YesU from Bacillus subtilis preferentially binds fucosylated glycans

The role of the glycome in symbiotic host-microbe interactions

Glycosylation plays a crucial role in many aspects of cell biology, including cellular and organismal integrity, structure-and-function of many glycosylated molecules in the cell, signal transduction, development, cancer, and in a number of diseases. Besides, at the inter-organismal level of interaction, a variety of glycosylated molecules are involved in the host-microbiota recognition and initiation of downstream signalling cascades depending on the outcomes of the glycome-mediated ascertainment. The role of glycosylation in host-microbe interactions is better elaborated within the context of virulence and pathogenicity in bacterial infection processes but the symbiotic host-microbe relationships also involve substantive glycome-mediated interactions. The works in the latter field have been reviewed to a much lesser extent, and the main aim of this mini-review is to compensate for this deficiency and summarise the role of glycomics in host-microbe symbiotic interactions.

RhgKL and CcpA directly regulate the rhiLFGN-rhgR-yesTUV operon involved in the metabolism of rhamnogalacturonan type I in Bacillus subtilis

The Bacillus subtilis rhiLFGN-rhgR-yesTUVWXYZ (formerly yesOPQRSTUVWXYZ) gene cluster includes genes for metabolizing rhamnogalacturonan type I (RG-I), a major pectin constituent, and the rhgR gene encoding an AraC/XylS transcriptional activator. The yesL-rhgKL (formerly yesLMN) operon, adjacent to the rhiL gene, includes the rhgKL genes encoding a two-component regulatory system. The reporter analyses showed that three promoters immediately upstream of the rhiL, yesW, and yesL genes were induced by RG-I and repressed by glucose in the medium. The reporter analyses also showed that RhgL and RhgR contribute to the RG-I-dependent induction of the rhiL promoter and that CcpA mediates the catabolite repression of the rhiL and yesL promoters. The in vitro experiments demonstrated that the RhgL response regulator and the CcpA complex bind to each site in the rhiL promoter region. The RT-PCR analysis and the different properties of the rhiL and yesW promoters suggested the rhiLFGN-rhgR-yesTUV genes as an operon.

Glycan-mediated molecular interactions in bacterial pathogenesis

Glycans are expressed on the surface of nearly all host and bacterial cells. Not surprisingly, glycan-mediated molecular interactions play a vital role in bacterial pathogenesis and host responses against pathogens. Glycan-mediated host-pathogen interactions can benefit the pathogen, host, or both. Here, we discuss (i) bacterial glycans that play a critical role in bacterial colonization and/or immune evasion, (ii) host glycans that are utilized by bacteria for pathogenesis, and (iii) bacterial and host glycans involved in immune responses against pathogens. We further discuss (iv) opportunities and challenges for transforming these research findings into more effective antibacterial strategies, and (v) technological advances in glycoscience that have helped to accelerate progress in research. These studies collectively offer valuable insights into new perspectives on antibacterial strategies that may effectively tackle the drug-resistant pathogens that are rapidly spreading globally.

LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction

Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins are abound in nature. Widely used as staining and characterization reagents in cell biology and crucial for understanding the interactions in biological systems, lectins are a focal point of study in glycobiology. Yet the sheer breadth and depth of specificity for diverse oligosaccharide motifs has made studying lectins a largely piecemeal approach, with few options to generalize. Here, LectinOracle, a model combining transformer-based representations for proteins and graph convolutional neural networks for glycans to predict their interaction, is presented. Using a curated data set of 564,647 unique protein-glycan interactions, it is shown that LectinOracle predictions agree with literature-annotated specificities for a wide range of lectins. Using a range of specialized glycan arrays, it is shown that LectinOracle predictions generalize to new glycans and lectins, with qualitative and quantitative agreement with experimental data. It is further demonstrated that LectinOracle can be used to improve lectin classification, accelerate lectin directed evolution, predict epidemiological outcomes in the context of influenza virus, and analyze whole lectomes in host-microbe interactions. It is envisioned that the herein presented platform will advance both the study of lectins and their role in (glyco)biology.

Functional Microarray Platform with Self-Assembled Monolayers on 3C-Silicon Carbide

Currently available bioplatforms such as microarrays and surface plasmon resonators are unable to combine high-throughput multiplexing with label-free detection. As such, emerging microelectromechanical systems (MEMS) and microplasmonics platforms offer the potential for high-resolution, high-throughput label-free sensing of biological and chemical analytes. Therefore, the search for materials capable of combining multiplexing and label-free quantitation is of great significance. Recently, interest in silicon carbide (SiC) as a suitable material in numerous biomedical applications has increased due to its well-explored chemical inertness, mechanical strength, bio- and hemocompatibility, and the presence of carbon that enables the transfer-free growth of graphene. SiC is also multifunctional as both a wide-band-gap semiconductor and an efficient low-loss plasmonics material and thus is ideal for augmenting current biotransducers in biosensors. Additionally, the cubic variant, 3C-SiC, is an extremely promising material for MEMS, being a suitable platform for the easy micromachining of microcantilevers, and as such capable of realizing the potential of real time miniaturized multiplexed assays. The generation of an appropriately functionalized and versatile organic monolayer suitable for the immobilization of biomolecules is therefore critical to explore label-free, multiplexed quantitation of biological interactions on SiC. Herein, we address the use of various silane self-assembled monolayers (SAMs) for the covalent functionalization of monocrystalline 3C-SiC films as a novel platform for the generation of functionalized microarray surfaces using high-throughput glycan arrays as the model system. We also demonstrate the ability to robotically print high throughput arrays on free-standing SiC microstructures. The implementation of a SiC-based label-free glycan array will provide a proof of principle that could be extended to the immobilization of other biomolecules in a similar SiC-based array format, thus making potentially significant advances to the way biological interactions are studied.