsRNA interactome capture provides an unbiased and comprehensive characterization of putative dsRBPs and will facilitate our understanding of dsRNA sensing in physiological and pathological contexts.
DeltaC and DeltaD ligands play different roles in the segmentation clock dynamics
The vertebrate segmentation clock drives periodic somite segmentation during embryonic development. Her1 and Her7 clock proteins generate oscillatory expression of their own genes as well as that of deltaC in zebrafish. In turn, DeltaC and DeltaD ligands activate Notch signaling, which then activates transcription of clock genes in neighboring cells. While DeltaC and DeltaD proteins form homo- and heterodimers, only DeltaC-containing oscillatory dimers were expected to be functional. To investigate the contributions of DeltaC and DeltaD proteins on the transcription of her1 and her7 segmentation clock genes, we counted their transcripts by performing single molecule fluorescent in situ hybridization imaging in different genetic backgrounds of zebrafish embryos. Surprisingly, we found that DeltaD homodimers are also functional. We further found that Notch signaling promotes transcription of both deltaC and deltaD genes, thereby creating a previously unnoticed positive feedback loop. Our computational model highlighted the intriguing differential roles of DeltaC and DeltaD dimers on the clock synchronization and transcript numbers, respectively. We anticipate that a mechanistic understanding of the Notch signaling pathway will not only shed light on the mechanism driving robust somite segmentation but also inspire similar quantitative studies in other tissues and organs.
Circular RNAs in neurological conditions – computational identification, functional validation, and potential clinical applications
Non-coding RNAs (ncRNAs) have gained significant attention in recent years due to advancements in biotechnology, particularly high-throughput total RNA sequencing. These developments have led to new understandings of non-coding biology, revealing that approximately 80% of non-coding regions in the genome possesses biochemical functionality. Among ncRNAs, circular RNAs (circRNAs), first identified in 1976, have emerged as a prominent research field. CircRNAs are abundant in most human cell types, evolutionary conserved, highly stable, and formed by back-splicing events which generate covalently closed ends. Notably, circRNAs exhibit high expression levels in neural tissue and perform diverse biochemical functions, including acting as molecular sponges for microRNAs, interacting with RNA-binding proteins to regulate their availability and activity, modulating transcription and splicing, and even translating into functional peptides in some cases. Recent advancements in computational and experimental methods have enhanced our ability to identify and validate circRNAs, providing valuable insights into their biological roles. This review focuses on recent developments in circRNA research as they related to neuropsychiatric and neurodegenerative conditions. We also explore their potential applications in clinical diagnostics, therapeutics, and future research directions. CircRNAs remain a relatively underexplored area of non-coding biology, particularly in the context of neurological disorders. However, emerging evidence supports their role as critical players in the etiology and molecular mechanisms of conditions such as schizophrenia, bipolar disorder, major depressive disorder, Alzheimer’s disease, and Parkinson’s disease. These findings suggest that circRNAs may provide a novel framework contributing to the molecular dysfunctions underpinning these complex neurological conditions.
T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity
T-cell receptor (TCR) structures are currently under-utilised in early-stage drug discovery and repertoire-scale informatics. Here, we leverage a large dataset of solved TCR structures from Immunocore to evaluate the current state-of-the-art for TCR structure prediction, and identify which regions of the TCR remain challenging to model. Through clustering analyses and the training of a TCR-specific model capable of large-scale structure prediction, we find that the alpha chain VJ-recombined loop (CDR3α) is as structurally diverse and correspondingly difficult to predict as the beta chain VDJ-recombined loop (CDR3β). This differentiates TCR variable domain loops from the genetically analogous antibody loops and supports the conjecture that both TCR alpha and beta chains are deterministic of antigen specificity. We hypothesise that the larger number of alpha chain joining genes compared to beta chain joining genes compensates for the lack of a diversity gene segment. We also provide over 1.5M predicted TCR structures to enable repertoire structural analysis and elucidate strategies towards improving the accuracy of future TCR structure predictors. Our observations reinforce the importance of paired TCR sequence information and capture the current state-of-the-art for TCR structure prediction, while our model and 1.5M structure predictions enable the use of structural TCR information at an unprecedented scale.
Modern biology of extrachromosomal DNA: A decade-long voyage of discovery
Genomic instability is a hallmark of cancer and is a major driving force of tumorigenesis. A key manifestation of genomic instability is the formation of extrachromosomal DNAs (ecDNAs) — acentric, circular DNA molecules ranging from 50 kb to 5 Mb in size, distinct from chromosomes. Ontological studies have revealed that ecDNA serves as a carrier of oncogenes, immunoregulatory genes, and enhancers, capable of driving elevated transcription of its cargo genes and cancer heterogeneity, leading to rapid tumor evolution and therapy resistance. Although ecDNA was documented over half a century ago, the past decade has witnessed a surge in breakthrough discoveries about its biological functions. Here, we systematically review the modern biology of ecDNA uncovered over the last ten years, focusing on how discoveries during this pioneering stage have illuminated our understanding of ecDNA-driven transcription, heterogeneity, and cancer progression. Furthermore, we discuss ongoing efforts to target ecDNA as a novel approach to cancer therapy. This burgeoning field is entering a new phase, poised to reshape our knowledge of cancer biology and therapeutic strategies.
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