Biology subjects

Pan, S.

Publications and source records attributed to Pan, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Reciprocal inflammatory signals establish profibrotic cross-feeding metabolism

Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung remodeling and collagen deposition that leads to respiratory failure. Myeloid cells are abundant in IPF lung and in murine lung fibrosis, but their functional effects are incompletely understood. Using mouse and human lung models, we show that ornithine produced by myeloid cells expressing Arg1 serves as a substrate for proline and collagen synthesis by lung fibroblasts. The predominant Arg1-expressing myeloid cells in mouse lung were macrophages, but in IPF lung, high-dimensional imaging revealed ARG1 to be expressed mainly in neutrophils. Arg1 inhibition suppressed both ornithine levels and collagen expression in cultured, precision-cut IPF lung slices and in murine lung fibrosis. These results were confirmed in macrophage-specific Arg1 KO mice. Furthermore, we find that this pathway is regulated by cell-to-cell crosstalk, starting with purinergic signaling: Fibroblast eATP receptor P2rx4 was necessary for fibroblast IL-6 expression, which in turn was necessary for Arg1 expression by myeloid cells. Taken together, our findings define an immune-mesenchymal circuit that governs profibrotic metabolism in lung fibrosis.

immunology↗

bioRxiv2023

Multi-scale characterisation of homologous recombination deficiency in breast cancer

BackgroundHomologous recombination is a robust, broadly error-free mechanism of double strand break repair, and deficiencies cause reliance on alternative repair processes, leading to sensitivity to PARP inhibitors. Patients displaying homologous recombination deficiency can be identified using mutational signatures. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour. ResultsHere, we apply two methods for classifying homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. Firstly, we apply a likelihood-based method which leverages small insertions and deletions to improve classification of homologous recombination deficiency in exome sequenced breast cancers. We find that whilst BRCA+ homologous recombination deficient samples display strong similarities to those harbouring BRCA defects, they deviate in microenvironmental features such as hypoxic signalling. Secondly, using this classification we develop a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is linked with PARP inhibitor response. Finally, we apply this signature to single-cell RNA-sequenced breast cancer cohorts to study homologous recombination deficiency at single cell resolution and demonstrate that these cells present a distinct milieu of interactions with immune cells in their microenvironment compared to their HR proficient counterparts, which could inform checkpoint blockade for HRD tumours. ConclusionsWe apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We show that indels, even at low levels, can improve homologous recombination deficiency classification. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.

genomics↗

bioRxiv2023

Meningeal CSF transport is primarily mediated by the arachnoid and pia maters during development

BackgroundThe recent characterization of the glymphatic system and meningeal lymphatics has re-emphasized the role of the meninges in facilitating CSF transport and clearance. Here, we characterize small and large CSF solute distribution patterns along the intracranial and surface meninges in neonatal rodents and compare our findings to a rodent model of intraventricular hemorrhage-posthemorrhagic hydrocephalus. We also examine CSF interactions with the tela choroidea and its pial invaginations into the choroid plexuses of the lateral, third, and fourth ventricles. Methods1.9-nm gold nanoparticles, 15-nm gold nanoparticles, or 3 kDa Red Dextran Tetramethylrhodamine constituted in aCSF were infused into the right lateral ventricle of P7 rats to track CSF circulation. 10 minutes post-1.9-nm gold nanoparticle and Red Dextran Tetramethylrhodamine injection and 4 hours post-15-nm gold nanoparticle injection, animals were sacrificed and brains harvested for histologic analysis to identify CSF tracer localization in the cranial and spine meninges and choroid plexus. Spinal dura and leptomeninges (arachnoid and pia) wholemounts were also performed. ResultsThere was significantly less CSF tracer distribution in the dura compared to the arachnoid and pia maters in neonatal rodents. Both small and large CSF tracers were transported intracranially to the arachnoid and pia mater of the perimesencephalic cisterns and tela choroidea, but not the dura mater of the falx cerebri. CSF tracers followed a similar distribution pattern in the spinal meninges. In the choroid plexus, there was large CSF tracer distribution in the apical surface of epithelial cells, and small CSF tracer along the basolateral surface. There were no significant differences in tracer intensity in the intracranial meninges of control vs. intraventricular hemorrhage-posthemorrhagic hydrocephalus (PHH) rodents, indicating preserved meningeal transport in the setting of PHH. ConclusionsDifferential CSF tracer handling by the leptomeninges suggests that there are distinct roles for CSF handling between the arachnoid-pia and dura maters in the developing brain. Similarly, differences in apical vs. luminal choroid plexus CSF handling may provide insight into particle-size dependent CSF transport at the CSF-choroid plexus border.

neuroscience↗

bioRxiv2023

Extracting herbicide and antibiotic natural products from a plant-microbe interaction system

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways by proceeding in multi-dimensional, multi-scale and multi-level coupling manners, leading to challenges of the co-existence of randomness and determinism, or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of new data mining theories and methods for complex systems, new coupled modelling for the system with different spatiotemporal scales and functional properties, or even universal theory of information and information interactions. In this study, we use a "close-loop" model to present a plant-microbe interaction system and describe the probable functions from the microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and herbicides for crop protection. Detailed laboratory experiments combined with comprehensive bioinformatics analysis allow us to rationalise a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglectable resources for the identification of novel functional molecules and provides a good reference to better understand the system biology in the complex ecosystems.

cell biology↗

bioRxiv2023

Inferring Neuron-level Brain Circuit Connection via Graph Neural Network Amidst Small Established Connections

MotivationReconstructing neuron-level brain circuit network is a universally recognized formidable task. A significant impediment involves discerning the intricate interconnections among multitudinous neurons in a complex brain network. However, the majority of current methodologies only rely on learning local visual synapse features while neglecting the incorporation of comprehensive global topological connectivity information. In this paper, we consider the perspective of network connectivity and introduce graph neural networks to learn the topological features of brain networks. As a result, we propose Neuronal Circuit Prediction Network (NCPNet), a simple and effective model to jointly learn node structural representation and neighborhood representation, constructing neuronal connection pair feature for inferring neuron-level connections in a brain circuit network. ResultsWe use a small number of connections randomly selected from a single brain circuit network as training data, expecting NCPNet to extrapolate known connections to unseen instances. We evaluated our model on Drosophila connectome and C. elegans worm connectome. The numerical results demonstrate that our model achieves a prediction accuracy of 91.88% for neuronal connections in the Drosophila connectome when utilizing only 5% of known connections. Similarly, under the condition of 5% known connections in C. elegans, our model achieves an accuracy of 93.79%. Additional qualitative analysis conducted on the learned representation vectors of Kenyon cells indicates that NCPNet successfully acquires meaningful features that enable the discrimination of neuronal sub-types. Our project is available at https://github.com/mxz12119/NCPNet.

neuroscience↗

bioRxiv2023

HistoMIL: a Python package for training Multiple Instance Learning models on histopathology slides

Haematoxilin and eosin (H&E) stained slides are commonly used as the gold standard for disease diagnosis. Remarkable progress in the deep learning field in recent years has enabled the detection of complex molecular patterns within such histopathology slides, suggesting automated approaches could help inform pathologists decisions. In this context, Multiple Instance Learning (MIL) algorithms have been shown to outperform Transfer Learning (TL) based methods for a variety of tasks. However, there is still a considerable complexity to implementing and using such methods for computational biology research and clinical practice. We introduce HistoMIL, a Python package designed to simplify the implementation, training, and inference process of MIL-based algorithms for computational pathologists and biomedical researchers. In HistoMIL, we have integrated a self-supervised learning-based module to train the feature encoder, a full pipeline encompassing TL as well as three MIL algorithms, namely ABMIL (1), DSMIL (2), and TransMIL (3). By utilising the PyTorch Lightning framework (4), HistoMIL enables effortless customization of training intricacies and implementation of novel algorithms. We illustrate the capabilities of HistoMIL by building predictive models for 2,487 cancer hallmark genes on breast cancer histology slides from The Cancer Genome Atlas, on which we demonstrate AUROC performances of up to 85%. Cell proliferation processes were most easily detected, shedding light on the opportunities but also limitations of applying deep learning for gene expression detection. The HistoMIL package is proposed as a tool to simplify the implementation and usage of deep learning tasks for researchers.

pathology↗

bioRxiv2023

Lipid-anchored Proteasomes Control Membrane Protein Homeostasis

Protein degradation in eukaryotic cells is mainly carried out by the 26S proteasome, a macromolecular complex not only present in the cytosol and nucleus but also associated with various membranes. How proteasomes are anchored to the membrane and the biological meaning thereof have been largely unknown in higher organisms. Here we show that N-myristoylation of the Rpt2 subunit is a general mechanism for proteasome-membrane interaction. Loss of this modification in the Rpt2-G2A mutant cells leads to profound changes in the membrane-associated proteome, perturbs the endomembrane system and undermines critical cellular processes such as cell adhesion, endoplasmic reticulum-associated degradation (ERAD) and membrane protein trafficking. Rpt2G2A/G2A homozygous mutation is embryonic lethal in mice and is sufficient to abolish tumor growth in a nude mice xenograft model. These findings have defined an evolutionarily conserved mechanism for maintaining membrane protein homeostasis and underscored the significance of compartmentalized protein degradation by myristoyl-anchored proteasomes (MAPs) in health and disease.

biochemistry↗

bioRxiv2023

EVIDENCE FOR ANGIOTENSIN II AS A NATURALLY EXISTING SUPPRESSOR FOR THE NATRIURETIC PEPTIDE SYSTEM

BackgroundNatriuretic peptide system (NPS) and renin angiotensin aldosterone system (RAAS) function oppositely at multiple levels. While it has long been suspected that angiotensin II (ANGII) may directly suppress NPS activity, no clear evidence to date support this notion. ObjectivesThis study was designed to systematically investigate ANGII-NPS interaction in humans, in vivo, and in vitro for translational insights. MethodsCirculating atrial, b-type, and c-type natriuretic peptides (ANP, BNP, CNP), cyclic guanosine monophosphate (cGMP), and ANGII were simultaneously investigated in 128 human subjects. Prompted hypothesis was validated in rat model to determine influence of ANGII on ANP actions. Multiple engineered HEK293 cells and surface plasmon resonance (SPR) technology were leveraged for mechanistic exploration. ResultsIn humans, ANGII showed inverse relationship with ANP, BNP, and cGMP. In regression models predicting cGMP, adding ANGII levels and interaction term between ANGII and natriuretic peptide increased predicting accuracy of base models constructed with either ANP or BNP, but not CNP. Importantly, stratified correlation analysis further revealed positive association between cGMP with ANP or BNP only in subjects with low, but not high, ANGII levels. In rats, co-infusion of ANGII even at physiological dose attenuated blood pressure reduction and cGMP generation triggered by ANP infusion. In vitro, we showed that the suppression effect of ANGII on ANP-stimulated cGMP requires the presence of ANGII type-1 (AT1) receptor and mechanistically involves protein kinase C (PKC), which can be substantially rescued by either valsartan (AT1 blocker) or Go6983 (PKC inhibitor). Using SPR, we showed ANGII has low affinity for particulate guanylyl cyclase A (GC-A) receptor binding compared to ANP or BNP. ConclusionsOur study reveals ANGII as a natural suppressor for cGMP-generating action of GC-A via AT1/PKC dependent manner and highlights importance of dual-targeting RAAS and NPS in maximizing beneficial properties of natriuretic peptides in cardiovascular disease. STRUCTURED GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/525806v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@6febe8org.highwire.dtl.DTLVardef@1e8e21corg.highwire.dtl.DTLVardef@54a98eorg.highwire.dtl.DTLVardef@47ade7_HPS_FORMAT_FIGEXP M_FIG C_FIG CLINICAL PERSPECTIVESAccumulating evidence continues to support the NPS as a promising therapeutic target via the function of the GC-A receptor and production of the second messenger cGMP for heart failure, hypertension, and other cardiovascular diseases. Improving our mechanistic understanding on GC-A/cGMP pathway regulation may further advance the development of novel NPS enhancing therapies. Here we report evidence from multiple avenues supporting a fundamental, yet previously underappreciated mechanism involving a negative action of ANGII in suppressing GC-A receptor-mediated cGMP production via an AT1 receptor-dependent manner. This study also provides a solid rationale for the superiority of combinatory neurohormonal therapies such as sacubitril/valsartan in treating cardiovascular disease, and further highlights a promising therapeutic avenue of dual targeting both the NPS and RAAS to maximize protection.

molecular biology↗

bioRxiv2023

SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing

MotivationMetagenomic binning methods to reconstruct metagenome-assembled genomes (MAGs) from environmental samples have been widely used in large-scale metagenomic studies. The recently proposed semi-supervised binning method, SemiBin, achieved state-of-the-art binning results in several environments. However, this required annotating contigs, a computationally costly and potentially biased process. ResultsWe propose SemiBin2, which uses self-supervised learning to learn feature embeddings from the contigs. In simulated and real datasets, we show that self-supervised learning achieves better results than the semi-supervised learning used in SemiBin1 and that SemiBin2 outperforms other state-of-the-art binners. Compared to SemiBin1, SemiBin2 can reconstruct 8.3%-21.5% more high-quality bins and requires only 25% of the running time and 11% of peak memory usage in real short-read sequencing samples. To extend SemiBin2 to long-read data, we also propose ensemble-based DBSCAN clustering algorithm, resulting in 13.1%-26.3% more high-quality genomes than the second best binner for long-read data. Availability and ImplementationSemiBin2 is available as open source software at https://github.com/BigDataBiology/SemiBin/ and the analysis scripts used in the study can be found at https://github.com/BigDataBiology/SemiBin2_benchmark.

bioinformatics↗

bioRxiv2022

A plant virus causes symptoms through the deployment of a host-mimicking protein domain to attract the insect vector

Viruses are obligate intracellular parasites with limited proteomes that heavily rely on the cell molecular machinery for their multiplication and spread. Plant viruses frequently cause symptoms through interference with host developmental programs. Despite the agricultural relevance of symptom development in virus-infected crops, the molecular mechanisms underlying these viral effects remain elusive. Here, we show that the symptoms triggered by tomato yellow leaf curl virus (TYLCV) depend on the physical interaction between the host-mimicking domain of a virus-encoded protein, C4, and a plant-specific family of RCC1-like domain-containing (RLD) proteins. C4 outcompetes endogenous interactors of RLDs, disrupting RLD function in the regulation of endomembrane trafficking and polar auxin transport, ultimately leading to the developmental alterations recognized as symptoms of the viral infection. Importantly, symptoms do not have a detectable effect on the performance of the virus in the plant host, but they serve as attractants for the viral insect vector, the whitefly Bemisia tabaci, hence promoting pathogen spread. Our work uncovers the molecular underpinnings of the viral manipulation that leads to symptom development in the TYLCV-tomato pathosystem, and suggests that symptoms have evolved as a strategy to promote viral transmission by the insect vector. Given that most plant viruses are insect-transmitted, the principles described here might have broad applicability to crop-virus interactions.

plant biology↗

bioRxiv2022

Mapping global land sharing-sparing patterns between human and wildlife

Understanding the global patterns of land sharing-sparing between humans and wildlife is essential for pragmatic conservation implementation, yet analytical foundations and indicator-based assessments are still lacking. By integrating distributions of 30,664 terrestrial vertebrates and human pressures, we provide a series of spatial explicit Human-Nature Indices (HNIs) before classifying the global lands into four categories. We found that the Co-occurring (C) regions, where lands are shared by humans and wildlife, are not insignificant (16.91% of global land). For land-sparing, the Diversity-intact (D) and the Anthropic (A) regions account for 45.64% and 1.41% of the land, respectively. The patterns of HNIs, varying considerably among taxonomic groups, are determined mainly by the expansion of human-dominated land use. Land sharing and sparing could work as complementary strategies to support biodiversity and human development toward ambitious and pragmatic 30 by 30 goals. Our results highlight that those regions should adopt different conservation strategies according to their sharing-sparing patterns and distribution of protected areas.

ecology↗

bioRxiv2022

In vivo and In vitro Characterization of the ClpC AAA+ ATPase of Chlamydia trachomatis

Bacterial AAA+ unfoldases are crucial for bacterial physiology by recognizing specific substrates and, typically, unfolding them for degradation by a proteolytic component. The caseinolytic protease (Clp) system is one example where a hexameric unfoldase (e.g., ClpC) interacts with the tetradecameric proteolytic core ClpP. Unfoldases can have both ClpP-dependent and ClpP-independent roles in protein homeostasis, development, virulence, and cell differentiation. ClpC is an unfoldase predominantly found in Gram-positive bacteria and mycobacteria. Intriguingly, the obligate intracellular Gram-negative pathogen Chlamydia, an organism with a highly reduced genome, also encodes a ClpC ortholog, implying an important function for ClpC in chlamydial physiology. Here, we used a combination of in vitro and in vivo approaches to gain insight into the function of chlamydial ClpC. ClpC exhibits intrinsic ATPase and chaperone activities, with a primary role for the Walker B motif in the first nucleotide binding domain (NBD1). Furthermore, ClpC binds ClpP1P2 complexes via ClpP2 to form the functional protease ClpCP2P1 in vitro, which degraded arginine-phosphorylated {beta}-casein. In vivo experiments confirmed that higher order complexes of ClpC are present in chlamydial cells. Importantly, the in vivo data further revealed severe negative effects of both overexpression and depletion of ClpC in Chlamydia as revealed by a significant reduction in chlamydial growth. Here again, NBD1 was critical for ClpC function. Hence, we provide the first mechanistic insight into the molecular and cellular function of chlamydial ClpC, which supports its essentiality in Chlamydia. ClpC is, therefore, a potential novel target for the development of anti-chlamydial agents. SignificanceChlamydia trachomatis is an obligate intracellular pathogen and the worlds leading cause of preventable infectious blindness and bacterial sexually transmitted infections. Due to the high prevalence of chlamydial infections along with negative effects of current broad-spectrum treatment strategies, new anti-chlamydial agents with novel targets are desperately needed. In this context, bacterial Clp proteases have emerged as promising new antibiotic targets, since they often play central roles in bacterial physiology and, for some bacterial species, are even essential for survival. Here, we report on the chlamydial AAA+ unfoldase ClpC, its functional reconstitution and characterization, individually and as part of the ClpCP2P1 protease, and establish an essential role for ClpC in chlamydial growth and intracellular development, thereby identifying ClpC as a potential target for anti-chlamydial compounds.

microbiology↗

bioRxiv2022

Transcriptome analysis of the binucleate ciliate Tetrahymena thermophila with asynchronous nuclear cell cycles

As a prototypic ciliated protozoan, Tetrahymena thermophila harbors two functionally and physically distinct nuclei within a shared cytoplasm. During vegetative growth, the cell cycles of the diploid germline micronucleus and polyploid somatic macronucleus are offset. Micronuclear S phase initiates just before cell division and is completed in daughter cells prior to the onset of macronuclear S phase. Whereas mitotic micronuclear division occurs mid-cell cycle, amitotic macronuclear division immediately precedes cytokinesis. Here we report the first RNA-seq analysis across the cell cycle of a binucleated organism. RNA was isolated at 30 min intervals across 1.5 vegetative cell cycles, starting with a macronuclear G1 population synchronized by centrifugal elutriation. Using MetaCycle, 3244 of the predicted 26,000+ T. thermophila genes were shown to be cell cycle regulated. Proteins that are required in micro- and macronuclei exhibit a single mRNA peak that correlates with their macronuclear function, while the expression of nucleus-limited protein-coding genes, including nucleoporins and importins, peak prior to their respective nucleus-specific role. Cyclin D and cyclin A/B genes showed distinct expression patterns that predict nucleus-specific functions. Clustering of periodically expressed genes revealed seven gene expression patterns. Four clusters have known PANTHER GO biological processes that are overrepresented for G1/S and G2/M phase functions. We propose that these clusters encode known and novel factors that coordinate micro- and macronuclear-specific events such as mitosis, amitosis, DNA replication and cell division.

bioinformatics↗

bioRxiv2022

A deep learning and graph-based approach to characterise the immunological landscape and spatial architecture of colon cancer tissue

Tumour immunity is key for the prognosis and treatment of colon adenocarcinoma, but its characterisation remains cumbersome and expensive, requiring sequencing or other complex assays. Detecting tumour-infiltrating lymphocytes in haematoxylin and eosin (H&E) slides of cancer tissue would provide a cost-effective alternative to support clinicians in treatment decisions, but inter- and intra-observer variability can arise even amongst experienced pathologists. Furthermore, the compounded effect of other cells in the tumour microenvironment is challenging to quantify but could yield useful additional biomarkers. We combined RNA sequencing, digital pathology and deep learning through the InceptionV3 architecture to develop a fully automated computer vision model that detects prognostic tumour immunity levels in H&E slides of colon adenocarcinoma with an area under the curve (AUC) of 82%. Amongst tumour infiltrating T cell subsets, we demonstrate that CD8+ effector memory T cell patterns are most recognisable algorithmically with an average AUC of 83%. We subsequently applied nuclear segmentation and classification via HoVer-Net to derive complex cell-cell interaction graphs, which we queried efficiently through a bespoke Neo4J graph database. This uncovered stromal barriers and lymphocyte triplets that could act as structural hallmarks of low immunity tumours with poor prognosis. Our integrated deep learning and graph-based workflow provides evidence for the feasibility of automated detection of complex immune cytotoxicity patterns within H&E-stained colon cancer slides, which could inform new cellular biomarkers and support treatment management of this disease in the future.

cancer biology↗

bioRxiv2022

Maps of high density microsatellites accumulation in human genome

BackgroundMicrosatellites are increasingly realized to have biological significance in human genome and health in past decades, the assembled complete reference sequence of human genome T2T-CHM13 brought great help for a comprehensive study of short tandem repeats in the human genome. ResultsMicrosatellites density landscapes of all 24 chromosomes were built here for the first complete reference sequence of human genome T2T-CHM13. These landscapes showed that short tandem repeats (STRs) are prone to aggregate characteristically to form a large number of STRs density peaks. We classified 8,823 High Microsatellites Density Peaks (HMDPs), 35,257 Middle Microsatellites Density Peaks (MMDPs) and 199, 649 Low Microsatellites Density Peaks (LMDPs) on the 24 chromosomes; and also classified the motif types of every microsatellites density peak. These STRs density aggregation peaks are mainly composing of a single motif, and AT is the most dominant motif, followed by AATGG and CCATT motifs. And 514 genomic regions were characterized by microsatellite density feature in the full T2T-CHM13 genome. ConclusionsThese landscape maps exhibited that microsatellites aggregate in many genomic positions to form a large number of microsatellite density peaks with composing of mainly single motif type in the complete reference genome, indicating that the local microsatellites density varies enormously along the every chromosome of T2T-CHM13.

bioinformatics↗

bioRxiv2022

Epac1 regulates cellular SUMOylation by promoting the formation of SUMO-activating nuclear condensates

Protein SUMOylation plays an essential role in maintaining cellular homeostasis when cells are under stress. However, precisely how SUMOylation is regulated, and a molecular mechanism linking cellular stress to SUMOylation remains elusive. Herein, we report that cAMP, a major stress-response second messenger, acts through Epac1 as a regulator of cellular SUMOylation. The Epac1-associated proteome is highly enriched with components of the SUMOylation pathway. Activation of Epac1 by intracellular cAMP triggers phase separation and the formation of nuclear condensates containing Epac1 and general components of the SUMOylation machinery to promote cellular SUMOylation. Furthermore, genetic knockout of Epac1 obliterates oxidized low-density lipoprotein induced cellular SUMOylation in macrophages, leading to suppression of foam cell formation. These results provide a direct nexus connecting two major cellular stress responses to define a molecular mechanism in which cAMP regulates the dynamics of cellular condensates to modulate protein SUMOylation.

cell biology↗

bioRxiv2021

An ultrapotent RBD-targeted biparatopic nanobody neutralizes broad SARS-CoV-2 variants

The wide transmission and host adaptation of SARS-CoV-2 have led to the rapid accumulation of mutations, posing significant challenges to the effectiveness of vaccines and therapeutic antibodies. Although several neutralizing antibodies were authorized for emergency clinical use, convalescent patients derived natural antibodies are vulnerable to SARS-CoV-2 Spike mutation. Here, we describe the screen of a panel of SARS-CoV-2 receptor-binding domain (RBD) targeted nanobodies (Nbs) from a synthetic library and the design of a biparatopic Nb, named Nb1-Nb2, with tight affinity and super wide neutralization breadth against multiple SARS-CoV-2 variants of concern. Deep-mutational scanning experiments identify the potential binding epitopes of the Nbs on the RBD and demonstrate that biparatopic Nb1-Nb2 has a strong escape resistant feature against more than 60 tested RBD amino acid substitutions. Using pseudovirion-based and trans-complementation SARS-CoV-2 tools, we determine that the Nb1-Nb2 broadly neutralizes multiple SARS-CoV-2 variants, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), Lambda (C.37), Kappa (B.1.617.1) and Mu (B.1.621). Furthermore, a heavy chain antibody is constructed by fusing the human IgG1 Fc to Nb1-Nb2 (designated as Nb1-Nb2-Fc) to improve its neutralization potency, yield, stability and potential half-life extension. For the new Omicron variant (B.1.1.529) that harbors unprecedented multiple RBD mutations, Nb1-Nb2-Fc keeps a firm affinity (KD < 1.0x10-12 M) and strong neutralizing activity (IC50 = 0.0017 nM). Together, we developed a tetravalent biparatopic human heavy chain antibody with ultrapotent and broad-spectrum SARS-CoV-2 neutralization activity which highlights the potential clinical applications.

microbiology↗

bioRxiv2021

Global cerebrospinal fluid circulation mapping using gold nanoparticle enhanced X-ray microtomography reveals region-specific brain and spinal cord CSF pathways

Cerebrospinal fluid (CSF) movement within the brain interstitium is essential for the development and functioning of the brain. However, the interstitium has largely been thought of as a single entity through which CSF circulates, and it is not known whether specific cell populations within the CNS preferentially interact with CSF. Here, we developed a novel technique for CSF tracking, gold nanoparticle enhanced X-ray microtomography, to achieve micrometer-scale resolution visualization of CSF pathways during development. Using this method and subsequent histological analysis, we map global CSF pathways and present novel particle size-dependent circulation patterns through the CNS. We identify an intraparenchymal CSF circulation that targets stem cell-rich and cholinergic neuronal populations. CSF solute distribution to these areas is mediated by CSF flow along projections from the basal cisterns which is altered in posthemorrhagic hydrocephalus. Our study uncovers region-specific patterns in a biologically driven CSF circulation that has implications for normal brain development and the pathophysiology of hydrocephalus and neurodegenerative disorders.

neuroscience↗