Biology subjects

Xu, J.

Publications and source records attributed to Xu, J..

At least 487 records · Page 27Linked to original sources

bioRxiv2023

Decoding CRISPR-Cas9 PAM recognition with UniDesign

The critical first step in CRISPR-Cas mediated gene editing is recognizing a preferred protospacer adjacent motif (PAM) on target DNAs by the proteins PAM-interacting amino acids (PIAAs). Thus, accurate computational modeling of PAM recognition is useful in assisting CRISPR-Cas engineering to relax or tighten PAM requirement for subsequence applications. Here we describe a universal computational protein design framework (UniDesign) for designing protein-nucleic acid interactions. As a proof of concept, we applied UniDesign to decode the PAM-PIAA interactions for eight Cas9 proteins. We show that, given native PIAAs, the UniDesign-predicted PAMs are largely identical to the natural PAMs of all Cas9s. In turn, given natural PAMs, the computationally redesigned PIAA residues largely recapitulated the native PIAAs (>70% and >80% in terms of identity and similarity, respectively). These results demonstrate that UniDesign faithfully captures the mutual preference between natural PAMs and native PIAAs, suggesting it as a useful tool for engineering CRISPR-Cas and other nucleic acid-interacting proteins. UniDesign is open-sourced at https://github.com/tommyhuangthu/UniDesign.

bioinformatics↗

bioRxiv2023

When Geometric Deep Learning Meets Pretrained Protein Language Models

Geometric deep learning has recently achieved great success in non-Euclidean domains, and learning on 3D structures of large biomolecules is emerging as a distinct research area. However, its efficacy is largely constrained due to the limited quantity of structural data. Meanwhile, protein language models trained on substantial 1D sequences have shown burgeoning capabilities with scale in a broad range of applications. Nevertheless, no preceding studies consider combining these different protein modalities to promote the representation power of geometric neural networks. To address this gap, we make the foremost step to integrate the knowledge learned by well-trained protein language models into several state-of-the-art geometric networks. Experiments are evaluated on a variety of protein representation learning benchmarks, including protein-protein interface prediction, model quality assessment, protein-protein rigid-body docking, and binding affinity prediction, leading to an overall improvement of 20% over baselines and the new state-of-the-art performance. Strong evidence indicates that the incorporation of protein language models knowledge enhances geometric networks capacity by a significant margin and can be generalized to complex tasks.

bioinformatics↗

bioRxiv2022

Neurological Disorder after Severe Pneumonia is Associated with Translocation of Bacteria from Lung to Brain

The neurological disorder is a common feature in patients who recovered from severe acute pneumonia. However, the underline mechanisms remain not very clear. Here we show that these neurological syndromes after severe acute pneumonia are partly attributed to the translocation of bacteria from the lung to the brain during pneumonia. We detected an emerging and increased bacteria in the brain tissue of mice with lipopolysaccharide-induced experimental severe pneumonia. Interestingly, using 16S rDNA amplification sequencing, similarities were found between the brains flora species and those of the lungs, indicating the bacteria in the brain may originate from the lung. We also observed the impairment of the lung-blood barrier and brain-blood barrier, simultaneously, allowing lung bacteria invade the brain during pneumonia. An elevated microglia and astrocytes activation signature through bacterial infection-related pathways is observed by single-cell RNA sequencing, indicating a bacteria-induced disruption of brain homeostasis. Rapamycin delivered by platelet-derived extracellular vesicles provides an effective strategy to rescue the dysfunction of microglia and astrocytes, and relief neurological disorders. Collectively, we identify lung bacteria that play a role in altering brain homeostasis, which provides new insight into the mechanism of neurological syndromes after severe pneumonia.

neuroscience↗

bioRxiv2022

Dissecting the Human Leptomeninges at single-cell resolution

Emerging evidence shows that the meninges conduct essential immune surveillance and immune defense at the brain border, and the dysfunction of meningeal immunity contributes to aging and neurodegeneration. However, no study exists on the molecular properties of cell types within human leptomeninges. Here, we provide the first single nuclei profiling of dissected postmortem leptomeninges from aged individuals. We detect diverse cell types, including unique meningeal endothelial, mural, and fibroblast subtypes. For immune cells, we show that most T cells express CD8 and bear characteristics of tissue-resident memory T cells. We also identify distinct subtypes of border-associated macrophages (BAMs) that display differential gene expressions from microglia and express risk genes for Alzheimers Disease (AD), as nominated by genome-wide association studies (GWAS). We discover cell-type-specific differentially expressed genes in individuals with Alzheimers dementia, particularly in fibroblasts and BAMs. Indeed, when cultured, leptomeningeal cells display the signature of ex vivo AD fibroblasts upon amyloid-{beta} treatment. We further explore ligand-receptor interactions within the leptomeningeal niche and computationally infer intercellular communications in AD. Thus, our study establishes a molecular map of human leptomeningeal cell types, providing significant insight into the border immune and fibrotic responses in AD.

genomics↗

bioRxiv2022

Role of HAO2 in rats with chronic kidney disease by regulating fatty acid metabolic processes in renal tissue

Fibrosis is a progressive, often irreversible histologic manifestation of chronic and end-stage renal disease. In this study, single-cell transcriptome sequencing technology was used to sequence and analyze blood and kidney tissue cells in normal control rats and rats with chronic kidney disease (CKD), focusing on key cell populations and functional enrichment to explore the pathogenesis of CKD. Oil red O staining and ELISA were used to detect lipid droplets and free fat acid (FFA). RT-PCR, WB were used to verify the differential gene HAO2 and fatty acid metabolic process in tissue to ensure the reliability of single-cell sequencing results. We successfully established a single-cell transcriptome atlas of blood and kidney tissue in rats with CKD, which were annotated into 14 cell subsets (MPCs, PT, Tc, DCT, B-IC, A-IC, CNT, ALOH, BC, Neu, Endo, Pla, NKT, Baso) according to marker gene, and the integrated single-cell atlas of rats showed a significant increase and decrease of MPCs and PTs in the model group, respectively. Functional analysis found extensive enrichment of metabolic-related pathways in PT cells, includes fatty acid metabolic process, cellular amino acid metabolic process and generation of precursor metabolites and energy. Immunohistochemical experiments determined that the differential gene HAO2 was localized in the renal tubules, and its expression was significantly reduced in model group compared with control, and oil red O staining showed that lipid droplets increased in the model group. ELISA assay showed that ATP content decreased in the model group and FFA increased in the model group. ACOX1, PPAR, PGC1 were decreased in the model group, while genes and proteins were increased after overexpression of HAO2, and the AMPK and ACC phosphorylated proteins were increased. Therefore, HAO2 may be an important regulator of fatty acid metabolic processes in CKD, and overexpression of HAO2 can enhance fatty acid metabolism by promoting fatty acid oxidation pathway.

cancer biology↗

bioRxiv2022

Discovery and remodeling of Vibrio natriegens as a microbial platform for efficient formic acid biorefinery

Formic acid (FA), an organic one-carbon source that is easily produced from CO2, has emerged as a promising CO2-equivalent feedstock for one-carbon biorefinery. However, developing efficient formatotrophs for an economically competitive FA utilization system remains a grand challenge. Here, we discovered that the gram-negative bacterium Vibrio natriegens has exceptional FA tolerance and metabolic capacity natively. This strain was then remodeled by rewiring the serine cycle and the TCA cycle which resulted in a non-native closed loop (S-TCA) for enhancing FA assimilation. The rational design generated a powerful metabolic sink that enabled rapid emergence of the evolved strains with further significantly improved performance in using FA as the major or sole carbon source. Furthermore, the introduction of a foreign indigoidine-forming pathway into the best-performing V. natriegens strain (S-TCA-2.0) led to production of 29.0 g{middle dot}L-1 indigoidine and consumption of 233.7 g{middle dot}L-1 formate within 72 h, achieving an order of magnitude higher formate consumption rate (3.2 g{middle dot}L-1{middle dot}h-1) than the reported highest level in microorganisms. This work represents a significant step towards the development of industrially viable microorganisms for FA biorefinery.

microbiology↗

bioRxiv2022

Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics

Cells do not live in a vacuum, but in a milieu defined by cell-cell communication that can be measured via emerging high-resolution spatial transcriptomics approaches. However, analytical tools that fully leverage such data for kinetic modeling remain lacking. Here we present Spateo (aristoteleo/spateo-release), a general framework for quantitative spatiotemporal modeling of single-cell resolution spatial transcriptomics. Spateo delivers novel methods for digitizing spatial layers/columns to identify spatially-polar genes, and develops a comprehensive framework of cell-cell interaction to reveal spatial effects of niche factors and cell type-specific ligand-receptor interactions. Furthermore, Spateo reconstructs 3D models of whole embryos, and performs 3D morphometric analyses. Lastly, Spateo introduces the concept of "morphometric vector field" of cell migrations, and integrates spatial differential geometry to unveil regulatory programs underlying various organogenesis patterns of Drosophila. Thus, Spateo enables the study of the ecology of organs at a molecular level in 3D space, beyond isolated single cells.

systems biology↗

bioRxiv2022

New high-resolution maps show that rubber causes significant deforestation

Understanding the impacts of cash crop expansion on natural forest is of fundamental importance. However, for most crops there are no remotely-sensed global maps1, and global deforestation impacts are estimated using models and extrapolations. Natural rubber is an example of a major commodity for which deforestation impacts have been highly uncertain, with estimates differing more than five-fold1-4. Here we harnessed earth observation satellite data and cloud computing5 to produce the first high-resolution maps of rubber and associated deforestation covering all Southeast Asia. Our maps indicate that rubber-related forest loss has been significantly underestimated in policy, by the public and in recent reports6-8. Our direct remotely-sensed observations show that deforestation for rubber is two to threefold higher than suggested by figures currently widely used for setting policy4. With over 3.76 million hectares of forest loss for rubber since 1993 (2.77 [2.5-3 95% CI] million hectares since 2000), and over 1 million hectares of rubber plantations established in Key Biodiversity Areas, the impacts of rubber on biodiversity and ecosystem services in Southeast Asia are extensive. Thus, rubber deserves more attention in domestic policy, within trade agreements and in incoming due diligence regulations.

ecology↗

bioRxiv2022

Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures

Delineating the gene regulatory programs underlying complex cell types is fundamental for understanding brain functions in health and disease. Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain.

neuroscience↗

bioRxiv2022

SapBase (Sapinaceae Genomic DataBase): a central portal for functional and comparative genomics of Sapindaceae species

Sapindaceae is a family of flowering plants, also known as the soapberry family, comprising 141 genera and about 1900 species (Pedro et al., 2010). Most of them are distributed in tropical and subtropical regions, including trees, shrubs, also woody or herbaceous vines. Some are dioecious, while others are monoecious. Many Sapindaceae species possess great economic value; some furnish delicious fruits, like lychee (Litchi chinensis), longan (Dimocarpus longan), rambutan (Nephelium lappaceum); and ackee (Blighia sapida) - the national fruit of Jamaica; some produce abundance secondary metabolites, like saponin from soapberry (Sapindus mukorossi), and seed oil from yellowhorn (Xanthoceras sorbifolium); some yield valuable timber including maple (Acer spp.) and buckeye (Aesculus glabra); and some are of great herbal medicinal value, like balloon-vine (Cardiospermum halicacabum). In the last decade, with the rocketing of next generation sequencing (NGS) and genomic technologies, the full genome sequences of several Sapindaceae plants have been resolved (Lin et al., 2017; Liang et al., 2019; Yang et al., 2019; Zhang et al., 2021; Hu et al., 2022; Xue et al., 2022). Among them, our recent publication of the lychee genome attracted broad attention (Edger, 2022; Hu et al., 2022; Lyu, 2022). Now the post-genome era arrives for Sapindaceae, however, there is no public genomic database available for any Sapindaceae species, let alone an integrative database for the whole Sapindaceae family. A unified data platform is in urgent need to collect, manage and share relevant data resources. Therefore, we integrated our home-brew NGS data with all publicly available data for seven Sapindaceae plants and constructed the Sapinaceae Genomic DataBase, named SapBase (www.sapindaceae.com), in order to provide genomic resources and an online powerful analytic platform for scientific research on Sapinaceae species and comparative studies with other plants.

genomics↗

bioRxiv2022

Mimicking genuine drought responses using a high throughput plate assay

Soil-free assays that induce water stress are routinely used to investigate drought responses in the plant Arabidopsis thaliana. Due to their ease of use, the research community often relies on polyethylene glycol (PEG), mannitol and salt (NaCl) treatments to reduce the water potential of agar media, and thus induce drought conditions in the laboratory. However, while these types of stress can create phenotypes that resemble those of water deficit experienced by soil-grown plants, it remains unclear how these treatments compare at the transcriptional level. Here, we demonstrate that these different methods of lowering water potential elicit both shared and distinct transcriptional responses in Arabidopsis shoot and root tissue. When we compared these transcriptional responses to those found in Arabidopsis roots subject to vermiculite drying, we discovered many genes induced by vermiculite drying were repressed by low water potential treatments on agar plates (and vice versa). Additionally, we also tested another method for lowering water potential of agar media. By increasing the nutrient content and tensile strength of agar, we show the hard agar (HA) treatment can be leveraged as a high-throughput assay to investigate natural variation in Arabidopsis growth responses to low water potential.

plant biology↗

bioRxiv2022

Novel mRNA vaccines encoding Monkeypox virus M1R and A35R protect mice from a lethal virus challenge

The outbreak of Monkeypox virus infection urgently need effective vaccines. However, the vaccines so far approved are all based on whole-virus, which raises safety concerns. MRNA vaccines has demonstrated its high efficacy and safety against SARS-Cov-2 infection. Here, we developed three mRNA vaccines encoding Monkeypox proteins M1R and A35R, including A35R-M1R fusions (VGPox1 and VGPox 2) and a combination of encapsulated full-length mRNAs for A35R and M1R (VGPox 3). All three vaccines induced anti-A35R total IgGs as early as day 7 following a single vaccination. However, only VGPox 1 and 2 produced anti-M1R total IgGs at early dates following vaccination while VGPox 3 did not show significant anti-M1R antibody till day 35. Similar results were also found in neutralizing antibodies and T cell immune response. However, all mRNA vaccine groups completely protected mice from a lethal dose virus challenge and effectively cleared virus in lungs. Collectively, our results indicate that the novel mRNA vaccines coding for a fusion protein of A35R and M1R had a better anti-virus immunity than co-expression of the two individual proteins. The mRNA vaccines are highly effective and can be an alternative to the current whole-virus vaccines to defend Monkeypox virus infection.

immunology↗

bioRxiv2022

SBMLKinetics: A Tool for Annotation Independent Data Driven Classification of Reaction Kinetics for SBML Models

BackgroundReaction networks are widely used as mechanistic models in systems biology to reveal principles of biological systems. Reactions are governed by kinetic laws that describe reaction rates. Selecting the appropriate kinetic laws is difficult for many modelers. There exist tools that attempt to find the correct kinetic laws based on annotations. Here, I developed annotation-independent technologies that assist modelers by focusing on finding kinetic laws commonly used for similar reactions. ResultsRecommending kinetic laws and other analyses of reaction networks can be viewed as a classification problem. Existing approaches to determining similar reactions rely heavily on having good annotations, a condition that is often unsatisfied in model repositories such as BioModels. I developed an annotation-independent approach to find similar reactions via reaction classifications. I proposed a two-dimensional kinetics classification scheme (2DK) that analyzed reactions along the dimensions of kinetics type (K type) and reaction type (R type). I identified approximately ten mutually exclusive K types, including zeroth order, mass action, Michaelis-Menten, Hill kinetics, and others. R types were organized by the number of distinct reactants and the number of distinct products in reactions. I constructed a tool, SBMLKinetics, that inputted a collection of SBML models and then calculated reaction classifications as the probability of each 2DK class. The effectiveness of 2DK was evaluated on BioModels, and the scheme classified over 95% of the reactions. Conclusions2DK had many applications. It provided a data-driven annotation-independent approach to recommending kinetic laws by using type common for the kind of models in combination with the R type of the reactions. Alternatively, 2DK could also be used to alert users that a kinetic law was unusual for the K type and R type. Last, 2DK provided a way to analyze groups of models to compare their kinetic laws. I applied 2DK to BioModels to compare the kinetics of signaling networks with the kinetics of metabolic networks and found significant differences in K type distributions.

systems biology↗

bioRxiv2022

An evolutionarily conserved olfactory receptor is required for sex differences in blood pressure

Sex differences in blood pressure are well-established, with premenopausal women having lower blood pressure than men by [~]10mmHg; however, the underlying mechanisms are not fully understood. We report here that olfactory receptor 558 (Olfr558), which has not previously been studied in non-olfactory tissues, localizes to vascular smooth muscle cells in numerous tissues including the kidney and heart. In the kidney, Olfr558 colocalizes with renin (a hormone that plays a key role in blood pressure regulation) in the renal afferent arteriole. Based on the localization of Olfr558, we hypothesized that Olfr558 plays a role in blood pressure regulation. We find that sex differences in blood pressure are intact in Olfr558 wildtype (WT) mice, but, are absent in Olfr558 knockout (KO) mice. We find that male KO mice have lowered diastolic blood pressure, decreased renin expression and activity, and altered vascular reactivity. Female KO mice exhibit increased blood pressure and increased pulse wave velocity, indicating increased vascular stiffness. The human ortholog of Olfr558, OR51E1, was previously identified as a locus associated with diastolic blood pressure. We report here that a rare OR51E1 missense variant has a statistically significant sex interaction effect with diastolic blood pressure, increasing diastolic blood pressure in women but decreasing it in men. In addition, we characterize how two different clinically relevant OR51E1 variants influence OR51E1 signaling in vitro. In sum, our findings demonstrate an evolutionarily conserved role for Olfr558/OR51E1 to mediate sex differences in blood pressure by altering renin, vascular reactivity, and arterial stiffness.

physiology↗

bioRxiv2022

Three-dimensional molecular architecture of mouse organogenesis

Mammalian embryos have sophisticated cell organizations that are orchestrated by molecular regulation at cellular and tissue level. It has recently been appreciated that the cells that make up the animal body themselves harbor significant heterogeneity in the context of both cellular and particularly spatial dimension. However, current spatial transcriptomics profiling of embryonic tissues either lack three-dimensional representation or are restricted to limited depth and organs. Here, we reported a holistic spatial transcriptome atlas of all major organs at embryonic day 13.5 of mouse embryo and delineated a 3D rendering of the molecular regulation of embryonic patterning. By integrating with corresponding single-cell transcriptome data, the spatial organogenesis atlas provides rich molecular annotation of the dynamic organ nature, spatial cellular interaction, embryonic axes and divergence of cell fates underlying mammalian development, which would pave the way for precise organ-engineering and stem-cell based regenerative medicine.

developmental biology↗

bioRxiv2022

Identification and Characterization of ML321: a Novel and Highly Selective D2 Dopamine Receptor Antagonist with Efficacy in Animal Models that Predict Atypical Antipsychotic Activity

We have developed and characterized a novel D2R antagonist with exceptional GPCR selectivity - ML321. In functional profiling screens of 168 different GPCRs, ML321 showed little activity beyond potent inhibition of the D2R, and to a lesser extent the D3R, demonstrating excellent receptor selectivity. The D2R selectivity of ML321 may be related to the fact that, unlike other monoaminergic ligands, ML321 lacks a positively charged amine group and adopts a unique binding pose within the orthosteric binding site of the D2R. PET imaging studies in non-human primates demonstrated that ML321 penetrates the CNS and occupies the D2R in a dose-dependent manner. Behavioral paradigms in rats demonstrate that ML321 can selectively antagonize a D2R-mediated response (hypothermia) while not affecting a D3R-mediated response (yawning) using the same dose of drug, thus indicating exceptional in vivo selectivity. We also investigated the effects of ML321 in animal models that are predictive of antipsychotic efficacy in humans. We found that ML321 attenuates both amphetamine- and phencyclidine-induced locomotor activity and restored pre-pulse inhibition (PPI) of acoustic startle in a dose-dependent manner. Surprisingly, using doses that were maximally effective in both the locomotor and PPI studies, ML321 was relatively ineffective in promoting catalepsy. Kinetic studies revealed that ML321 exhibits slow-on and fast-off receptor binding rates, similar to those observed with atypical antipsychotics with reduced extrapyramidal side effects. Taken together, these observations suggest that ML321, or a derivative thereof, may exhibit "atypical" antipsychotic activity in humans with significantly fewer side effects than observed with currently FDA-approved D2R antagonists.

pharmacology and toxicology↗

bioRxiv2022

Human cerebrospinal fluid sample preparation and annotation for integrated lipidomics and metabolomics profiling studies

ObjectiveMass spectrometry (MS)-based lipidomics and metabolomics approaches play an essential role in identifying molecular profiles and relevant clinical biomarkers associated with diseases. Cerebrospinal fluid (CSF) is a metabolically diverse biofluid and a key specimen for exploring biochemical changes in neurodegenerative diseases because its composition reflects brain metabolic activity. CSF lipidomics is receiving increasing attention owing to the importance of lipids in brain molecular signaling and their association with several neurological diseases. Detecting lipid species in CSF using MS-based techniques remains challenging because lipids are highly complex in structure and their concentrations span over a broad dynamic range. This work aimed to develop a robust lipidomics and metabolomics method based on commonly used two-phase extraction systems from human CSF samples. MethodsPrioritizing lipid detection, biphasic extraction methods, Folch, Bligh & Dyer (B&D), Matyash and acidified Folch and B&D (aFolch and aB&D), were compared using 150 l of human CSF samples (n=6) for the simultaneous extraction of lipids and metabolites with a wide range of polarity in a single extraction. Multiple chromatographical separation approaches, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), and gas chromatography (GC), were utilized to characterize human CSF metabolome through MS-based untargeted approaches. ResultsA total of 219 lipids across 12 lipid subclasses were identified in CSF samples using RPLC-MS/MS. The aB&D method was found as the most reproducible technique (RSD <15%) for lipid extraction. We found remarkable differences in extraction efficiencies among the five different procedures. The aB&D and B&D yielded the highest peak intensities for targeted lipid internal standards and displayed superior extracting power for major endogenous lipid classes. A total of 674 unique metabolites with a wide polarity range were annotated in CSF using, combining RPLC-MS/MS (n=219), HILIC-MS/MS (n=304) and GC-QTOF MS (n=151). ConclusionsOverall, our findings show that the aB&D extraction method provided suitable lipid coverage, reproducibility, and extraction efficiency for global lipidomics profiling of human CSF samples. In combination with RPLC-MS/MS lipidomics, complementary screening approaches enabled a comprehensive metabolite signature that can be employed in an array of clinical studies.

biochemistry↗

bioRxiv2022

Oral Feeding of Nanoplastics reduces Brain function of Mice by Inducing Intestinal IL-1β-producing Macrophages

Background and AimsNanoplastics (NPs) as contaminants in food and water have drawn an increasing public attention. However, little is known about how NPs shape the gut immune landscape after entering the body. The objective of the study was to explore indirect effects caused by the interaction of NPs with the mammalian gut and whole immune system after entering the body. MethodsIn this study, we fabricated NPs ([~]500 nm) and microplastics (MPs) ([~]2 m) and aimed to evaluate their in vivo effects by feeding them in mice. The mechanism was then investigated by various technology including single-cell RNA sequencing of gut and brain tissue. ResultsThe results suggested that NPs showed a better ability to induce gut macrophage activation than did MPs. In addition, NPs triggered gut interleukin 1 beta (IL-1{beta})-producing macrophage reprogramming via inducing lysosomal damage after phagocytosis. More importantly, IL-1{beta} released from the intestine could affect brain immunity, leading to microglial activation and Th17 differentiation, all of which correlated with a decline in cognitive and short-term memory in NPs-fed mice ConclusionsThus, this study provides new insight into the mechanism of action of the gut-brain axis and delineates the way NPs reduce brain function, highlights the importance to fix the plastic pollution problem worldwide.

immunology↗