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Xu, S.

Publications and source records attributed to Xu, S..

At least 253 records · Page 14Linked to original sources
bioRxiv2023

Discovery of First-in-Class PROTAC Degraders of SARS-CoV-2 Main Protease

We have witnessed three coronavirus (CoV) outbreaks in the past two decades, including the COVID-19 pandemic caused by SARS-CoV-2. Main protease (MPro) is a highly conserved and essential protease that plays key roles in viral replication and pathogenesis among various CoVs, representing one of the most attractive drug targets for antiviral drug development. Traditional antiviral drug development strategies focus on the pursuit of high-affinity binding inhibitors against MPro. However, this approach often suffers from issues such as toxicity, drug resistance, and a lack of broad-spectrum efficacy. Targeted protein degradation represents a promising strategy for developing next-generation antiviral drugs to combat infectious diseases. Here we leverage the proteolysis targeting chimera (PROTAC) technology to develop a new class of small-molecule antivirals that induce the degradation of SARS-CoV-2 MPro. Our previously developed MPro inhibitors MPI8 and MPI29 were used as MPro ligands to conjugate a CRBN E3 ligand, leading to compounds that can both inhibit and degrade SARS-CoV-2 MPro. Among them, MDP2 was demonstrated to effectively reduce MPro protein levels in 293T cells (DC50 = 296 nM), relying on a time-dependent, CRBN-mediated, and proteasome-driven mechanism. Furthermore, MPD2 exhibited remarkable efficacy in diminishing MPro protein levels in SARS-CoV-2-infected A549-ACE2 cells, concurrently demonstrating potent anti-SARS-CoV-2 activity (EC50 = 492 nM). This proof-of-concept study highlights the potential of PROTAC-mediated targeted protein degradation of MPro as an innovative and promising approach for COVID-19 drug discovery.

biochemistry↗
bioRxiv2023

Flexible 3-D Electrochemical Impedance Spectroscopy Sensors Incorporating Phase Delay for Comprehensive Characterization of Atherosclerosis

BackgroundDistinguishing quiescent from rupture-prone atherosclerotic lesions has significant translational and clinical implications. Electrochemical impedance spectroscopy (EIS) characterizes biological tissues by assessing impedance and phase delay responses to alternating current at multiple frequencies. We evaluated invasive 6-point stretchable EIS sensors over a spectrum of experimental atherosclerosis and compared results with intravascular ultrasound (IVUS), molecular positron emission tomography (PET) imaging, and histology. MethodsMale New Zealand White rabbits (n=16) were placed on a high-fat diet for 4 or 8 weeks, with or without endothelial denudation via balloon injury of the infrarenal abdominal aorta. Rabbits underwent in vivo micro-PET imaging of the abdominal aorta with 68Ga-DOTATATE, 18F-NaF, and 18F-FDG, followed by invasive interrogation via IVUS and EIS. Background signal corrected values of impedance and phase delay were determined. Abdominal aortic samples were collected for histological analyses. Analyses were performed blindly. ResultsPhase delay correlated with anatomic markers of plaque burden, namely intima/media ratio (r=0.883 at 1 kHz, P=0.004) and %stenosis (r=0.901 at 0.25 kHz, P=0.002), similar to IVUS. Moreover, impedance was associated with markers of plaque activity including macrophage infiltration (r=0.813 at 10 kHz, P=0.008) and macrophage/smooth muscle cell (SMC) ratio (r=0.813 at 25 kHz, P=0.026). 68Ga-DOTATATE correlated with intimal macrophage infiltration (r=0.861, P=0.003) and macrophage/SMC ratio (r=0.831, P=0.021), 18F-NaF with SMC infiltration (r=-0.842, P=0.018), and 18F-FDG correlated with macrophage/SMC ratio (r=0.787, P=0.036). ConclusionsEIS with phase delay integrates key atherosclerosis features that otherwise require multiple complementary invasive and non-invasive imaging approaches to capture. These findings indicate the potential of invasive EIS as a comprehensive modality for evaluation of human coronary artery disease. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/558681v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1d02071org.highwire.dtl.DTLVardef@101ec0eorg.highwire.dtl.DTLVardef@130bff7org.highwire.dtl.DTLVardef@18b0955_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIElectrochemical impedance spectroscopy (EIS) characterizes both anatomic features - via phase delay; and inflammatory activity - via impedance profiles, of underlying atherosclerosis. C_LIO_LIEIS can serve as an integrated, comprehensive metric for atherosclerosis evaluation by capturing morphological and compositional plaque characteristics that otherwise require multiple imaging modalities to obtain. C_LIO_LITranslation of these findings from animal models to human coronary artery disease may provide an additional strategy to help guide clinical management. C_LI

bioengineering↗
bioRxiv2023

SECRET AGENT O-GlcNAcylates hundreds of proteins involved in diverse cellular processes in Arabidopsis

O-GlcNAcylation is a critical post-translational modification of proteins observed in both plants and animals and plays a key role in growth and development. While considerable knowledge exists about over 3000 substrates in animals, our understanding of this modification in plants remains limited. Unlike animals, plants possess two putative homologs: SECRET AGENT (SEC) and SPINDLY (SPY), with SPY also exhibiting O-fucosylation activity. To investigate SECs role as a major O-GlcNAc transferase in plants, we utilized LWAC enrichment and SILIA labeling, quantifying at both MS1 and MS2 levels. Our findings reveal a significant reduction in O-GlcNAc levels in the sec mutant, indicating SECs critical role in mediating O-GlcNAcylation. Through a comprehensive approach, combining HCD and EThcD fragmentation with substantial fractionations, we expanded our GlcNAc profiling, identifying 436 O-GlcNAc targets, including 227 new targets. The targets span diverse cellular processes, suggesting broad regulatory functions of O-GlcNAcylation. The expanded targets also enabled exploration of crosstalk between O-GlcNAcylation and O-fucosylation. We also examined EThcD fragmentation for site assignment. This report advances our understanding of O-GlcNAcylation in plants, facilitating further research in this field.

plant biology↗
bioRxiv2023

Sclerotic prostate cancer bone metastasis: woven bone lesions with a twist.

Bone metastasis (BM) are the most severe and prevalent consequences of prostate cancer (PC) affecting more than 80% of patients with advanced PC. PCBM generate pain, pathological fractures, and paralysis. As modern therapies increase survival, more patients are suffering from these catastrophic consequences of PCBM. Radiographically, PCBM are predominantly osteosclerotic, but the mechanisms of abnormal bone formation, and how this "more and new" bone is related to fractures is unclear. In this study, we conducted a comprehensive analysis on a cohort of 76 cadaveric PCBM samples and 12 from non-PC donors as control. We used -CT to determine three-dimensional organization and quantify bone characteristics, quantitative backscattering electron microscopy to characterize mineral content and details in bone structure, nano indentation to determine mechanical properties, and we finalize with histological and immunohistochemical analysis of bone structure and composition. We define 4 phenotypes of PCBM, osteolytic, mixed lytic-sclerotic, and two subgroups of osteosclerotic lesions, those with residual trabeculae, and others without residual trabeculae. The osteosclerotic lesions are characterized by the presence of abnormal bone within the trabeculae surfaces and intertrabecular spaces. This abnormal bone is characterized by higher lacunae density, abnormal lacunae morphology and orientation. However, we observed no significant difference between this irregular bone and residual trabeculae in terms of mineral content, hardness, and elastic modulus at micron-scale. The collagen matrix of this abnormal bone presents with irregular organization and is accompanied by increased proteoglycan and phosphorylated glycoprotein content. These characteristics suggests the presence of woven bone in PCBM. However, the lack of subsequent bone remodelling, absence of lamellar bone deposition on its surface, absence of markers of matrix vesicles but evidence of alkaline phosphatase dominated mineralization and collagen-III structure, set up differences from woven bone, while the role of PC cells in inducing this irregular bone phenotype remains unclear.

cancer biology↗
bioRxiv2023

Permanent Neonatal Diabetes-causing Insulin Mutations have Dominant Effects on Proinsulin Processing and Beta Cell Identity

Heterozygous coding sequence mutations of the INS gene are a cause of permanent neonatal diabetes (PNDM) that results from beta cell failure. We explored the causes of beta cell failure in two PNDM patients with two distinct INS mutations. Using b and mutated hESCs, we detected accumulation of misfolded proinsulin and impaired proinsulin processing in vitro, and a dominant-negative effect of these mutations on the in vivo performance of patient-derived SC-beta cells after transplantation into NSG mice. These insulin mutations derange endoplasmic reticulum (ER) homeostasis, and result in the loss of beta-cell mass and function. In addition to anticipated apoptosis, we found evidence of beta-cell dedifferentiation, characterized by an increase of cells expressing both Nkx6.1 and ALDH1A3, but negative for insulin and glucagon. These results highlight both known and novel mechanisms contributing to the loss and functional failure of human beta cells with specific insulin gene mutations.

cell biology↗
bioRxiv2023

Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language Model

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Anti-body Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials.

bioinformatics↗
bioRxiv2023

Structure of a benzosulfonamide based inhibitor 11l bound to a disulfide stabilised HIV-1 capsid hexamer

The Human Immunodeficiency Virus Type 1 (HIV-1) continues to be a major global health issue, with infection leading to Acquired Immunodeficiency Syndrome (AIDS). Despite advances in antiviral therapy, the need for new and more effective treatments remains critical. In this study, we determined the structure of the disulfide stabilised HIV-1 capsid protein hexamer in complex with the novel antiviral capsid inhibitor compound 11l. The structure revealed the presence of six 11l molecules bound to the capsid hexamer in a conserved site shared by nuclear import factors, and other capsid inhibitor compounds such as PF74 and GS-6207. The 11l compound exhibits disorder in the benzo-sulfonamide groups and disruption in the loop between helix 8 and 9 for the capsid C-terminal domain, an important 2-fold symmetry axis for hexamer formation. Our findings provide insights into the mechanism of action of 11l as a capsid inhibitor and antiviral. These results contribute to the ongoing efforts to develop more effective antiviral treatments for the global burden of HIV and AIDS. SynopsisInsight into the mechanism of action for a novel HIV-1 capsid inhibitor antivirals are elucidated by structure of HIV-1 capsid hexamer bound to the novel inhibitor compound 11l.

biochemistry↗
bioRxiv2023

Proteogenomic characterization reveals antitumor mechanisms of intrahepatic cholangiocarcinoma

Diagnosing and managing intrahepatic cholangiocarcinoma (iCCA) poses a significant oncological hurdle as it is a deadly form of liver cancer.A significant role is played by nonapoptotic regulatory cell death (NRCD) in the tumor immune microenvironment (TME) of iCCA. Nevertheless, the precise functions of NRCD-associated genes (NRGs) in the tumor microenvironment (TME) are still not well understood. Transcriptomics, proteomic analysis, and single-cell RNA analysis were utilized to distinguish two NRG-related clusters in iCCA patients from the FU-iCCA cohort in this study. We have shown the clear disparities in immune traits and predictive categorization among two groups. To address the risk stratification and prognosis prediction, a prognostic signature model called NPS (NRG-related risks core prognostic signature model) was created using the FU-iCCA cohort. The validation of the NRG-associated risk score in prognosis and immunotherapy confirmed its predictive capabilities. In iCCA patients with high-risk, the secretion of CP and TGF-{beta} proteins strengthened the enriched TGF-{beta} signaling network between CD4+ T cells and erythroid cells. Patients exhibiting a low-risk score demonstrated improvement in the effector function of CD4+ T cells, resulting in a more favorable reaction to chemotherapy medications. The NPS-risk score showed a significant negative correlation with the IC50 values of four drugs (Trametinib, CI-1040, X17-ACC, and PD-0325901). From these findings, it can be inferred that a clear connection exists between the NRG and the TME in iCCA. Additionally, the risk score has the potential to act as a reliable prognostic indicator, offering advantageous outcomes for chemotherapy and immunotherapy. This could aid in making informed clinical decisions for patients with iCCA.

biochemistry↗
bioRxiv2023

Mechanoreceptive Aβ primary afferents discriminate naturalistic social touch inputs at a functionally relevant time scale

Interpersonal touch is an important part of our social and emotional interactions. How these physical, skin-to-skin touch expressions are processed in the peripheral nervous system is not well understood. From single-unit microneurography recordings in humans, we evaluated the capacity of six subtypes of cutaneous afferents to differentiate perceptually distinct social touch expressions. By leveraging conventional statistical analyses and classification analyses using convolutional neural networks and support vector machines, we found that single units of multiple A{beta} subtypes, especially slowly adapting type II (SA-II) and fast adapting hair follicle afferents (HFA), can reliably differentiate the skin contact of those expressions at accuracies similar to those perceptually. Rapidly adapting field (Field) afferents exhibit lower accuracies, whereas C-tactile (CT), fast adapting Pacinian corpuscles (FA-II), and muscle spindle (MS) afferents can barely differentiate the expressions, despite responding to the stimuli. We then identified the most informative firing patterns of SA-II and HFA afferents spike trains, which indicate that an average duration of 3-4 s of firing provides sufficient discriminative information. Those two subtypes also exhibit robust tolerance to shifts in spike-timing of up to 10 ms. A greater shift in spike-timing, however, drastically compromises an afferents discrimination capacity, and can change a firing patterns envelope to resemble that of another expression. Altogether, the findings indicate that SA-II and HFA afferents differentiate the skin contact of social touch at time scales relevant for such interactions, which is 1-2 orders of magnitude longer than those relevant for discriminating non-social touch inputs.

neuroscience↗
bioRxiv2023

Population genomics and epigenomics provide insights into the evolution of facultative asexuality in plants

Many organisms, particularly plants, are facultatively asexual. Because asexual reproduction is beneficial for the short term but costly for the long term, during the range expansion, natural selection should act on the genetic controls of asexuality in these facultatively asexual organisms. However, the genomic evidence of natural selection driving asexuality remains scarce, and the evolutionary consequences of facultatively asexuality on the genomic and epigenomic diversity remain controversial. Here, by analyzing population genomes and epigenomes of Spirodela polyrhiza (L.) Schleid., a facultatively asexual plant that flowers rarely, we show that this plant has the lowest genomic diversity and DNA methylation levels among all studied multicellular eukaryotes. Within species, demographic history and the frequency of asexual reproduction jointly determined intra-specific variations of genomic diversity and DNA methylation levels. Genome-wide scans revealed that multiple genes involved in flowering and embryogenesis were under positive selection, consistent with the hypothesis that natural selection drove the evolution of asexuality during the recent habitat expansions in this plant. Together, these results provide new insights into the evolution of plant reproductive systems and suggest that natural selection can drive the evolutionary changes of asexuality, which in turn alters the levels of genomic and epigenomic diversity.

evolutionary biology↗
bioRxiv2023

Long-Distance Electron Transport in Multicellular Freshwater Cable Bacteria

Filamentous multicellular cable bacteria perform centimeter-scale electron transport in a process that couples oxidation of an electron donor (sulfide) in deeper sediment to the reduction of an electron acceptor (oxygen or nitrate) near the surface. While this electric metabolism is prevalent in both marine and freshwater sediments, detailed electronic measurements of the conductivity previously focused on the marine cable bacteria (Candidatus Electrothrix), rather than freshwater cable bacteria, which form a separate genus (Candidatus Electronema) and contribute essential geochemical roles in freshwater sediments. Here, we characterize the electron transport characteristics of Ca. Electronema cable bacteria from Southern California freshwater sediments. Current-voltage measurements of intact cable filaments bridging interdigitated electrodes confirmed their persistent conductivity under a controlled atmosphere and the variable sensitivity of this conduction to air exposure. Electrostatic and conductive atomic force microscopies mapped out the characteristics of the cell envelopes nanofiber network, implicating it as the conductive pathway in a manner consistent with previous findings in marine cable bacteria. Four-probe measurements of microelectrodes addressing intact cables demonstrated nanoampere currents up to 200 m lengths at modest driving voltages, allowing us to quantify the nanofiber conductivity at 0.1 S/cm for freshwater cable bacteria filaments under our measurement conditions. Such a high conductivity can support the remarkable sulfide-to-oxygen electrical currents mediated by cable bacteria in sediments. These measurements expand the knowledgebase of long-distance electron transport to the freshwater niche while shedding light on underlying conductive network of cable bacteria. SignificanceCable bacteria are multicellular filaments composed of up-to-thousands of end-to-end cells and are found worldwide in both marine and freshwater sediments. Remarkably, these cells gain energy from a long-distance electron transport process that carries electrons generated by sulfide oxidation in deeper sediment layers to drive oxygen reduction near the sediment-water interface. This electric metabolism requires an unusually high electronic conductivity, previously thought impossible in natural biological materials. However, the underlying mechanism(s) remain poorly understood, and previous characterization of the conductivity largely focused on marine cable bacteria. Here, we characterize and quantify the electronic conductivity of freshwater cable bacteria from sediments in Southern California, with emphasis on the role of the conductive periplasmic fiber network in routing electron transport along cables.

biophysics↗
bioRxiv2023

Leveraging Permutation Testing to Assess Confidence in Positive-Unlabeled Learning Applied to High-Dimensional Biological Datasets

BackgroundCompared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify "unlabeled" samples based on a smaller proportion of known positive examples. This more challenging modeling goal reflects many real-world scenarios in which negative examples are not available, posing direct challenges to defining prediction accuracy robustness. While several studies have evaluated predictions learned from only definitive positive examples, few have investigated whether correct classification of a high proportion of known positives (KP) samples from among unlabeled samples can act as a surrogate to indicate a performance. ResultsIn this study, we report a novel methodology combining multiple established PU learning-based strategies to evaluate the potential of KP samples to accurately classify unlabeled samples without using "ground truth" positive and negative labels for validation. To address model robustness, we report the first application of permutation test in PU learning. Multivariate synthetic datasets and real-world high-dimensional benchmark datasets were employed to validate the proposed pipeline with varied underlying ground truth class label compositions among the unlabeled set and different proportions of KP examples. Comparisons between model performance with actual and permutated labels could be used to distinguish reliable from unreliable models. ConclusionsLike in fully supervised machine learning, permutation testing offers a means to set a baseline "no-information rate" benchmark in the context of semi-supervised PU learning inference tasks against which model performance can be compared.

bioinformatics↗
bioRxiv2023

Strengthening E-cadherin adhesion via antibody mediated binding stabilization.

E-cadherins (Ecads) are a crucial cell-cell adhesion protein with tumor suppression properties. Ecad adhesion can be enhanced by the monoclonal antibody 66E8, which has potential applications in inhibiting cancer metastasis. However, the biophysical mechanisms underlying 66E8 mediated adhesion strengthening are unknown. Here, we use molecular dynamics simulations, site directed mutagenesis and single molecule atomic force microscopy experiments to demonstrate that 66E8 strengthens Ecad binding by stabilizing the primary Ecad adhesive conformation: the strand-swap dimer. By forming electrostatic interactions with Ecad, 66E8 stabilizes the swapped {beta}-strand and its hydrophobic pocket and impedes Ecad conformational changes, which are necessary for rupture of the strand-swap dimer. Our findings identify fundamental mechanistic principles for strengthening of Ecad binding using monoclonal antibodies.

biophysics↗
bioRxiv2023

HCCDB v2.0: Decompose the Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). By integrating 15 transcriptomic datasets of HCC clinical samples, the first version of HCCDB was released in 2018. The meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. After four years, the database needs to integrate recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics provided a great opportunity to decipher the complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size, adding 1656 new samples of 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric was proposed to summarize the cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

cancer biology↗
bioRxiv2023

AGILE Platform: A Deep Learning-Powered Approach to Accelerate LNP Development for mRNA Delivery

Ionizable lipid nanoparticles (LNPs) have seen widespread use in mRNA delivery for clinical applications, notably in SARS-CoV-2 mRNA vaccines. Despite their successful use, expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored to different target cell types. The traditional process of LNP development remains labor-intensive and cost-inefficient, relying heavily on trial and error. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines the iterative development of ionizable lipids, crucial components for LNP-mediated mRNA delivery. This approach brings forth three significant features: efficient design and synthesis of combinatorial lipid libraries, comprehensive in silico lipid screening employing deep neural networks, and adaptability to diverse cell lines. Using AGILE, we were able to rapidly design, synthesize, and evaluate new ionizable lipids for mRNA delivery in muscle and immune cells, selecting from a library of over 10,000 candidates. Importantly, AGILE has revealed cell-specific preferences for ionizable lipids, indicating the need for different tail lengths and head groups for optimal delivery to varying cell types. These results underscore the potential of AGILE in expediting the development of customized LNPs. This could significantly contribute to addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies. One Sentence SummaryAI and combinatorial chemistry expedite ionizable lipid creation for mRNA delivery.

biochemistry↗
bioRxiv2023

Pore-forming activity of S. pneumoniae pneumolysin disrupts the paracellular localization of the epithelial adherens junction protein E-cadherin

Streptococcus pneumoniae, a common cause of community-acquired bacterial pneumonia, can cross the respiratory epithelial barrier to cause lethal septicemia and meningitis. S. pneumoniae pore-forming toxin pneumolysin (PLY) triggers robust neutrophil (PMN) infiltration that promotes bacterial transepithelial migration in vitro and disseminated disease in mice. Apical infection of polarized respiratory epithelial monolayers by S. pneumoniae at a multiplicity of infection (MOI) of 20 resulted in recruitment of PMNs, loss of 50% of the monolayer, and PMN-dependent bacterial translocation. Reducing the MOI to 2 decreased PMN recruitment two-fold and preserved the monolayer, but apical-to-basolateral translocation of S. pneumoniae remained relatively efficient. At both MOI of 2 and 20, PLY was required for maximal PMN recruitment and bacterial translocation. Co-infection by wild type S. pneumoniae restored translocation by a PLY-deficient mutant, indicating that PLY can act in trans. Investigating the contribution of S. pneumoniae infection on apical junction complexes in the absence of PMN transmigration, we found that S. pneumoniae infection triggered the cleavage and mislocalization of the adherens junction (AJ) protein E-cadherin. This disruption was PLY-dependent at MOI of 2 and was recapitulated by purified PLY, requiring its pore-forming activity. In contrast, at MOI of 20, E-cadherin disruption was independent of PLY, indicating that S. pneumoniae encodes multiple means to disrupt epithelial integrity. This disruption was insufficient to promote bacterial translocation in the absence of PMNs. Thus, S. pneumoniae triggers cleavage and mislocalization of E-cadherin through PLY-dependent and PLY-independent mechanisms, but maximal bacterial translocation across epithelial monolayers requires PLY-dependent neutrophil transmigration.

microbiology↗
bioRxiv2023

Seasonal Variation in Bacterial Community Structures of Mangrove Sediments

Climate change globally and sea level rise affect the mangrove ecosystem. The high diversity and temporal heterogeneity of the mangrove ecosystem will lead to a high diversity of sediment bacterial community structure and function. However, seasonal variations and potential assembly mechanisms of sediment bacterial communities in mangrove ecosystems remain to be discovered. We collected rhizosphere sediments and bulk sediments from Kandelia obovata and Aegiceras corniculatum at three locations covering Dongzhai Harbour in spring, summer, autumn, and winter, and sequenced 16S rRNAs. The results indicated that the alpha and beta diversity of bacterial communities in mangrove sediments differed significantly between seasons, and the bacterial communities in rhizosphere sediments had smaller seasonal changes and were more stable than those in bulk sediment bacterial communities. The seasonal changes in carbon, nitrogen content, and pH were the main influencing factors. The stochastic process dominated the assembly of bacterial communities in mangrove sediments. The assembly of bacterial communities varies between seasons. We found that the proportion of dispersal limitation was significantly negatively correlated with the carbon and nitrogen content in the sediment. Compared with bulk components, the dispersal limitation of bacterial communities in rhizosphere sediments accounted for a lower proportion of community construction, which might be caused by higher carbon and nitrogen content conditions in rhizosphere sediments. We found that beta diversity based on Bray-Curtis distance was significantly positively correlated with dispersal limitation, which explained why the beta diversity of bacterial communities in rhizosphere sediments was significantly lower than that of bulk components. This study increases the understanding of the responses of mangrove bacterial communities to seasonal change and may be beneficial for the protection of mangrove ecosystems in the face of climate change.

ecology↗