Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations.

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Ordered assembly of the cytosolic RNA-sensing MDA5-MAVS signaling complex via binding to unanchored K63-linked poly-ubiquitin chains.

The RNA sensor MDA5 recruits the signaling adaptor MAVS to initiate type I interferon signaling and downstream antiviral responses, a process that requires K63-linked polyubiquitin chains. Here, we examined the mechanisms whereby K63-polyUb chain regulate MDA5 activation. Only long unanchored K63-polyUbn (n ≥ 8) could mediate tetramerization of the caspase activation and recruitment domains of MDA5 (MDA5CARDs). Cryoelectron microscopy structures of a polyUb13-bound MDA5CARDs tetramer and a polyUb11-bound MDA5CARDs-MAVSCARD assembly revealed a tower-like formation, wherein eight Ubs tethered along the outer rim of the helical shell, bridging MDA5CARDs and MAVSCARD tetramers into proximity. ATP binding and hydrolysis promoted the stabilization of RNA-bound MDA5 prior to MAVS activation via allosteric effects on CARDs-polyUb complex. Abundant ATP prevented basal activation of apo MDA5. Our findings reveal the ordered assembly of a MDA5 signaling complex competent to recruit and activate MAVS and highlight differences with RIG-I in terms of CARD orientation and Ub sensing that suggest different abilities to induce antiviral responses.

Hormone- and antibody-mediated activation of the thyrotropin receptor.

Thyroid-stimulating hormone (TSH), through activation of its G-protein-coupled thyrotropin receptor (TSHR), controls the synthesis of thyroid hormone-an essential metabolic hormone1-3. Aberrant signalling of TSHR by autoantibodies causes Graves' disease (hyperthyroidism) and hypothyroidism, both of which affect millions of patients worldwide4. Here we report the active structures of TSHR with TSH and the activating autoantibody M225, both bound to the allosteric agonist ML-1096, as well as an inactivated TSHR structure with the inhibitory antibody K1-707. Both TSH and M22 push the extracellular domain (ECD) of TSHR into an upright active conformation. By contrast, K1-70 blocks TSH binding and cannot push the ECD into the upright conformation. Comparisons of the active and inactivated structures of TSHR with those of the luteinizing hormone/choriogonadotropin receptor (LHCGR) reveal a universal activation mechanism of glycoprotein hormone receptors, in which a conserved ten-residue fragment (P10) from the hinge C-terminal loop mediates ECD interactions with the TSHR transmembrane domain8. One notable feature is that there are more than 15 cholesterols surrounding TSHR, supporting its preferential location in lipid rafts9. These structures also highlight a similar ECD-push mechanism for TSH and autoantibody M22 to activate TSHR, therefore providing the molecular basis for Graves' disease.

Dominant activities of fear engram cells in the dorsal dentate gyrus underlie fear generalization in mice.

Over-generalized fear is a maladaptive response to harmless stimuli or situations characteristic of posttraumatic stress disorder (PTSD) and other anxiety disorders. The dorsal dentate gyrus (dDG) contains engram cells that play a crucial role in accurate memory retrieval. However, the coordination mechanism of neuronal subpopulations within the dDG network during fear generalization is not well understood. Here, with the Tet-off system combined with immunostaining and two-photon calcium imaging, we report that dDG fear engram cells labeled in the conditioned context constitutes a significantly higher proportion of dDG neurons activated in a similar context where mice show generalized fear. The activation of these dDG fear engram cells encoding the conditioned context is both sufficient and necessary for inducing fear generalization in the similar context. Activities of mossy cells in the ventral dentate gyrus (vMCs) are significantly suppressed in mice showing fear generalization in a similar context, and activating the vMCs-dDG pathway suppresses generalized but not conditioned fear. Finally, modifying fear memory engrams in the dDG with "safety" signals effectively rescues fear generalization. These findings reveal that the competitive advantage of dDG engram cells underlies fear generalization, which can be rescued by activating the vMCs-dDG pathway or modifying fear memory engrams, and provide novel insights into the dDG network as the neuronal basis of fear generalization.

Charge barriers in the kidney elimination of engineered nanoparticles.

The renal elimination pathway is increasingly harnessed to reduce nonspecific accumulation of engineered nanoparticles within the body and expedite their clinical applications. While the size of nanoparticles is recognized as crucial for their passive filtration through the glomerulus due to its limited pore size, the influence of nanoparticle charge on their transport and interactions within the kidneys remains largely elusive. Herein, we report that the proximal tubule and peritubular capillary, rather than the glomerulus, serve as primary charge barriers to the transport of charged nanoparticles within the kidney. Employing a series of ultrasmall, renal-clearable gold nanoparticles (AuNPs) with precisely engineered surface charge characteristics as multimodal imaging agents, we have tracked their distribution and retention across various kidney components following intravenous administration. Our results reveal that retention in the proximal tubules is governed not by the nanoparticle's zeta-potential, but by direct Coulombic interactions between the positively charged surface ligands of the AuNPs and the negatively charged microvilli of proximal tubules. However, further enhancing these interactions leads to increased binding of the positively charged AuNPs to the peritubular capillaries during the initial phase of elimination, subsequently facilitating their slow passage through the glomeruli and interaction with tubular components in a charge-selective manner. By identifying these two critical charge-dependent barriers in the renal transport of nanoparticles, our findings offer a fundamental insight for the design of renal nanomedicines tailored for selective targeting within the kidney, laying down a foundation for developing targeting renal nanomedicines for future kidney disease management in the clinics.

The intrinsically disordered CARDs-Helicase linker in RIG-I is a molecular gate for RNA proofreading.

The innate immune receptor RIG-I provides a first line of defense against viral infections. Viral RNAs are recognized by RIG-I's C-terminal domain (CTD), but the RNA must engage the helicase domain to release the signaling CARD (Caspase Activation and Recruitment Domain) domains from their autoinhibitory CARD2:Hel2i interactions. Because the helicase itself lacks RNA specificity, mechanisms to proofread RNAs entering the helicase domain must exist. Although such mechanisms would be crucial in preventing aberrant immune responses by non-specific RNAs, they remain largely uncharacterized to date. This study reveals a previously unknown proofreading mechanism through which RIG-I ensures that the helicase engages RNAs explicitly recognized by the CTD. A crucial part of this mechanism involves the intrinsically disordered CARDs-Helicase Linker (CHL), which connects the CARDs to the helicase subdomain Hel1. CHL uses its negatively charged regions to antagonize incoming RNAs electrostatically. In addition to this RNA gating function, CHL is essential for stabilization of the CARD2:Hel2i interface. Overall, we uncover that the CHL and CARD2:Hel2i interface work together to establish a tunable gating mechanism that allows CTD-chosen RNAs to bind the helicase domain, while at the same time blocking non-specific RNAs. These findings also indicate that CHL could represent a novel target for RIG-I-based therapeutics.

Integrating pH into the metabolic theory of ecology to predict bacterial diversity in soil.

Microorganisms play essential roles in soil ecosystem functioning and maintenance, but methods are currently lacking for quantitative assessments of the mechanisms underlying microbial diversity patterns observed across disparate systems and scales. Here we established a quantitative model to incorporate pH into metabolic theory to capture and explain some of the unexplained variation in the relationship between temperature and soil bacterial diversity. We then tested and validated our newly developed models across multiple scales of ecological organization. At the species level, we modeled the diversification rate of the model bacterium Pseudomonas fluorescens evolving under laboratory media gradients varying in temperature and pH. At the community level, we modeled patterns of bacterial communities in paddy soils across a continental scale, which included natural gradients of pH and temperature. Last, we further extended our model at a global scale by integrating a meta-analysis comprising 870 soils collected worldwide from a wide range of ecosystems. Our results were robust in consistently predicting the distributional patterns of bacterial diversity across soil temperature and pH gradients-with model variation explaining from 7 to 66% of the variation in bacterial diversity, depending on the scale and system complexity. Together, our study represents a nexus point for the integration of soil bacterial diversity and quantitative models with the potential to be used at distinct spatiotemporal scales. By mechanistically representing pH into metabolic theory, our study enhances our capacity to explain and predict the patterns of bacterial diversity and functioning under current or future climate change scenarios.

Genetic basis of I-complex plasmid stability and conjugation.

Plasmids are major drivers of increasing antibiotic resistance, necessitating an urgent need to understand their biology. Here we describe a detailed dissection of the molecular components controlling the genetics of I-complex plasmids, a group of antibiotic resistance plasmids found frequently in pathogenic Escherichia coli and other Enterobacteriaceae that cause significant human disease. We show these plasmids cluster into four distinct subgroups, with the prototype IncI1 plasmid R64 subgroup displaying low nucleotide sequence conservation to other I-complex plasmids. Using pMS7163B, an I-complex plasmid distantly related to R64, we performed a high-resolution transposon-based genetic screen and defined genes involved in replication, stability, and conjugative transfer. We identified the replicon and a partitioning system as essential for replication/stability. Genes required for conjugation included the type IV secretion system, relaxosome, and several uncharacterised genes located in the pMS7163B leading transfer region that exhibited an upstream strand-specific transposon insertion bias. The overexpression of these genes severely impacted host cell growth or reduced fitness during mixed competitive growth, demonstrating that their expression must be controlled to avoid deleterious impacts. These genes were present in >80% of all I-complex plasmids and broadly conserved across multiple plasmid incompatibility groups, implicating an important role in plasmid dissemination.

ExosomePurity: tumour purity deconvolution in serum exosomes based on miRNA signatures.

Exosomes cargo tumour-characterized biomolecules secreted from cancer cells and play a pivotal role in tumorigenesis and cancer progression, thus providing their potential for non-invasive cancer monitoring. Since cancer cell-derived exosomes are often mixed with those from healthy cells in liquid biopsy of tumour patients, accurately measuring the purity of tumour cell-derived exosomes is not only critical for the early detection but also essential for unbiased identification of diagnosis biomarkers. Here, we propose 'ExosomePurity', a tumour purity deconvolution model to estimate tumour purity in serum exosomes of cancer patients based on microribonucleic acid (miRNA)-Seq data. We first identify the differently expressed miRNAs as signature to distinguish cancer cell- from healthy cell-derived exosomes. Then, the deconvolution model was developed to estimate the proportions of cancer exosomes and normal exosomes in serum. The purity predicted by the model shows high correlation with actual purity in simulated data and actual data. Moreover, the model is robust under the different levels of noise background. The tumour purity was also used to correct differential expressed gene analysis. ExosomePurity empowers the research community to study non-invasive early diagnosis and to track cancer progression in cancers more efficiently. It is implemented in R and is freely available from GitHub (https://github.com/WangHYLab/ExosomePurity).

SL-Miner: a web server for mining evidence and prioritization of cancer-specific synthetic lethality.

SUMMARY: Synthetic lethality (SL) refers to a type of genetic interaction in which the simultaneous inactivation of two genes leads to cell death, while the inactivation of a single gene does not affect cell viability. It significantly expands the range of potential therapeutic targets for anti-cancer treatments. SL interactions are primarily identified through experimental screening and computational prediction. Although various computational methods have been proposed, they tend to ignore providing evidence to support their predictions of SL. Besides, they are rarely user-friendly for biologists who likely have limited programming skills. Moreover, the genetic context specificity of SL interactions is often not taken into consideration. Here, we introduce a web server called SL-Miner, which is designed to mine the evidence of SL relationships between a primary gene and a few candidate SL partner genes in a specific type of cancer, and to prioritize these candidate genes by integrating various types of evidence. For intuitive data visualization, SL-Miner provides a range of charts (e.g. volcano plot and box plot) to help users get insights from the data. AVAILABILITY AND IMPLEMENTATION: SL-Miner is available at https://slminer.sist.shanghaitech.edu.cn.

TEFDTA: a transformer encoder and fingerprint representation combined prediction method for bonded and non-bonded drug-target affinities.

MOTIVATION: The prediction of binding affinity between drug and target is crucial in drug discovery. However, the accuracy of current methods still needs to be improved. On the other hand, most deep learning methods focus only on the prediction of non-covalent (non-bonded) binding molecular systems, but neglect the cases of covalent binding, which has gained increasing attention in the field of drug development. RESULTS: In this work, a new attention-based model, A Transformer Encoder and Fingerprint combined Prediction method for Drug-Target Affinity (TEFDTA) is proposed to predict the binding affinity for bonded and non-bonded drug-target interactions. To deal with such complicated problems, we used different representations for protein and drug molecules, respectively. In detail, an initial framework was built by training our model using the datasets of non-bonded protein-ligand interactions. For the widely used dataset Davis, an additional contribution of this study is that we provide a manually corrected Davis database. The model was subsequently fine-tuned on a smaller dataset of covalent interactions from the CovalentInDB database to optimize performance. The results demonstrate a significant improvement over existing approaches, with an average improvement of 7.6% in predicting non-covalent binding affinity and a remarkable average improvement of 62.9% in predicting covalent binding affinity compared to using BindingDB data alone. At the end, the potential ability of our model to identify activity cliffs was investigated through a case study. The prediction results indicate that our model is sensitive to discriminate the difference of binding affinities arising from small variances in the structures of compounds. AVAILABILITY AND IMPLEMENTATION: The codes and datasets of TEFDTA are available at https://github.com/lizongquan01/TEFDTA.

Growth characteristics of HCT116 xenografts lacking asparagine synthetase vary according to sex.

BACKGROUND: Sex-related differences in colorectal (CRC) incidence and mortality are well-documented. However, the impact of sex on metabolic pathways that drive cancer growth is not well understood. High expression of asparagine synthetase (ASNS) is associated with inferior survival for female CRC patients only. Here, we used a CRISPR/Cas9 technology to generate HCT116 ASNS-/- and HCT 116 ASNS+/+ cancer cell lines. We examine the effects of ASNS deletion on tumor growth and the subsequent rewiring of metabolic pathways in male and female Rag2/IL2RG mice. RESULTS: ASNS loss reduces cancer burden in male and female tumor-bearing mice (40% reduction, q < 0.05), triggers metabolic reprogramming including gluconeogenesis, but confers a survival improvement (30 days median survival, q < 0.05) in female tumor-bearing mice alone. Transcriptomic analyses revealed upregulation of G-protein coupled estrogen receptor (GPER1) in tumors from male and female mice with HCT116 ASNS-/- xenograft. Estradiol activates GPER1 in vitro in the presence of ASNS and suppresses tumor growth. CONCLUSIONS: Our study indicates that inferior survival for female CRC patients with high ASNS may be due to metabolic reprogramming that sustains tumor growth. These findings have translational relevance as ASNS/GPER1 signaling could be a future therapeutic target to improve the survival of female CRC patients.

A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis.

BACKGROUND: 'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056). RESULTS: We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null. CONCLUSION: Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.

Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

DNA-Directed Assembly of Hierarchical MOF-Cellulose Nanofiber Microbioreactors with "Branch-Fruit" Structures.

Assembling metal-organic frameworks (MOFs) into ordered multidimensional porous superstructures promises the encapsulation of enzymes for heterogeneous biocatalysts. However, the full potential of this approach has been limited by the poor stability of enzymes and the uncontrolled assembly of MOF nanoparticles onto suitable supports. In this study, a novel and exceptionally robust Ni-imidazole-based MOF was synthesized in water at room temperature, enabling in situ enzyme encapsulation. Based on this MOF platform, we developed a DNA-directed assembly strategy to achieve the uniform placement of MOF nanoparticles onto bacterial cellulose nanofibers, resulting in a distinctive "branch-fruit" structure. The resulting hybrid materials demonstrated remarkable versatility across various catalytic systems, accommodating natural enzymes, nanoenzymes, and multienzyme cascades, thus showcasing enormous potential as universal microbioreactors. Furthermore, the hierarchical composites facilitated rapid diffusion of the bulky substrate while maintaining the enzyme stability, with ∼3.5-fold higher relative activity compared to the traditional enzyme@MOF immobilized in bacterial cellulose nanofibers.

Layered Ferromagnetic Structure Caused by the Proximity Effect and Interlayer Charge Transfer for LaNiO3/LaMnO3 Superlattices.

Magnetic proximity-induced magnetism in paramagnetic LaNiO3 (LNO) has spurred intensive investigations in the past decade. However, no consensus has been reached so far regarding the magnetic order in LNO layers in relevant heterostructures. This paper reports a layered ferromagnetic structure for the (111)-oriented LNO/LaMnO3 (LMO) superlattices. It is found that each period of the superlattice consisted of an insulating LNO-interfacial phase (five unit cells in thickness, ∼1.1 nm), a metallic LNO-inner phase, a poorly conductive LMO-interfacial phase (three unit cells in thickness, ∼0.7 nm), and an insulating LMO-inner phase. All four of these phases are ferromagnetic, showing different magnetizations. The Mn-to-Ni interlayer charge transfer is responsible for the emergence of a layered magnetic structure, which may cause magnetic interaction across the LNO/LMO interface and double exchange within the LMO-interfacial layer. This work indicates that the proximity effect is an effective means of manipulating the magnetic state and associated properties of complex oxides.

Interface Engineering of the Cu1.5Mn1.5O4/CeO2 Heterostructure for Highly Efficient Electrocatalytic Nitrate Reduction to Ammonia.

The electrochemical nitrate reduction reaction (NO3RR) is considered a sustainable technology to convert the nitrate pollutants to ammonia. However, developing highly efficient electrocatalysts is necessary and challenging given the slow kinetics of the NO3RR with an eight-electron transfer process. Here, a Cu1.5Mn1.5O4 (CMO)/CeO2 heterostructure with rich interfaces is designed and fabricated through an electrospinning and postprocessing technique. Benefiting from the strong coupling between CMO and CeO2, the optimized CMO/CeO2-2 catalyst presents excellent NO3RR performance, with NH3 Faraday efficiency (FE) up to 93.07 ± 1.45% at -0.481 V vs reversible hydrogen electrode (RHE) and NH3 yield rate up to 48.06 ± 1.32 mg cm-2 h-1 at -0.681 V vs RHE. Theoretical calculations demonstrate that the integration of CeO2 with CMO modulates the adsorption/desorption process of the reactants and intermediates, showing a reduced energy barrier in the rate determination step of NO* to N* and achieving an outstanding NO3RR performance.

How much does TRPV1 deviate from an ideal MWC-type protein?

Many ion channels are known to behave as an allosteric protein, coupling environmental stimuli captured by specialized sensing domains to the opening of a central pore. The classic Monod-Wyman-Changeux (MWC) model, originally proposed to describe binding of gas molecules to hemoglobin, has been widely used as a framework for analyzing ion channel gating. Here, we address the issue of how accurately the MWC model predicts activation of the capsaicin receptor TRPV1 by vanilloids. Taking advantage of a concatemeric design that makes it possible to lock TRPV1 in states with zero to four bound vanilloid molecules, we showed quantitatively that the overall gating behavior is satisfactorily predicted by the MWC model. There is, however, a small yet detectable subunit position effect: ligand binding to two kitty-corner subunits is 0.3-0.4 kcal/mol more effective in inducing opening than binding to two neighbor subunits. This difference-less than 10% of the overall energetic contribution from ligand binding-might be due to the restriction on subunit arrangement imposed by the planar membrane; if this is the case, then the position effect is not expected in hemoglobin, in which each subunit is related equivalently to all the other subunits.

The capsaicin binding affinity of wildtype and mutant TRPV1 ion channels.

Vanilloids such as capsaicin and resiniferatoxin are highly selective and potent activators for transient receptor potential vanilloid subfamily, member 1, a nociceptor for heat and pain perception. However, the intrinsic vanilloid binding affinity, key for understanding transient receptor potential vanilloid subfamily, member 1 function, remains unknown despite intensive investigations by electrophysiological, structural, and computational methods. In this study, we determined capsaicin binding affinity under physiological conditions by isolating individual binding steps to each subunit with concatemers. We estimated the capsaicin association constant of a wildtype subunit to be in the order of 106 M-1 and that of the Y511A mutant subunit to be a hundred times lower, in the order of 104 M-1. The Y511A mutation, located at the entrance of the vanilloid binding pocket, reduces binding affinity without a noticeable effect on activation gating. We further affirmed that there is little cooperativity between vanilloid binding steps. Models based on independent binding and equally cooperative subunit gating can accurately describe capsaicin activation.