Novel Antibody-Based Protection/Therapeutics in Staphylococcus aureus.

Staphylococcus aureus is a commensal of the skin and nares of humans as well as the causative agent of infections associated with significant mortality. The acquisition of antibiotic resistance traits complicates the treatment of such infections and has prompted the development of monoclonal antibodies. The selection of protective antigens is typically guided by studying the natural antibody responses to a pathogen. What happens when the pathogen masks these antigens and subverts adaptive responses, or when the pathogen inhibits or alters the effector functions of antibodies? S. aureus is constantly exposed to its human host and has evolved all these strategies. Here, we review how anti-S. aureus targets have been selected and how antibodies have been engineered to overcome the formidable immune evasive activities of this pathogen. We discuss the prospects of antibody-based therapeutics in the context of disease severity, immune competence, and history of past infections.

Immunoglobulin G subclasses confer protection against Staphylococcus aureus bloodstream dissemination through distinct mechanisms in mouse models.

Antibodies bind target molecules with exquisite specificity. The removal of these targets is mediated by the effector functions of antibodies. We reported earlier that the monoclonal antibody (mAb) 3F6 promotes opsonophagocytic killing of Staphylococcus aureus in blood and reduces bacterial replication in animals. Here, we generated mouse immunoglobulin G (mIgG) subclass variants and observed a hierarchy in protective efficacy 3F6-mIgG2a > 3F6-mIgG1 ≥ 3F6-mIgG2b >> 3F6-mIgG3 following bloodstream challenge of C57BL/6J mice. This hierarchy was not observed in BALB/cJ mice: All IgG subclasses conferred similar protection. IgG subclasses differ in their ability to activate complement and interact with Fcγ receptors (FcγR) on immune cells. 3F6-mIgG2a-dependent protection was lost in FcγR-deficient, but not in complement-deficient C57BL/6J animals. Measurements of the relative ratio of FcγRIV over complement receptor 3 (CR3) on neutrophils suggest the preferential expression of FcγRIV in C57BL/6 mice and of CR3 in BALB/cJ mice. To determine the physiological significance of these differing ratios, blocking antibodies against FcγRIV or CR3 were administered to animals before challenge. Correlating with the relative abundance of each receptor, 3F6-mIgG2a-dependent protection in C57BL/6J mice showed a greater reliance for FcγRIV while protection in BALB/cJ mice was only impaired upon neutralization of CR3. Thus, 3F6-based clearance of S. aureus in mice relies on a strain-specific contribution of variable FcγR- and complement-dependent pathways. We surmise that these variabilities are the result of genetic polymorphism(s) that may be encountered in other mammals including humans and may have clinical implications in predicting the efficacy of mAb-based therapies.

Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks.

Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique for studying gene expression patterns at the single-cell level. Inferring gene regulatory networks (GRNs) from scRNA-seq data provides insight into cellular phenotypes from the genomic level. However, the high sparsity, noise and dropout events inherent in scRNA-seq data present challenges for GRN inference. In recent years, the dramatic increase in data on experimentally validated transcription factors binding to DNA has made it possible to infer GRNs by supervised methods. In this study, we address the problem of GRN inference by framing it as a graph link prediction task. In this paper, we propose a novel framework called GNNLink, which leverages known GRNs to deduce the potential regulatory interdependencies between genes. First, we preprocess the raw scRNA-seq data. Then, we introduce a graph convolutional network-based interaction graph encoder to effectively refine gene features by capturing interdependencies between nodes in the network. Finally, the inference of GRN is obtained by performing matrix completion operation on node features. The features obtained from model training can be applied to downstream tasks such as measuring similarity and inferring causality between gene pairs. To evaluate the performance of GNNLink, we compare it with six existing GRN reconstruction methods using seven scRNA-seq datasets. These datasets encompass diverse ground truth networks, including functional interaction networks, Loss of Function/Gain of Function data, non-specific ChIP-seq data and cell-type-specific ChIP-seq data. Our experimental results demonstrate that GNNLink achieves comparable or superior performance across these datasets, showcasing its robustness and accuracy. Furthermore, we observe consistent performance across datasets of varying scales. For reproducibility, we provide the data and source code of GNNLink on our GitHub repository: https://github.com/sdesignates/GNNLink.

Exogenous L-Alanine promotes phagocytosis of multidrug-resistant bacterial pathogens.

Multidrug-resistant bacteria present a major threat to public health that urgently requires new drugs or treatment approaches. Here, we conduct integrated proteomic and metabolomics analyses to screen for molecular candidates improving survival of mice infected with Vibrio parahaemolyticus, which indicate that L-Alanine metabolism and phagocytosis are strongly correlated with mouse survival. We also assess the role of L-Alanine in improving mouse survival by in vivo bacterial challenge experiments using various bacteria species, including V. parahaemolyticus, Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae. Functional studies demonstrate that exogenous L-Alanine promotes phagocytosis of these multidrug-resistant pathogen species. We reveal that the underlying mechanism involves two events boosted by L-Alanine: TLR4 expression and L-Alanine-enhanced TLR4 signaling via increased biosynthesis and secretion of fatty acids, including palmitate. Palmitate enhances binding of lipopolysaccharide to TLR4, thereby promoting TLR4 dimer formation and endocytosis for subsequent activation of the PI3K/Akt and NF-κB pathways and bacteria phagocytosis. Our data suggest that modulation of the metabolic environment is a plausible approach for combating multidrug-resistant bacteria infection.

Engineered human antibodies for the opsonization and killing of Staphylococcus aureus.

Gram-positive organisms with their thick envelope cannot be lysed by complement alone. Nonetheless, antibody-binding on the surface can recruit complement and mark these invaders for uptake and killing by phagocytes, a process known as opsonophagocytosis. The crystallizable fragment of immunoglobulins (Fcγ) is key for complement recruitment. The cell surface of S. aureus is coated with Staphylococcal protein A (SpA). SpA captures the Fcγ domain of IgG and interferes with opsonization by anti-S. aureus antibodies. In principle, the Fcγ domain of therapeutic antibodies could be engineered to avoid the inhibitory activity of SpA. However, the SpA-binding site on Fcγ overlaps with that of the neonatal Fc receptor (FcRn), an interaction that is critical for prolonging the half-life of serum IgG. This evolutionary adaptation poses a challenge for the exploration of Fcγ mutants that can both weaken SpA-IgG interactions and retain stability. Here, we use both wild-type and transgenic human FcRn mice to identify antibodies with enhanced half-life and increased opsonophagocytic killing in models of S. aureus infection and demonstrate that antibody-based immunotherapy can be improved by modifying Fcγ. Our experiments also show that by competing for FcRn-binding, staphylococci effectively reduce the half-life of antibodies during infection. These observations may have profound impact in treating cancer, autoimmune, and asthma patients colonized or infected with S. aureus and undergoing monoclonal antibody treatment.

The Type 7b Secretion System of S. aureus and Its Role in Colonization and Systemic Infection.

Staphylococcus aureus bears a type 7b secretion system (T7bSS) that assembles in the bacterial envelope to promote the secretion of WXG-like proteins and toxic effectors bearing LXG domains. Cognate immunity proteins bind cytosolic effectors to mute their toxicity prior to secretion. T7b-secreted factors have been associated with the pathogenesis of staphylococcal disease and intraspecies competition. We identified earlier strain WU1, an S. aureus ST88 isolate that caused outbreaks of skin and soft tissue infections in mouse breeding facilities. WU1 was also found to persistently colonize the nasopharynx of animals, suggesting a strong host adaptation. In this manner, WU1 colonization and infectivity in mice resembles that of methicillin-sensitive and -resistant S. aureus strains in humans, where nasal carriage is a major risk factor for invasive infections. Here, animals were colonized with wild-type or T7-deficient WU1 strains or combinations thereof. Absence of the T7bSS did not affect colonization in the nasopharynx of animals, and although fluctuations were observed in weekly samplings, the wild-type strain did not replace the T7-deficient strain in cocolonization experiments. Bloodstream infection with a T7b-deficient strain resulted in enhanced survival and reduced bacterial loads and abscesses in soft tissues compared to infection with wild-type WU1. Together, experiments using a mouse-adapted strain suggest that the T7bSS of S. aureus is an important contributor to the pathogenesis of invasive disease.

Interfacial Charge Transfer Modulated Static Friction Resistance of Water Drops.

The sliding of liquid drops over solid surfaces is a common phenomenon in nature and crucial in a variety of technological applications. Frictional dissipation along the contact line and viscous dissipation has long been regarded to dominate drop sliding. However, the ubiquitous solid-liquid interface charge transfer has received little attention. In this study, we systematically investigated the interfacial charge transfer between water drops and polarized poly(vinylidene fluoride) (ferroelectric insulator) surfaces and the effects of surface charge on static friction resistances acting on water drops. It is found that static friction resistance, reflected by the corresponding critical sliding angle, has a fourth-order function dependence on the surface potential as revealed by experiments and theoretical modeling. Interfacial charge transfer could either strengthen or weaken the surface potential up to the charge density carried by the water drops and substrates, thus resulting in the change of static friction resistance during sequential drop sliding. These findings apply to generalized problems for water at solid surfaces with charged interfaces (water, solid, or both are charged) and highlight the pivotal role of charge transfer at liquid-solid interfaces in governing drop motion.

Glycosylation-dependent opsonophagocytic activity of staphylococcal protein A antibodies.

Antibodies may bind to bacterial pathogens or their toxins to control infections, and their effector activity is mediated through the recruitment of complement component C1q or the engagement with Fcγ receptors (FcγRs). For bacterial pathogens that rely on a single toxin to cause disease, immunity correlates with toxin neutralization. Most other bacterial pathogens, including Staphylococcus aureus, secrete numerous toxins and evolved multiple mechanisms to escape opsonization and complement killing. Several vaccine candidates targeting defined surface antigens of S. aureus have failed to meet clinical endpoints. It is unclear that such failures can be solely attributed to the poor selection of antibody targets. Thus far, studies to delineate antibody-mediated uptake and killing of Gram-positive pathogens remain extremely limited. Here, we exploit 3F6-hIgG1, a human monoclonal antibody that binds and neutralizes the abundant surface-exposed Staphylococcal protein A (SpA). We find that galactosylation of 3F6-hIgG1 that favors C1q recruitment is indispensable for opsonophagocytic killing of staphylococci and for protection against bloodstream infection in animals. However, the simple removal of fucosyl residues, which results in reduced C1q binding and increased engagement with FcγR, maintains the opsonophagocytic killing and protective attributes of the antibody. We confirm these results by engineering 3F6-hIgG1 variants with biased binding toward C1q or FcγRs. While the therapeutic benefit of monoclonal antibodies against infectious disease agents may be debatable, the functional characterization of such antibodies represents a powerful tool for the development of correlates of protection that may guide future vaccine trials.

A Neural Network-Based Mesh Quality Indicator for Three-Dimensional Cylinder Modelling.

Evaluating mesh quality prior to performing the computational fluid dynamics (CFD) simulation is an essential step to ensure the acceptable accuracy of cylinder modelling. However, traditional mesh quality indicators are often insufficient since they only check geometric information on individual distorted elements. To yield more accurate results, the current evaluation process usually requires careful manual re-evaluation for quality properties such as mesh distribution and local refinement, which heavily increase the meshing overhead. In this paper, we introduce an efficient quality indicator for varisized cylinder meshes, consisting of a mesh pre-processing method and a neural network-based indicator, Mesh-Net. We also publish a cylinder mesh benchmark dataset. The proposed indicator is trained to study the role of CFD meshes on the accuracy of numerical simulations. It considers both the effect of element geometry (e.g., orthogonality) and quality properties (e.g., smoothness and distribution). Thereafter, the well-trained indicator is used as a black-box to predict the overall quality of the input mesh automatically. Experimental results demonstrate that the proposed indicator is accurate and can be applied in the mesh quality evaluation process without manual interactions.

Staphylococcus aureus Decolonization of Mice With Monoclonal Antibody Neutralizing Protein A.

Staphylococcus aureus persistently colonizes the nasopharynx of about one-third of the human population, a key risk factor for community- and hospital-acquired invasive infections. Current strategies for S. aureus decolonization include topical and systemic administration of antibiotics, which is associated with selection for antibiotic resistance and posttreatment recolonization. Using a mouse model for S. aureus colonization, we show here that systemic administration of a recombinant monoclonal antibody neutralizing staphylococcal protein A (SpA) can stimulate antibacterial immunoglobulin G and immunoglobulin A responses and promote S. aureus decolonization. These results suggest that antibody neutralizing SpA, a B-cell superantigen, may also be useful for S. aureus decolonization in humans.

Expression and interaction of small heat shock proteins (sHsps) in rice in response to heat stress.

The inherent immobility of rice (Oryza sativa L.) limited their abilities to avoid heat stress and required them to contend with heat stress through innate defense abilities in which heat shock proteins played important roles. In this study, Hsp26.7, Hsp23.2, Hsp17.9A, Hsp17.4 and Hsp16.9A were up-regulated in Nipponbare during seedling and anthesis stages in response to heat stress. Subsequently, the expressing levels of these five sHsps in the heat-tolerant rice cultivar, Co39, were all significantly higher than that in the heat-susceptible rice cultivar, Azucena. This indicated that the expressive level of these five sHsps was positively related to the ability of rice plants to avoid heat stress. Thus, the expression level of these five sHsps can be regarded as bio-markers for screening rice cultivars with different abilities to avoid heat stress. Hsp18.1, Hsp17.9A, Hsp17.7 and Hsp16.9A, in the three rice cultivars under heat stress were found to be involved in one protein complex by Native-PAGE, and the interactions of Hsp18.1 and Hsp 17.7, Hsp18.1 and Hsp 17.9A, and Hsp17.7 and Hsp16.9A were further validated by yeast 2-hybridization. Pull down assay also confirmed the interaction between Hsp17.7 and Hsp16.9A in rice under heat stress. In conclusion, the up-regulation of the 5 sHsps is a key step for rice to tolerate heat stress, after that some sHsps assembled into a large hetero-oligomeric complex. In addition, through protein-protein interaction, Hsp101 regulated thiamine biosynthesis, and Hsp82 homology affected nitrogen metabolism, while Hsp81-1 were involved in the maintenance of sugar or starch synthesis in rice plants under heat stress. These results provide new insight into the regulatory mechanism of sHsps in rice.

Genome-wide identification of heat shock proteins (Hsps) and Hsp interactors in rice: Hsp70s as a case study.

BACKGROUND: Heat shock proteins (Hsps) perform a fundamental role in protecting plants against abiotic stresses. Although researchers have made great efforts on the functional analysis of individual family members, Hsps have not been fully characterized in rice (Oryza sativa L.) and little is known about their interactors. RESULTS: In this study, we combined orthology-based approach with expression association data to screen rice Hsps for the expression patterns of which strongly correlated with that of heat responsive probe-sets. Twenty-seven Hsp candidates were identified, including 12 small Hsps, six Hsp70s, three Hsp60s, three Hsp90s, and three clpB/Hsp100s. Then, using a combination of interolog and expression profile-based methods, we inferred 430 interactors of Hsp70s in rice, and validated the interactions by co-localization and function-based methods. Subsequent analysis showed 13 interacting domains and 28 target motifs were over-represented in Hsp70s interactors. Twenty-four GO terms of biological processes and five GO terms of molecular functions were enriched in the positive interactors, whose expression levels were positively associated with Hsp70s. Hsp70s interaction network implied that Hsp70s were involved in macromolecular translocation, carbohydrate metabolism, innate immunity, photosystem II repair and regulation of kinase activities. CONCLUSIONS: Twenty-seven Hsps in rice were identified and 430 interactors of Hsp70s were inferred and validated, then the interacting network of Hsp70s was induced and the function of Hsp70s was analyzed. Furthermore, two databases named Rice Heat Shock Proteins (RiceHsps) and Rice Gene Expression Profile (RGEP), and one online tool named Protein-Protein Interaction Predictor (PPIP), were constructed and could be accessed at http://bioinformatics.fafu.edu.cn/.

Biofunctional lipid nanoparticles for precision treatment and prophylaxis of bacterial infections.

The lack of bacterial-targeting function in antibiotics and their prophylactic usage have caused overuse of antibiotics, which lead to antibiotic resistance and inevitable long-term toxicity. To overcome these issues, we develop neutrophil-bacterial hybrid cell membrane vesicle (HMV)-coated biofunctional lipid nanoparticles (LNP@HMVs), which are designed to transport antibiotics specifically to bacterial cells at the infection site for the effective treatment and prophylaxis of bacterial infection. The dual targeting ability of HMVs to inflammatory vascular endothelial cells and homologous Gram-negative bacterial cells results in targeted accumulation of LNP@HMVs in the site of infections. LNP@HMVs loaded with the antibiotic norfloxacin not only exhibit enhanced activity against planktonic bacteria and bacterial biofilms in vitro but also achieve potent therapeutic efficacy in treating both systemic infection and lung infection. Furthermore, LNP@HMVs trigger the activation of specific humoral and cellular immunity to prevent bacterial infection. Together, LNP@HMVs provide a promising strategy to effectively treat and prevent bacterial infection.

A humanized monoclonal antibody targeting protein a promotes opsonophagocytosis of Staphylococcus aureus in human umbilical cord blood.

Low and very-low-birth-weight (V/LBW) neonates are highly susceptible to bacterial sepsis and meningitis. Bacterial infections caused by Staphylococcus aureus can be particularly dangerous for neonates and can result in high mortality and long-term disabilities.Antibody-based strategies have been attempted to protect V/LBW neonates against staphylococcal disease. However, these efforts have so far been unsuccessful. Failures were attributed to the immaturity of the neonatal immune system but did not account for the anti-opsonic activity of Staphylococcal protein A (SpA). Here we show that monoclonal antibody 3F6, which blocks SpA activity, promotes complement-dependent cell-mediated phagocytosis of S. aureus in human umbilical cord blood. A substitution in the crystallizable fragment (Fc) region of 3F6 that enhances recruitment of complement component C1q further increases the phagocytic activity of cord blood. Our data demonstrate that the neonatal immune system possesses bactericidal activity that can be harnessed by antibodies that circumvent a key innate immune strategy of S. aureus.

Uracil restores susceptibility of methicillin-resistant Staphylococcus aureus to aminoglycosides through metabolic reprogramming.

Background: Methicillin-resistant Staphylococcus aureus (MRSA) has now become a major nosocomial pathogen bacteria and resistant to many antibiotics. Therefore, Development of novel approaches to combat the disease is especially important. The present study aimed to provide a novel approach involving the use of nucleotide-mediated metabolic reprogramming to tackle intractable methicillin-resistant S. aureus (MRSA) infections. Objective: This study aims to explore the bacterial effects and mechanism of uracil and gentamicin in S. aureus. Methods: Antibiotic bactericidal assays was used to determine the synergistic bactericidal effect of uracil and gentamicin. How did uracil regulate bacterial metabolism including the tricarboxylic acid (TCA) cycle by GC-MS-based metabolomics. Next, genes and activity of key enzymes in the TCA cycle, PMF, and intracellular aminoglycosides were measured. Finally, bacterial respiration, reactive oxygen species (ROS), and ATP levels were also assayed in this study. Results: In the present study, we found that uracil could synergize with aminoglycosides to kill MRSA (USA300) by 400-fold. Reprogramming metabolomics displayed uracil reprogrammed bacterial metabolism, especially enhanced the TCA cycle to elevate NADH production and proton motive force, thereby promoting the uptake of antibiotics. Furthermore, uracil increased cellular respiration and ATP production, resulting the generation of ROS. Thus, the combined activity of uracil and antibiotics induced bacterial death. Inhibition of the TCA cycle or ROS production could attenuate bactericidal efficiency. Moreover, uracil exhibited bactericidal activity in cooperation with aminoglycosides against other pathogenic bacteria. In a mouse mode of MRSA infection, the combination of gentamicin and uracil increased the survival rate of infected mice. Conclusion: Our results suggest that uracil enhances the activity of bactericidal antibiotics to kill Gram-positive bacteria by modulating bacterial metabolism.

Sparking potential over 1200 V by a falling water droplet.

Hydrovoltaic technology has achieved notable breakthroughs in electric output via using the moving boundary of electric double layer, but the output voltage induced by droplets is saturated around 350 volts, and the underlying mechanism remains to be further clarified. Here, we show that falling water droplets can stably spark an unprecedented voltage up to 1200 volts within microseconds that they contact an electrode placed on top of an electret surface, approaching the theoretical upper limit. This sparking potential can be explained and described by a comprehensive model considering the water-electrode contact dynamics from both the macroscale droplet spreading and the microscale electric double layer formation, as well as the presence of a circuit capacitance. It is demonstrated that a droplet-induced electric spark is sufficient to directly ionize gas at atmospheric pressure and split water into hydrogen and oxygen, showing wide application potential in fields of green energy and intelligence.

Current Promising Strategies against Antibiotic-Resistant Bacterial Infections.

Infections caused by antibiotic-resistant bacteria (ARB) are one of the major global health challenges of our time. In addition to developing new antibiotics to combat ARB, sensitizing ARB, or pursuing alternatives to existing antibiotics are promising options to counter antibiotic resistance. This review compiles the most promising anti-ARB strategies currently under development. These strategies include the following: (i) discovery of novel antibiotics by modification of existing antibiotics, screening of small-molecule libraries, or exploration of peculiar places; (ii) improvement in the efficacy of existing antibiotics through metabolic stimulation or by loading a novel, more efficient delivery systems; (iii) development of alternatives to conventional antibiotics such as bacteriophages and their encoded endolysins, anti-biofilm drugs, probiotics, nanomaterials, vaccines, and antibody therapies. Clinical or preclinical studies show that these treatments possess great potential against ARB. Some anti-ARB products are expected to become commercially available in the near future.

Phosphoproteins regulated by heat stress in rice leaves.

BACKGROUND: High temperature is a critical abiotic stress that reduces crop yield and quality. Rice (Oryza sativa L.) plants remodel their proteomes in response to high temperature stress. Moreover, phosphorylation is the most common form of protein post-translational modification (PTM). However, the differential expression of phosphoproteins induced by heat in rice remains unexplored. METHODS: Phosphoprotein in the leaves of rice under heat stress were displayed using two-dimensional electrophoresis (2-DE) and Pro-Q Diamond dye. Differentially expressed phosphoproteins were identified by MALDI-TOF-TOF-MS/MS and confirmed by Western blotting. RESULTS: Ten heat-phosphoproteins were identified from twelve protein spots, including ribulose bisphos-phate carboxylase large chain, 2-Cys peroxiredoxin BAS1, putative mRNA binding protein, Os01g0791600 protein, OSJNBa0076N16.12 protein, putative H(+)-transporting ATP synthase, ATP synthase subunit beta and three putative uncharacterized proteins. The identification of ATP synthase subunit beta was further validated by Western-blotting. Four phosphorylation site predictors were also used to predict the phosphorylation sites and the specific kinases for these 10 phosphoproteins. CONCLUSION: Heat stress induced the dephosphorylation of RuBisCo and the phosphorylation of ATP-ß, which decreased the activities of RuBisCo and ATP synthase. The observed dephosphorylation of the mRNA binding protein and 2-Cys peroxiredoxin may be involved in the transduction of heat-stress signaling, but the functional importance of other phosphoproteins, such as H+-ATPase, remains unknown.

An improved data-free surrogate model for solving partial differential equations using deep neural networks.

Partial differential equations (PDEs) are ubiquitous in natural science and engineering problems. Traditional discrete methods for solving PDEs are usually time-consuming and labor-intensive due to the need for tedious mesh generation and numerical iterations. Recently, deep neural networks have shown new promise in cost-effective surrogate modeling because of their universal function approximation abilities. In this paper, we borrow the idea from physics-informed neural networks (PINNs) and propose an improved data-free surrogate model, DFS-Net. Specifically, we devise an attention-based neural structure containing a weighting mechanism to alleviate the problem of unstable or inaccurate predictions by PINNs. The proposed DFS-Net takes expanded spatial and temporal coordinates as the input and directly outputs the observables (quantities of interest). It approximates the PDE solution by minimizing the weighted residuals of the governing equations and data-fit terms, where no simulation or measured data are needed. The experimental results demonstrate that DFS-Net offers a good trade-off between accuracy and efficiency. It outperforms the widely used surrogate models in terms of prediction performance on different numerical benchmarks, including the Helmholtz, Klein-Gordon, and Navier-Stokes equations.