Assembly and activation of EBV latent membrane protein 1.

Latent membrane protein 1 (LMP1) is the primary oncoprotein of Epstein-Barr virus (EBV) and plays versatile roles in the EBV life cycle and pathogenesis. Despite decades of extensive research, the molecular basis for LMP1 folding, assembly, and activation remains unclear. Here, we report cryo-electron microscopy structures of LMP1 in two unexpected assemblies: a symmetric homodimer and a higher-order filamentous oligomer. LMP1 adopts a non-canonical and unpredicted fold that supports the formation of a stable homodimer through tight and antiparallel intermolecular packing. LMP1 dimers further assemble side-by-side into higher-order filamentous oligomers, thereby allowing the accumulation and specific organization of the flexible cytoplasmic tails for efficient recruitment of downstream factors. Super-resolution microscopy and cellular functional assays demonstrate that mutations at both dimeric and oligomeric interfaces disrupt LMP1 higher-order assembly and block multiple LMP1-mediated signaling pathways. Our research provides a framework for understanding the mechanism of LMP1 and for developing potential therapies targeting EBV-associated diseases.

Spatially coordinated heterochromatinization of long synaptic genes in fragile X syndrome.

Short tandem repeat (STR) instability causes transcriptional silencing in several repeat expansion disorders. In fragile X syndrome (FXS), mutation-length expansion of a CGG STR represses FMR1 via local DNA methylation. Here, we find megabase-scale H3K9me3 domains on autosomes and encompassing FMR1 on the X chromosome in FXS patient-derived iPSCs, iPSC-derived neural progenitors, EBV-transformed lymphoblasts, and brain tissue with mutation-length CGG expansion. H3K9me3 domains connect via inter-chromosomal interactions and demarcate severe misfolding of TADs and loops. They harbor long synaptic genes replicating at the end of S phase, replication-stress-induced double-strand breaks, and STRs prone to stepwise somatic instability. CRISPR engineering of the mutation-length CGG to premutation length reverses H3K9me3 on the X chromosome and multiple autosomes, refolds TADs, and restores gene expression. H3K9me3 domains can also arise in normal-length iPSCs created with perturbations linked to genome instability, suggesting their relevance beyond FXS. Our results reveal Mb-scale heterochromatinization and trans interactions among loci susceptible to instability.

Structural biology of innate immunity.

Innate immune responses depend on timely recognition of pathogenic or danger signals by multiple cell surface or cytoplasmic receptors and transmission of signals for proper counteractions through adaptor and effector molecules. At the forefront of innate immunity are four major signaling pathways, including those elicited by Toll-like receptors, RIG-I-like receptors, inflammasomes, or cGAS, each with its own cellular localization, ligand specificity, and signal relay mechanism. They collectively engage a number of overlapping signaling outcomes, such as NF-κB activation, interferon response, cytokine maturation, and cell death. Several proteins often assemble into a supramolecular complex to enable signal transduction and amplification. In this article, we review the recent progress in mechanistic delineation of proteins in these pathways, their structural features, modes of ligand recognition, conformational changes, and homo- and hetero-oligomeric interactions within the supramolecular complexes. Regardless of seemingly distinct interactions and mechanisms, the recurring themes appear to consist of autoinhibited resting-state receptors, ligand-induced conformational changes, and higher-order assemblies of activated receptors, adaptors, and signaling enzymes through conserved protein-protein interactions.

Changes in genome architecture and transcriptional dynamics progress independently of sensory experience during post-natal brain development.

Both transcription and three-dimensional (3D) architecture of the mammalian genome play critical roles in neurodevelopment and its disorders. However, 3D genome structures of single brain cells have not been solved; little is known about the dynamics of single-cell transcriptome and 3D genome after birth. Here, we generated a transcriptome (3,517 cells) and 3D genome (3,646 cells) atlas of the developing mouse cortex and hippocampus by using our high-resolution multiple annealing and looping-based amplification cycles for digital transcriptomics (MALBAC-DT) and diploid chromatin conformation capture (Dip-C) methods and developing multi-omic analysis pipelines. In adults, 3D genome "structure types" delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first post-natal month. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, we examine allele-specific structure of imprinted genes, revealing local and chromosome (chr)-wide differences. These findings uncover an unknown dimension of neurodevelopment.

Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus.

Eukaryotic genomes are packaged into a 3-dimensional structure in the nucleus. Current methods for studying genome-wide structure are based on proximity ligation. However, this approach can fail to detect known structures, such as interactions with nuclear bodies, because these DNA regions can be too far apart to directly ligate. Accordingly, our overall understanding of genome organization remains incomplete. Here, we develop split-pool recognition of interactions by tag extension (SPRITE), a method that enables genome-wide detection of higher-order interactions within the nucleus. Using SPRITE, we recapitulate known structures identified by proximity ligation and identify additional interactions occurring across larger distances, including two hubs of inter-chromosomal interactions that are arranged around the nucleolus and nuclear speckles. We show that a substantial fraction of the genome exhibits preferential organization relative to these nuclear bodies. Our results generate a global model whereby nuclear bodies act as inter-chromosomal hubs that shape the overall packaging of DNA in the nucleus.

Disease-Associated Short Tandem Repeats Co-localize with Chromatin Domain Boundaries.

More than 25 inherited human disorders are caused by the unstable expansion of repetitive DNA sequences termed short tandem repeats (STRs). A fundamental unresolved question is why some STRs are susceptible to pathologic expansion, whereas thousands of repeat tracts across the human genome are relatively stable. Here, we discover that nearly all disease-associated STRs (daSTRs) are located at boundaries demarcating 3D chromatin domains. We identify a subset of boundaries with markedly higher CpG island density compared to the rest of the genome. daSTRs specifically localize to ultra-high-density CpG island boundaries, suggesting they might be hotspots for epigenetic misregulation or topological disruption linked to STR expansion. Fragile X syndrome patients exhibit severe boundary disruption in a manner that correlates with local loss of CTCF occupancy and the degree of FMR1 silencing. Our data uncover higher-order chromatin architecture as a new dimension in understanding repeat expansion disorders.

Polymerization of ZBTB transcription factors regulates chromatin occupancy.

BCL6, an oncogenic transcription factor (TF), forms polymers in the presence of a small-molecule molecular glue that stabilizes a complementary interface between homodimers of BCL6's broad-complex, tramtrack, and bric-à-brac (BTB) domain. The BTB domains of other proteins, including a large class of TFs, have similar architectures and symmetries, raising the possibility that additional BTB proteins self-assemble into higher-order structures. Here, we surveyed 189 human BTB proteins with a cellular fluorescent reporter assay and identified 18 ZBTB TFs that show evidence of polymerization. Through biochemical and cryoelectron microscopy (cryo-EM) studies, we demonstrate that these ZBTB TFs polymerize into filaments. We found that BTB-domain-mediated polymerization of ZBTB TFs enhances chromatin occupancy within regions containing homotypic clusters of TF binding sites, leading to repression of target genes. Our results reveal a role of higher-order structures in regulating ZBTB TFs and suggest an underappreciated role for TF polymerization in modulating gene expression.

Cryoelectron tomography reveals the multiplex anatomy of condensed native chromatin and its unfolding by histone citrullination.

Nucleosome chains fold and self-associate to form higher-order structures whose internal organization is unknown. Here, cryoelectron tomography (cryo-ET) of native human chromatin reveals intrinsic folding motifs such as (1) non-uniform nucleosome stacking, (2) intermittent parallel and perpendicular orientations of adjacent nucleosome planes, and (3) a regressive nucleosome chain path, which deviates from the direct zigzag topology seen in reconstituted nucleosomal arrays. By examining the self-associated structures, we observed prominent nucleosome stacking in cis and anti-parallel nucleosome interactions, which are consistent with partial nucleosome interdigitation in trans. Histone citrullination strongly inhibits nucleosome stacking and self-association with a modest effect on chromatin folding, whereas the reconstituted arrays undergo a dramatic unfolding into open zigzag chains induced by histone citrullination. This study sheds light on the internal structure of compact chromatin nanoparticles and suggests a mechanism for how epigenetic changes in chromatin folding are retained across both open and condensed forms.

Higher-order SPOP assembly reveals a basis for cancer mutant dysregulation.

The speckle-type POZ protein (SPOP) functions in the Cullin3-RING ubiquitin ligase (CRL3) as a receptor for the recognition of substrates involved in cell growth, survival, and signaling. SPOP mutations have been attributed to the development of many types of cancers, including prostate and endometrial cancers. Prostate cancer mutations localize in the substrate-binding site of the substrate recognition (MATH) domain and reduce or prevent binding. However, most endometrial cancer mutations are dispersed in seemingly inconspicuous solvent-exposed regions of SPOP, offering no clear basis for their cancer-causing and peculiar gain-of-function properties. Herein, we present the first structure of SPOP in its oligomeric form, uncovering several new interfaces important for SPOP self-assembly and normal function. Given that many previously unaccounted-for cancer mutations are localized in these newly identified interfaces, we uncover molecular mechanisms underlying dysregulation of SPOP function, with effects ranging from gross structural changes to enhanced self-association, and heightened stability and activity.

E3 ligase autoinhibition by C-degron mimicry maintains C-degron substrate fidelity.

E3 ligase recruitment of proteins containing terminal destabilizing motifs (degrons) is emerging as a major form of regulation. How those E3s discriminate bona fide substrates from other proteins with terminal degron-like sequences remains unclear. Here, we report that human KLHDC2, a CRL2 substrate receptor targeting C-terminal Gly-Gly degrons, is regulated through interconversion between two assemblies. In the self-inactivated homotetramer, KLHDC2's C-terminal Gly-Ser motif mimics a degron and engages the substrate-binding domain of another protomer. True substrates capture the monomeric CRL2KLHDC2, driving E3 activation by neddylation and subsequent substrate ubiquitylation. Non-substrates such as NEDD8 bind KLHDC2 with high affinity, but its slow on rate prevents productive association with CRL2KLHDC2. Without substrate, neddylated CRL2KLHDC2 assemblies are deactivated via distinct mechanisms: the monomer by deneddylation and the tetramer by auto-ubiquitylation. Thus, substrate specificity is amplified by KLHDC2 self-assembly acting like a molecular timer, where only bona fide substrates may bind before E3 ligase inactivation.

Hybridization-proximity labeling reveals spatially ordered interactions of nuclear RNA compartments.

The ability of RNAs to form specific contacts with other macromolecules provides an important mechanism for subcellular compartmentalization. Here we describe a suite of hybridization-proximity (HyPro) labeling technologies for unbiased discovery of proteins (HyPro-MS) and transcripts (HyPro-seq) associated with RNAs of interest in genetically unperturbed cells. As a proof of principle, we show that HyPro-MS and HyPro-seq can identify both known and previously unexplored spatial neighbors of the noncoding RNAs 45S, NEAT1, and PNCTR expressed at markedly different levels. Notably, HyPro-seq uncovers an extensive repertoire of incompletely processed, adenosine-to-inosine-edited transcripts accumulating at the interface between their encoding chromosomal regions and the NEAT1-containing paraspeckle compartment. At least some of these targets require NEAT1 for their optimal expression. Overall, this study provides a versatile toolkit for dissecting RNA interactomes in diverse biomedical contexts and expands our understanding of the functional architecture of the mammalian nucleus.

Cryo-EM analyses of dimerized spliceosomes provide new insights into the functions of B complex proteins.

The B complex is a key intermediate stage of spliceosome assembly. To improve the structural resolution of monomeric, human spliceosomal B (hB) complexes and thereby generate a more comprehensive hB molecular model, we determined the cryo-EM structure of B complex dimers formed in the presence of ATP γ S. The enhanced resolution of these complexes allows a finer molecular dissection of how the 5' splice site (5'ss) is recognized in hB, and new insights into molecular interactions of FBP21, SNU23 and PRP38 with the U6/5'ss helix and with each other. It also reveals that SMU1 and RED are present as a heterotetrameric complex and are located at the interface of the B dimer protomers. We further show that MFAP1 and UBL5 form a 5' exon binding channel in hB, and elucidate the molecular contacts stabilizing the 5' exon at this stage. Our studies thus yield more accurate models of protein and RNA components of hB complexes. They further allow the localization of additional proteins and protein domains (such as SF3B6, BUD31 and TCERG1) whose position was not previously known, thereby uncovering new functions for B-specific and other hB proteins during pre-mRNA splicing.

The Nuclear Matrix Protein SAFB Cooperates with Major Satellite RNAs to Stabilize Heterochromatin Architecture Partially through Phase Separation.

Interphase chromatin is hierarchically organized into higher-order architectures that are essential for gene functions, yet the biomolecules that regulate these 3D architectures remain poorly understood. Here, we show that scaffold attachment factor B (SAFB), a nuclear matrix (NM)-associated protein with RNA-binding functions, modulates chromatin condensation and stabilizes heterochromatin foci in mouse cells. SAFB interacts via its R/G-rich region with heterochromatin-associated repeat transcripts such as major satellite RNAs, which promote the phase separation driven by SAFB. Depletion of SAFB leads to changes in 3D genome organization, including an increase in interchromosomal interactions adjacent to pericentromeric heterochromatin and a decrease in genomic compartmentalization, which could result from the decondensation of pericentromeric heterochromatin. Collectively, we reveal the integrated roles of NM-associated proteins and repeat RNAs in the 3D organization of heterochromatin, which may shed light on the molecular mechanisms of nuclear architecture organization.

Developmental emergence of first- and higher-order thalamic neuron molecular identities.

The thalamus is organized into nuclei that have distinct input and output connectivities with the cortex. Whereas first-order (FO) nuclei - also called core nuclei - relay input from sensory organs on the body surface and project to primary cortical sensory areas, higher-order (HO) nuclei - matrix nuclei - instead receive their driver input from the cortex and project to secondary and associative areas within cortico-thalamo-cortical loops. Input-dependent processes have been shown to play a crucial role in the emergence of FO thalamic neuron identity from a ground-state HO neuron identity, yet how this identity emerges during development remains unknown. Here, using single-cell RNA sequencing of the developing mouse embryonic thalamus, we show that, although they are born together, HO neurons start differentiating earlier than FO neurons. Within the FO visual thalamus, postnatal peripheral input is crucial for the maturation of excitatory, but not inhibitory, neurons. Our findings reveal different differentiation tempos and input sensitivities of HO and FO neurons, and highlight neuron type-specific molecular differentiation programs in the developing thalamus.

Gene-Specific H1 Eviction through a Transcriptional Activator→p300→NAP1→H1 Pathway.

Linker histone H1 has been correlated with transcriptional inhibition, but the mechanistic basis of the inhibition and its reversal during gene activation has remained enigmatic. We report that H1-compacted chromatin, reconstituted in vitro, blocks transcription by abrogating core histone modifications by p300 but not activator and p300 binding. Transcription from H1-bound chromatin is elicited by the H1 chaperone NAP1, which is recruited in a gene-specific manner through direct interactions with activator-bound p300 that facilitate core histone acetylation (by p300) and concomitant eviction of H1 and H2A-H2B. An analysis in B cells confirms the strong dependency on NAP1-mediated H1 eviction for induction of the silent CD40 gene and further demonstrates that H1 eviction, seeded by activator-p300-NAP1-H1 interactions, is propagated over a CCCTC-binding factor (CTCF)-demarcated region through a distinct mechanism that also involves NAP1. Our results confirm direct transcriptional inhibition by H1 and establish a gene-specific H1 eviction mechanism through an activator→p300→NAP1→H1 pathway.

Higher-order homophily on simplicial complexes.

Higher-order network models are becoming increasingly relevant for their ability to explicitly capture interactions between three or more entities in a complex system at once. In this paper, we study homophily, the tendency for alike individuals to form connections, as it pertains to higher-order interactions. We find that straightforward extensions of classical homophily measures to interactions of size 3 and larger are often inflated by homophily present in pairwise interactions. This inflation can even hide the presence of anti-homophily in higher-order interactions. Hence, we develop a structural measure of homophily, simplicial homophily, which decouples homophily in pairwise interactions from that of higher-order interactions. The definition applies when the network can be modeled as a simplicial complex, a mathematical abstraction which makes a closure assumption that for any higher-order relationship in the network, all corresponding subsets of that relationship occur in the data. Whereas previous work has used this closure assumption to develop a rich theory in algebraic topology, here we use the assumption to make empirical comparisons between interactions of different sizes. The simplicial homophily measure is validated theoretically using an extension of a stochastic block model for simplicial complexes and empirically in large-scale experiments across 16 datasets. We further find that simplicial homophily can be used to identify when node features are valuable for higher-order link prediction. Ultimately, this highlights a subtlety in studying node features in higher-order networks, as measures defined on groups of size k can inherit features described by interactions of size [Formula: see text].

Nonlinear bias toward complex contagion in uncertain transmission settings.

Current epidemics in the biological and social domains are challenging the standard assumptions of mathematical contagion models. Chief among them are the complex patterns of transmission caused by heterogeneous group sizes and infection risk varying by orders of magnitude in different settings, like indoor versus outdoor gatherings in the COVID-19 pandemic or different moderation practices in social media communities. However, quantifying these heterogeneous levels of risk is difficult, and most models typically ignore them. Here, we include these features in an epidemic model on weighted hypergraphs to capture group-specific transmission rates. We study analytically the consequences of ignoring the heterogeneous transmissibility and find an induced superlinear infection rate during the emergence of a new outbreak, even though the underlying mechanism is a simple, linear contagion. The dynamics produced at the individual and group levels are therefore more similar to complex, nonlinear contagions, thus blurring the line between simple and complex contagions in realistic settings. We support this claim by introducing a Bayesian inference framework to quantify the nonlinearity of contagion processes. We show that simple contagions on real weighted hypergraphs are systematically biased toward the superlinear regime if the heterogeneity of the weights is ignored, greatly increasing the risk of erroneous classification as complex contagions. Our results provide an important cautionary tale for the challenging task of inferring transmission mechanisms from incidence data. Yet, it also paves the way for effective models that capture complex features of epidemics through nonlinear infection rates.

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we have proposed a simple framework that incorporates higher-order interactions into a bottom-up prediction of the microbial community assembly and examined its accuracy using a seven-member synthetic bacterial community on a host plant, duckweed. Although the synthetic community exhibited emergent properties that cannot be predicted from pairwise coculturing results, our results demonstrated that incorporating information from three-member combinations allows the acceptable prediction of the community structure and actual interaction forces within it. This reflects that the occurrence of higher-order effects follows consistent patterns, which can be predicted even from trio combinations, the smallest unit of higher-order interactions. These results highlight the possibility of predicting, explaining, and understanding the microbial community structure from the bottom-up by learning interspecies interactions from simple beyond-pairwise combinations.

Frequent winners explain apparent skewness preferences in experience-based decisions.

Do people's attitudes toward the (a)symmetry of an outcome distribution affect their choices? Financial investors seek return distributions with frequent small returns but few large ones, consistent with leading models of choice in economics and finance that assume right-skewed preferences. In contrast, many experiments in which decision-makers learn about choice options through experience find the opposite choice tendency, in favor of left-skewed options. To reconcile these seemingly contradicting findings, the present work investigates the effect of skewness on choices in experience-based decisions. Across seven studies, we show that apparent preferences for left-skewed outcome distributions are a consequence of those distributions having a higher value in most direct outcome comparisons, a "frequent-winner effect." By manipulating which option is the frequent winner, we show that choice tendencies for frequent winners can be obtained even with identical outcome distributions. Moreover, systematic choice tendencies in favor of right- or left-skewed options can be obtained by manipulating which option is experienced as the frequent winner. We also find evidence for an intrinsic preference for right-skewed outcome distributions. The frequent-winner phenomenon is robust to variations in outcome distributions and experimental paradigms. These findings are confirmed by computational analyses in which a reinforcement-learning model capturing frequent winning and intrinsic skewness preferences provides the best account of the data. Our work reconciles conflicting findings of aggregated behavior in financial markets and experiments and highlights the need for theories of decision-making sensitive to joint outcome distributions of the available options.

HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction.

Numerous studies have demonstrated that microRNAs (miRNAs) are critically important for the prediction, diagnosis, and characterization of diseases. However, identifying miRNA-disease associations through traditional biological experiments is both costly and time-consuming. To further explore these associations, we proposed a model based on hybrid high-order moments combined with element-level attention mechanisms (HHOMR). This model innovatively fused hybrid higher-order statistical information along with structural and community information. Specifically, we first constructed a heterogeneous graph based on existing associations between miRNAs and diseases. HHOMR employs a structural fusion layer to capture structure-level embeddings and leverages a hybrid high-order moments encoder layer to enhance features. Element-level attention mechanisms are then used to adaptively integrate the features of these hybrid moments. Finally, a multi-layer perceptron is utilized to calculate the association scores between miRNAs and diseases. Through five-fold cross-validation on HMDD v2.0, we achieved a mean AUC of 93.28%. Compared with four state-of-the-art models, HHOMR exhibited superior performance. Additionally, case studies on three diseases-esophageal neoplasms, lymphoma, and prostate neoplasms-were conducted. Among the top 50 miRNAs with high disease association scores, 46, 47, and 45 associated with these diseases were confirmed by the dbDEMC and miR2Disease databases, respectively. Our results demonstrate that HHOMR not only outperforms existing models but also shows significant potential in predicting miRNA-disease associations.