Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Computational design and engineering of self-assembling multivalent microproteins with therapeutic potential against SARS-CoV-2.

Multivalent drugs targeting homo-oligomeric viral surface proteins, such as the SARS-CoV-2 trimeric spike (S) protein, have the potential to elicit more potent and broad-spectrum therapeutic responses than monovalent drugs by synergistically engaging multiple binding sites on viral targets. However, rational design and engineering of nanoscale multivalent protein drugs are still lacking. Here, we developed a computational approach to engineer self-assembling trivalent microproteins that simultaneously bind to the three receptor binding domains (RBDs) of the S protein. This approach involves four steps: structure-guided linker design, molecular simulation evaluation of self-assembly, experimental validation of self-assembly state, and functional testing. Using this approach, we first designed trivalent constructs of the microprotein miniACE2 (MP) with different trimerization scaffolds and linkers, and found that one of the constructs (MP-5ff) showed high trimerization efficiency, good conformational homogeneity, and strong antiviral neutralizing activity. With its trimerization unit (5ff), we then engineered a trivalent nanobody (Tr67) that exhibited potent and broad neutralizing activity against the dominant Omicron variants, including XBB.1 and XBB.1.5. Cryo-EM complex structure confirmed that Tr67 stably binds to all three RBDs of the Omicron S protein in a synergistic form, locking them in the "3-RBD-up" conformation that could block human receptor (ACE2) binding and potentially facilitate immune clearance. Therefore, our approach provides an effective strategy for engineering potent protein drugs against SARS-CoV-2 and other deadly coronaviruses.

Structure-guided design of a trivalent nanobody cluster targeting SARS-CoV-2 spike protein.

Nanobodies are natural anti-SARS-CoV-2 drug candidates. Engineering multivalent nanobodies is an effective way to improve the functional binding affinity of natural nanobodies by simultaneously targeting multiple sites on viral proteins. However, multivalent nanobodies have usually been engineered by trial and error, and rational designs are still lacking. Here, we describe a structure-guided design of a self-assembled trivalent nanobody cluster targeting the SARS-CoV-2 spike protein. Using the nanobody Nb6 as a monovalent binder, we first selected a human-derived trimerization scaffold evaluated by molecular dynamics simulations, then selected an optimal linker according to the minimum distance between Nb6 and the trimerization scaffold, and finally successfully engineered a trivalent nanobody cluster called Tribody. Compared with the low-affinity monovalent counterpart (Nb6), Tribody showed much higher target binding affinity (KD < 1 pM) and thus had a 900-fold increase in antiviral neutralization against SARS-CoV-2 pseudovirus. We determined the cryo-EM structure of the Tribody-spike complex and confirmed that all three Nb6 binders of Tribody collectively bind to the three receptor-binding domains (RBDs) of the spike and lock them in a 3-RBD-down conformation, fully consistent with our structure-guided design. This study demonstrates that synthetic nanobody clusters with human-derived self-assembled scaffolds are potential protein drugs against SARS-CoV-2 coronaviruses.

Full-Length Model of SaCas9-sgRNA-DNA Complex in Cleavage State.

Staphylococcus aureus Cas9 (SaCas9) is a widely used genome editing tool. Understanding its molecular mechanisms of DNA cleavage could effectively guide the engineering optimization of this system. Here, we determined the first cryo-electron microscopy structure of the SaCas9-sgRNA-DNA ternary complex. This structure reveals that the HNH nuclease domain is tightly bound to the cleavage site of the target DNA strand, and is in close contact with the WED and REC domains. Moreover, it captures the complete structure of the sgRNA, including the previously unresolved stem-loop 2. Based on this structure, we build a full-length model for the ternary complex in cleavage state. This model enables identification of the residues for the interactions between the HNH domain and the WED and REC domains. Moreover, we found that the stem-loop 2 of the sgRNA tightly binds to the PI and RuvC domains and may also regulate the position shift of the RuvC domain. Further mutagenesis and molecular dynamics simulations supported the idea that the interactions of the HNH domain with the WED and REC domains play an important role in the DNA cleavage. Thus, this study provides new mechanistic insights into the DNA cleavage of SaCas9 and is also useful for guiding the future engineering of SaCas9-mediated gene editing systems.

The adaptability of H9N2 avian influenza A virus to humans: A comparative docking simulation study.

Influenza A virus, the H9N2 subtype, is an avian influenza virus that has long been circulating in the worldwide poultry industry and is occasionally found to be transmissible to humans. Evidence from genomic analysis suggests that H9N2 provides the genes for the H5N1 and H7N9 subtypes, which have been found to infect mammals and pose a threat to human health. However, due to the lack of a structural model of the interaction between H9N2 and host cells, the mechanism of the extensive adaptability and strong transformation capacity of H9N2 is not fully understood. In this paper, we collected 40 representative H9N2 virus samples reported recently, mainly in China and neighboring countries, and investigated the interactions between H9N2 hemagglutinin and the mammalian receptor, the polysaccharide α-2,6-linked lactoseries tetrasaccharide c, at the atomic level using docking simulation tools. We categorized the mutations of studied H9N2 hemagglutinin according to their effects on ligand-binding interactions and the phylogenetic analysis. The calculations indicated that all the studied H9N2 viruses can establish a tight binding with LSTc although the mutations caused a variety of perturbations to the local conformation of the binding pocket. Our calculations suggested that a marginal equilibrium is established between the conservative ligand-receptor interaction and the conformational dynamics of the binding pocket, and it might be this equilibrium that allows the virus to accommodate mutations to adapt to a variety of environments. Our results provided a way to understand the adaptive mechanisms of H9N2 viruses, which may help predict its propensity to spread in mammals.

PGG.Han: the Han Chinese genome database and analysis platform.

As the largest ethnic group in the world, the Han Chinese population is nonetheless underrepresented in global efforts to catalogue the genomic variability of natural populations. Here, we developed the PGG.Han, a population genome database to serve as the central repository for the genomic data of the Han Chinese Genome Initiative (Phase I). In its current version, the PGG.Han archives whole-genome sequences or high-density genome-wide single-nucleotide variants (SNVs) of 114 783 Han Chinese individuals (a.k.a. the Han100K), representing geographical sub-populations covering 33 of the 34 administrative divisions of China, as well as Singapore. The PGG.Han provides: (i) an interactive interface for visualization of the fine-scale genetic structure of the Han Chinese population; (ii) genome-wide allele frequencies of hierarchical sub-populations; (iii) ancestry inference for individual samples and controlling population stratification based on nested ancestry informative markers (AIMs) panels; (iv) population-structure-aware shared control data for genotype-phenotype association studies (e.g. GWASs) and (v) a Han-Chinese-specific reference panel for genotype imputation. Computational tools are implemented into the PGG.Han, and an online user-friendly interface is provided for data analysis and results visualization. The PGG.Han database is freely accessible via http://www.pgghan.org or https://www.hanchinesegenomes.org.

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules.

MOTIVATION: Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecular particle images from thousands of low-contrast, high-noisy electron micrographs. Although machine-learning methods were developed to get rid of this bottleneck, it still lacks universal methods that could automatically picking the noisy cryo-EM particles of various macromolecules. RESULTS: Here, we present a deep-learning segmentation model that employs fully convolutional networks trained with synthetic data of known 3D structures, called PARSED (PARticle SEgmentation Detector). Without using any experimental information, PARSED could automatically segment the cryo-EM particles in a whole micrograph at a time, enabling faster particle picking than previous template/feature-matching and particle-classification methods. Applications to six large public cryo-EM datasets clearly validated its universal ability to pick macromolecular particles of various sizes. Thus, our deep-learning method could break the particle-picking bottleneck in the single-particle analysis, and thereby accelerates the high-resolution structure determination by cryo-EM. AVAILABILITY AND IMPLEMENTATION: The PARSED package and user manual for noncommercial use are available as Supplementary Material (in the compressed file: parsed_v1.zip). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sequence-based prediction of physicochemical interactions at protein functional sites using a function-and-interaction-annotated domain profile database.

BACKGROUND: Identifying protein functional sites (PFSs) and, particularly, the physicochemical interactions at these sites is critical to understanding protein functions and the biochemical reactions involved. Several knowledge-based methods have been developed for the prediction of PFSs; however, accurate methods for predicting the physicochemical interactions associated with PFSs are still lacking. RESULTS: In this paper, we present a sequence-based method for the prediction of physicochemical interactions at PFSs. The method is based on a functional site and physicochemical interaction-annotated domain profile database, called fiDPD, which was built using protein domains found in the Protein Data Bank. This method was applied to 13 target proteins from the very recent Critical Assessment of Structure Prediction (CASP10/11), and our calculations gave a Matthews correlation coefficient (MCC) value of 0.66 for PFS prediction and an 80% recall in the prediction of the associated physicochemical interactions. CONCLUSIONS: Our results show that, in addition to the PFSs, the physical interactions at these sites are also conserved in the evolution of proteins. This work provides a valuable sequence-based tool for rational drug design and side-effect assessment. The method is freely available and can be accessed at http://202.119.249.49 .

[The effects of prenatal stress on the astrocytes after cerebral ischemia/reperfusion injury in adult offspring rats].

OBJECTIVE: To investigate the effects of prenatal stress on astrocytes after ischemia/reperfusion of cerebral middle artery in adult offspring rats. METHODS: Pregnant rats were randomly assigned to prenatal stress treatment group, which was exposed to restraint three times daily in the last week of pregnancy, and no prenatal stress treatment group. Adult male offspring rats were subjected to transient focal cerebral ischemia by middle cerebral artery occlusion (MCAO). There were three groups:prenatal stress+sham group, MCAO group and prenatal stress+MCAO group (n=10). After 5 days of reperfusion, the infarct size was evaluated. The morphology of astrocytes, co-local-ization of erythropoietin-producing hepatocellular receptor A4 (EphA4) and glial fibrillary acidic protein (GFAP) were detected by double im-munofluorescent staining. And the protein expressions of EphA4, GFAP and Neurocan in peri-ischemic regions were detected by Western blot. RESULTS: The infarct size and the expression of EphA4, GFAP and Neurocan were significantly increased in prenatal stress+MCAO group compared with MCAO group (all P<0.05). And the morphological changes of GFAP-positive astrocytes and co-localization of EphA4/GFAP were more obvious in prenatal stress+MCAO group compared with MCAO group. CONCLUSIONS: Prenatal stress may upregulate the expression of EphA4 on astrocytes in the offspring rats after cerebral ischemia/reperfusion, which promotes the reactivity of astrocyte and increases the ex-pression of neurocan.

Reduction of the systemic inflammatory induced by acute cerebral infarction through ultra-early thrombolytic therapy.

Acute ischemic stroke induces systemic inflammation, exhibited as changes in body temperature, white blood cell counts and C-reactive protein (CRP) levels. The aim of the present study was to observe the effects of intravenous thrombolytic therapy on inflammatory indices in order to investigate the hypothesis that post-stroke systemic inflammatory response occurs in response to the necrosis of brain tissues. In this study, 62 patients with acute cerebral infarction and indications for intravenous thrombolysis were divided into three groups on the basis of their treatment and response: Successful thrombolysis (n=36), failed thrombolysis (n=12) and control (n=14) groups. The body temperature, white blood cell counts and high-sensitivity (hs)-CRP levels were recorded pre-treatment and on post-stroke days 1, 3, 5 and 7. Spearman's correlation analysis showed that the pre-treatment National Institutes of Health Stroke Scale (NIHSS) score positively correlated with body temperature, white blood cell count and hs-CRP levels. On day 3 of effective intravenous thrombolysis, the body temperature and white blood cell were decreased and on days 3 and 5, the serum levels of hs-CRP were reduced compared with those in the failed thrombolysis and control groups. The results indicate that the systemic inflammatory response following acute cerebral infarction was mainly caused by ischemic injury of local brain tissue; the more serious the stroke, the stronger the inflammatory response. Ultra-early thrombolytic therapy may inhibit the necrosis of brain tissue and thereby reduce the inflammatory response.

Docking polysaccharide to proteins that have a Tryptophan box in the binding pocket.

Protein-carbohydrate interactions (PCIs) involve a variety of essential biological processes such as cell recognition and migration, metabolism processes and immunological reactions, which are important for securing functions of living organisms. Due to the polysaccharide structural diversity and dynamics flexibility, PCIs can be very difficult for experimental measurement and computer prediction. Here we report a simple method for docking polysaccharide to proteins whose binding pockets have a Tryptophan box. The method samples polysaccharide conformations using constraint conditions imposed by the box, evaluate the conformation energies based on a knowledge-based potential function, and finds the best docking structures using the conventional Monte Carlo simulated annealing technique. We applied the method to dock polysaccharides with 2 to 4 monomers to three carbohydrate-binding proteins, whose pockets have clear aromatic residue-defined binding channels. The predictions found correct carbohydrate binding conformations with atomic RMSD of 1.1-1.6 Å from X-ray crystal structures. The calculation can be performed in ordinary PC and only cost a couple of minutes for a single docking. Our method, when combined with other docking programs, provides a reliable start conformation for further accurate simulation of PCIs.

[The effects of prenatal stress on the cell apoptosis after MCAO in adult offspring rats].

OBJECTIVE: To evaluate the effects of prenatal stress on neurological functions after middle cerebral artery occlusion (MCAO) in adult offspring rats. METHODS: Pregnant rats were randomly assigned to prenatal stress treatment, which was exposed to restraint three times daily in the last week of pregnancy, and no prenatal stress treatment. Adult male offspring rats were subjected to transient focal cerebral ischemia by MCAO. They were randomly divided into four groups: sham group, prenatal stress + sham group, MCAO group and prenatal stress + MCAO group (n = 10). After 24 hours of reperfusion, the neurological deficits were evaluated. The infarct size, cell apoptosis and expression of Caspase 3, cleaved Caspase 3 and Bcl-2 were detected. RESULTS: Compared with MCAO group, the neurological deficits, infarct size and apoptotic cells in prenatal stress + MCAO group were increased significantly (all P < 0.05). The expressions of Caspase 3 and cleaved Caspase 3 were much greater in prenatal stress + MCAO group than those of MCAO group, while the expression of Bcl-2 was significantly decreased in prenatal stress + MCAO group compared with MCAO group (all P < 0.05). CONCLUSION: Prenatal stress might exacerbate neuroloeical deficits in the offspring rats after MCAO by increasing cell apoptosis.