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Gou, X.

Publications and source records attributed to Gou, X..

15 recordsLinked to original sources

De novo design of a protein fold for small-molecule binding through aromatic π stacking

The de novo design of proteins that bind chemically complex small molecules has broad chemical and biological implications, but strategies typically rely on a small set of protein scaffolds and require extensive experimental screening. Here, we computationally designed proteins around a minimal aromatic {pi}-stacking motif to bind the anthracycline anticancer drug doxorubicin. Experimental characterization of twelve proteins revealed a {micro}M doxorubicin binder; two additional design cycles improved scaffold stability and binding affinity to yield an 85-residue protein that binds doxorubicin with a dissociation constant of 85 nM. An X-ray crystal structure of the protein-drug complex confirmed the accuracy of the designed {pi}-{pi} stacking interactions. The designed protein could act to protect cultured cells from doxorubicin-induced cytotoxicity. Unlike previous ligand-binding protein designs based on repeat proteins or naturally occurring folds, the designed protein adopts a previously unobserved 5-helix globular fold, indicating that a broader space of folded, functional proteins exists even for compact tertiary structures smaller than 100 residues. These results demonstrate that motif-guided generative protein design can discover compact de novo protein folds capable of high-affinity recognition of chemically complex small molecules.

biochemistry↗

Single-Cell Transcriptomic Analysis of the Immune Response to CHIKVInfection

BackgroundThe Chikungunya virus (CHIKV), a re-emerging mosquito-borne alphavirus, is responsible for acute febrile illness and severe polyarthralgia. Although both innate and adaptive immune responses influence the disease outcomes, the detailed cellular immunopathogenesis of CHIKV in peripheral blood is not yet fully elucidated. MethodsWe conducted single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (PBMCs) obtained from patients acutely infected with CHIKV and from healthy control subjects. Cellular interactions were inferred, and the transcriptomic results were orthogonally validated through quantitative real-time PCR (qPCR) and Enzyme-Linked Immunosorbent Assay (ELISA) to assess systemic interferon-stimulated responses. Furthermore, a comparative analysis was performed using publicly available single-cell data from Dengue virus (DENV) infections. ResultsCHIKV infection significantly altered the immune system, increasing monocytes and dendritic cells while reducing T and B lymphocytes. Monocytes and NK cells showed strong activation of interferon-stimulated genes (ISGs). Monocytes were identified as key in driving inflammatory and immune responses. In adaptive immunity, CHIKV led B cells to become plasmablasts with antiviral immunoglobulins and caused T cells and NK-like T cells to show signs of cytotoxicity and exhaustion. Validation showed increased levels of IFN-{gamma}, IFN-{beta}1, MX1, and ISG15. CHIKV triggered a more intense, monocyte-driven interferon response than DENV. ConclusionsAcute CHIKV infection induces a systemic interferon response predominantly centered on monocytes, accompanied by significant alterations in adaptive immunity. Circulating ISG products, including MX1 and ISG15, reflect the transcriptomic activation and may serve as potential biomarkers for assessing the early intensity of innate antiviral responses.

immunology↗

Microbial network rewiring mediates the function-biosafety trade-off in transboundary Pamir lakes

The Pamir Plateau is a transboundary water tower whose source lakes serve as critical biogeochemical hubs with implications for downstream freshwater security. However, it remains unclear how environmental shifts in these high-altitude lakes reshape the microbial communities that drive ecosystem functioning and water safety. Here, we conducted a multi-omics survey across 20 lakes spanning Chinese and Tajikistani Pamir. Our results revealed that prokaryotes exhibited lower diversity but higher among-lake connectivity in China, while eukaryotes showed higher diversity but stronger dispersal limitation. These contrasting biogeographic responses triggered profound rewiring of microbial associations. Under intensified anthropogenic pressures, Chinese cross-kingdom networks decoupled from environmental constraints and became more centralized and complex. Conversely, Tajikistani lakes maintained more modular networks governed by hydrochemical filtering. Critically, this rewiring mediated a trade-off between multifunctionality and potential biosafety risk, with higher element cycling abundances in Chinese lakes, whereas Tajikistani lakes harbored larger biosafety burden dominated by virulence, pathogen, and toxic-algae potential. Incorporating network topology also substantially improved the prediction of these ecological consequences. These findings highlight the importance of network-informed monitoring and management strategies to safeguard ecosystem sustainability in transboundary Pamir lakes under global change.

microbiology↗

Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a integrated single-cell spatial molecular, cellular, anatomic and projectomic atlas of mouse prefrontal cortex (PFC). The projectomic and transcriptomic cell clusters display distinct modular organization principles, but are coordinately configured in the PFC. The projection neurons gradiently occupied different territories in the PFC aligning with their wiring patterns. Importantly, they show higher co-projection probability to the downstream nuclei with reciprocal circuit connections. Moreover, we integrated projectomic atlas with their distinct spectrum of neurotransmitter/neuropeptide and the receptors-related gene profiles and depicted PFC neural signal transmission network. By which, we uncovered potential mechanisms underlying the complexity and specificity of neural transmission. Finally, leveraging machine learning, we predicted neuron projections with high accuracy by combining gene profiles and spatial information. As a proof of concept, we used this model to predict projections of fear recall engram neurons. This study facilitates our understanding of brain multi-modal network and neural computation.

neuroscience↗

Fast Loading and Transformation of Large-Volume Bioimaging Data Consistently Approaching the I/O Peak Speed

High-resolution large-volume biological imaging techniques are now widely used in biological research, but inefficiencies in data processing and visualization persist due to bottlenecks in loading/saving pipelines and limitations of conventional pyramid formats. To address these issues, we have decoupled data loading process into reading from disk and in-memory decompression, while data saving has been separated into in-memory compression and writing to disk. This approach allows us to dedicate more CPU cores to decompression and compression tasks, optimizing resource allocation and maximizing disk I/O throughput. As a result, both loading and saving processes operate near the disks peak data transfer capacity. Further, we integrated a video stream-inspired format into the pyramid structure, allowing direct access to regions of interest (ROIs) without loading extraneous data into RAM, reducing memory overhead. Compared to the latest methods, our approach improves pyramid data transformation efficiency by at least 6x and dramatically accelerates downstream tasks like visualization and deep learning inference. TeaserNovel bioimaging data processing pipeline achieves near-peak I/O throughput via decoupled architecture and video-formatting.

bioinformatics↗

PointTree: Automatic and accurate reconstruction of long-range axonal projections of single-neuron

Single-neuron axonal projections reveal the route map of neuron output and provide a key cue for understanding how information flows across the brain. Reconstruction of single-neuron axonal projections requires intensive manual operations in tens of terabytes of brain imaging data, and is highly time-consuming and labor-intensive. The main issue lies in the need for precise reconstruction algorithms to avoid reconstruction errors, yet current methods struggle with densely distributed axons, focusing mainly on skeleton extraction. To overcome this, we introduce a point assignment-based method that uses cylindrical point sets to accurately represent axons and a minimal information flow tree model to suppress the snowball effect of reconstruction errors. Our method successfully reconstructs single-neuron axonal projections across hundreds of GBs (Gigabytes) images with an average of 80% F1-score, while current methods only provide less than 40% F1-score reconstructions from a few hundred MBs (Megabytes) images. This huge improvement is helpful for high-throughput mapping of neuron projections.

neuroscience↗

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low M, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles. One Sentence SummaryWe use informatic sampling to design low nM drug-binding proteins, and physics-based calculations to accurately predict affinities.

biophysics↗

Effects of homoeologous exchange on gene expression and alternative splicing in a newly formed allotetraploid wheat

Homoeologous exchange (HE) is a major mechanism generating post-polyploidization genetic variation with important evolutionary consequences. However, the direct impacts of HE without entangling with additional evolutionary forces on gene expression remains to be fully understood. Here, we analyzed high-throughput RNA-seq data of young leaves from individuals of a synthetic allotetraploid wheat (AADD), which contain variable numbers of HEs. We aimed to investigate if and to which extent HE directly impacts gene expression and alternative splicing (AS). We found that HE impacts expression of genes located within HE regions primarily via cis-acting dosage effect, which led to significant changes in the total expression of homoeolog pairs, especially for homoeologs whose original expression was biased. In parallel, HE influences expression of a large amount of genes residing in non-HE regions by trans-regulation leading to convergent expression of homoeolog pairs. Intriguingly, when taking into account of the original relative homoeolog expression states, homoeolog pairs under trans-effect are more prone to showing convergent response to HE whereas those under cis-effect trended to show subgenome-specific expression. Moreover, HE induced quantitative, largely individual-specific, changes of alternative splicing (AS) events. Like homoeologs expression, homoeo-AS events which related to trans effect were more responsive to HE. HE therefore exerts multifaceted immediate effects on gene expression and, to a less extent, also transcript diversity in nascent allopolyploidy.

plant biology↗

An oligosaccharide analog exhibited antifungal activity by misleading cell wall organization via targeting PHR transglucosidases

The fungal cell wall is an ideal target for the design of antifungal drugs. In this study we used an analog of cell wall polymer, a highly deacetylated long-chain chitosan oligosaccharide (HCOS), to test its effect against pathogenic Candida strains. Results showed that HCOS was successfully incorporated into the dynamic cell wall organization process and exhibited an apparent antifungal activity against both plankton and mature fungal biofilm, by impairing the cell wall integrity. Unexpectedly, mechanistic studies suggested that HCOS exerts its activity by interfering with family members of PHR {beta}-(1,3)-glucanosyl transferases and affecting the connection and assembly of cell wall polysaccharides. Furthermore, HCOS showed great synergistic activity with different fungicides against Candida cells, especially those in biofilm. These findings indicated HCOS has a great potential as an antifungal drug or drug synergist and proposed a novel antifungal strategy with structure-specific oligosaccharides mimicking cell wall polysaccharide fragments. IMPORTANCEFungal infections have always been a puzzle in clinical medicine. Only a few antifungal drugs are available for medical usage and the widespread use of antifungal drugs increased the incidence of drug resistance. It is an urgent need for the development of novel treatment strategies against fungal infections. In this study, we proposed a novel strategy targeting to fungal cell wall against C. albicans. To our knowledge, it is the first study to show a cell wall polysaccharide fragment analog integrate into and interfere with the fungal cell wall, indicating a novel antifungal strategy using structure-specific oligosaccharides mimicking cell wall polysaccharide fragments.

microbiology↗

Subsynaptic positioning of AMPARs by LRRTM2 controls synaptic strength

Recent evidence suggests that nanoorganization of proteins within synapses may control the strength of communication between neurons in the brain. The unique subsynaptic distribution of glutamate receptors, which cluster in nanoalignment with presynaptic sites of glutamate release, supports this idea. However, testing it has been difficult because mechanisms controlling subsynaptic organization remain unknown. Reasoning that transcellular interactions could position AMPA receptors, we targeted a key transsynaptic adhesion molecule implicated in controlling AMPAR number, LRRTM2, using engineered, rapid proteolysis. Severing the LRRTM2 extracellular domain led quickly to nanoscale de-clustering of AMPARs away from release sites, not prompting their escape from synapses until much later. This rapid remodeling of AMPAR position produced significant deficits in evoked, but not spontaneous, postsynaptic receptor activation. These results dissociate receptor numbers from their nanopositioning in determination of synaptic function, and support the novel concept that adhesion molecules acutely position AMPA receptors to dynamically control synaptic strength.

neuroscience↗

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

Gastric cancer is among the most malignant tumours with the highest incidence and mortality rates. The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. While the worldwide shortage of pathologists has imposed burdens on current histopathology services, it also offers a unique opportunity for the use of artificial intelligence assistance systems to alleviate the workload and increase diagnostic accuracy. To the best of our knowledge, there has not been a clinically applicable histopathological assistance system with high accuracy that can generalize to whole slide images created with diverse digital scanner models from different hospitals. Here, we report a clinically applicable artificial intelligence assistance system developed at the Chinese PLA General Hospital, China, using a deep convolutional neural network trained with 2,123 pixel-level annotated H&E-stained whole slide images. The model achieved a sensitivity near 100% and an average specificity of 80.6% on a real-world test dataset, which included 3,212 whole slide images digitalized with three scanner models. We showed that the system could aid pathologists in improving diagnostic accuracy and preventing misdiagnoses. Moreover, we demonstrated that our system could perform robustly with 1,582 whole slide images from two other medical centres. Our study suggests the feasibility and benefits of using histopathological artificial intelligence assistance systems in routine practice scenarios.Competing Interest StatementXiaoqing Zhang is the founder of Thorough Images. Shuhao Wang is the co-founder and chief technology officer (CTO) of Thorough Images. Calvin Ku, Cancheng Liu, Zhuo Sun, Gang Xu, Yuefeng Wang are algorithm researchers of Thorough Images. All remaining authors have declared no conflicts of interest.View Full Text

pathology↗

Convergent genomic signatures of high altitude adaptation among domestic mammals

Abundant and diverse domestic mammals living on the Tibetan Plateau provide useful materials for investigating adaptive evolution and genetic convergence. Here, we utilized 327 genomes from horses, sheep, goats, cattle, pigs and dogs living at both high and low altitudes, including 73 genomes generated for this study, to disentangle the genetic mechanisms underlying local adaptation of domestic mammals. Although molecular convergence is comparatively rare at the DNA sequence level, we found convergent signature of positive selection at the gene level, particularly EPAS1 gene in these Tibetan domestic mammals. We also reported a potential function in response to hypoxia for the gene C10orf67, which underwent positive selection in three of the domestic mammals. Our data provides insight into adaptive evolution of high-altitude domestic mammals, and should facilitate the search for additional novel genes involved in the hypoxia response pathway.

evolutionary biology↗

Natural selection on TMPRSS6 associated with the blunted erythropoiesis and improved blood viscosity in Tibetan Pigs

Tibetan pigs, indigenous to Tibetan plateau, are well adapted to hypoxia. So far, there have been not any definitively described genes and functional sites responsible for hypoxia adaptation for the Tibetan pig. Here we conducted resequencing of the nearly entire genomic region (40.1 kb) of the candidate gene TMPRSS6 (Transmembrane protease, serine 6) associated with hemoglobin concentration (HGB) and red blood cell count (RBC) in 40 domestic pigs and 40 wild boars from five altitudes along the Tea-horse ancient road and identified 708 SNPs, in addition to an indel (CGTG/----) in the intron 10. Both the CGTG deletion frequency and the pairwise r2 linkage disequilibrium showed an increase with elevated altitudes in 838 domestic pigs from five altitudes, suggesting that TMPRSS6 has been under Darwinian positive selection. As the conserved core sequence of hypoxia-response elements (HREs), the deletion of CGTG in Tibetan pigs decreased the expression levels of TMPRSS6 mRNA and protein in the liver revealed by real-time quantitative PCR and western blot, respectively. To explore whether reduced TMPRSS6 expression level could improve blood viscosity, the relationship between CGTG indel and hematologic and hemorheologic parameters in 482 domestic pigs from continuous altitudes was detected and dissected a genetic effect on reducing HGB by 13.25g/L in Gongbogyamda Tibetan pigs and decreasing MCV by 4.79 fl in Diqing Tibetan pigs. In conclusion, the CGTG deletion of TMPRSS6 resulted in lower HGB and smaller MCV, thereby blunting erythropoiesis and improving blood viscosity as well as erythrocyte deformability.

physiology↗

Development of an Intrinsic Skin Sensor for Blood Glucose Level with CRISPR-mediated Genome Editing in Epidermal Stem Cells

Biointegrated sensors can address various challenges in medicine by transmitting a wide variety of biological signals. A tempting possibility that has not been explored before is whether we can take advantage of genome editing technology to transform a small portion of endogenous tissue into an intrinsic and long-lasting sensor of physiological signals. The human skin and the epidermal stem cells have several unique advantages, making them particularly suitable for genetic engineering and applications in vivo. In this report, we took advantage of a novel platform for manipulation and transplantation of epidermal stem cells, and presented the key evidence that genome-edited skin stem cells can be exploited for continuous monitoring of blood glucose level in vivo. Additionally, by advanced design of genome editing, we developed an autologous skin graft that can sense glucose level and deliver therapeutic proteins for diabetes treatment. Our results revealed the clinical potential for skin somatic gene therapy.

cell biology↗

Species composition and environmental adaptation of indigenous Chinese cattle

Indigenous Chinese cattle combine taurine and indicine origins and occupy a broad range of different environments. By 50K SNP genotyping we found a discontinuous distribution of taurine and indicine cattle ancestries with extremes of less than 10% indicine cattle in the north and more than 90% in the far south and southwest China. Model-based clustering and f4-statistics indicate introgression of both banteng and gayal into southern Chinese cattle while the sporadic yak influence in cattle in or near Tibetan area validate earlier findings of mitochondrial DNA analysis. Geographic patterns of taurine and indicine mitochondrial and Y-chromosomal DNA diversity largely agree with the autosomal cline. The geographic distribution of the genomic admixture of different bovine species is proposed to be the combined effect of prehistoric immigrations, gene flow, major rivers acting as genetic barriers, local breeding objectives and environmental adaptation. Whole-genome scan for genetic differentiation and association analyses with both environmental and morphological covariables are remarkably consistent with previous studies and identify a number of genes implicated in adaptation, which include TNFRSF19, RFX4, SP4 and several coat color genes. We propose indigenous Chinese cattle as a unique and informative resource for gene-level studies of climate adaptation in mammals.

evolutionary biology↗