Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

Glycoconjugates are major constituents of mammalian cells that are formed via covalent conjugation of carbohydrates to other biomolecules like proteins and lipids and often expressed on the cell surfaces. Among the three major classes of glycoconjugates, proteoglycans and glycoproteins contain glycans linked to the protein backbone via amino acid residues such as Asn for N-linked glycans and Ser/Thr for O-linked glycans. In glycolipids, glycans are linked to a lipid component such as glycerol, polyisoprenyl pyrophosphate, fatty acid ester, or sphingolipid. Recently, glycoconjugates have become better structurally defined and biosynthetically understood, especially those associated with human diseases, and are accessible to new drug, diagnostic, and therapeutic developments. This review describes the status and new advances in the biological study and therapeutic applications of natural and synthetic glycoconjugates, including proteoglycans, glycoproteins, and glycolipids. The scope, limitations, and novel methodologies in the synthesis and clinical development of glycoconjugates including vaccines, glyco-remodeled antibodies, glycan-based adjuvants, glycan-specific receptor-mediated drug delivery platforms, etc., and their future prospectus are discussed.

Fluorinated carbohydrates have found many applications in the glycosciences. Typically, these contain fluorination at a single position. There are not many applications involving polyfluorinated carbohydrates, here defined as monosaccharides in which more than one carbon has at least one fluorine substituent directly attached to it, with the notable exception of their use as mechanism-based inhibitors. The increasing attention to carbohydrate physical properties, especially around lipophilicity, has resulted in a surge of interest for this class of compounds. This review covers the considerable body of work toward the synthesis of polyfluorinated hexoses, pentoses, ketosugars, and aminosugars including sialic acids and nucleosides. An overview of the current state of the art of their glycosidation is also provided.

Viruses are a heterogeneous ensemble of entities, all sharing the need for a suitable host to replicate. They are extremely diverse, varying in morphology, size, nature, and complexity of their genomic content. Typically, viruses use host-encoded glycosyltransferases and glycosidases to add and remove sugar residues from their glycoproteins. Thus, the structure of the glycans on the viral proteins have, to date, typically been considered to mimick those of the host. However, the more recently discovered large and giant viruses differ from this paradigm. At least some of these viruses code for an (almost) autonomous glycosylation pathway. These viral genes include those that encode the production of activated sugars, glycosyltransferases, and other enzymes able to manipulate sugars at various levels. This review focuses on large and giant viruses that produce carbohydrate-processing enzymes. A brief description of those harboring these features at the genomic level will be discussed, followed by the achievements reached with regard to the elucidation of the glycan structures, the activity of the proteins able to manipulate sugars, and the organic synthesis of some of these virus-encoded glycans. During this progression, we will also comment on many of the challenging questions on this subject that remain to be addressed.

Antimicrobial resistance (AMR) is emerging as the next potential pandemic. Different microorganisms, including the bacteria Acinetobacter baumannii, Clostridioides difficile, Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae, Neisseria gonorrhoeae, Pseudomonas aeruginosa, non-typhoidal Salmonella, and Staphylococcus aureus, and the fungus Candida auris, have been identified by the WHO and CDC as urgent or serious AMR threats. Others, such as group A and B Streptococci, are classified as concerning threats. Glycoconjugate vaccines have been demonstrated to be an efficacious and cost-effective measure to combat infections against Haemophilus influenzae, Neisseria meningitis, Streptococcus pneumoniae, and, more recently, Salmonella typhi. Recent times have seen enormous progress in methodologies for the assembly of complex glycans and glycoconjugates, with developments in synthetic, chemoenzymatic, and glycoengineering methodologies. This review analyzes the advancement of glycoconjugate vaccines based on synthetic carbohydrates to improve existing vaccines and identify novel candidates to combat AMR. Through this literature survey we built an overview of structure-immunogenicity relationships from available data and identify gaps and areas for further research to better exploit the peculiar role of carbohydrates as vaccine targets and create the next generation of synthetic carbohydrate-based vaccines.

Recent years have witnessed promising artificial intelligence (AI) applications in many disciplines, including optics, engineering, medicine, economics, and education. In particular, the synergy of AI and meta-optics has greatly benefited both fields. Meta-optics are advanced flat optics with novel functions and light-manipulation abilities. The optical properties can be engineered with a unique design to meet various optical demands. This review offers comprehensive coverage of meta-optics and artificial intelligence in synergy. After providing an overview of AI and meta-optics, we categorize and discuss the recent developments integrated by these two topics, namely AI for meta-optics and meta-optics for AI. The former describes how to apply AI to the research of meta-optics for design, simulation, optical information analysis, and application. The latter reports the development of the optical Al system and computation via meta-optics. This review will also provide an in-depth discussion of the challenges of this interdisciplinary field and indicate future directions. We expect that this review will inspire researchers in these fields and benefit the next generation of intelligent optical device design.

Nanostructured surfaces with designed optical functionalities, such as metasurfaces, allow efficient harvesting of light at the nanoscale, enhancing light-matter interactions for a wide variety of material combinations. Exploiting light-driven matter excitations in these artificial materials opens up a new dimension in the conversion and management of energy at the nanoscale. In this review, we outline the impact, opportunities, applications, and challenges of optical metasurfaces in converting the energy of incoming photons into frequency-shifted photons, phonons, and energetic charge carriers. A myriad of opportunities await for the utilization of the converted energy. Here we cover the most pertinent aspects from a fundamental nanoscopic viewpoint all the way to applications.

Molecular plasmonics, the area which deals with the interactions between surface plasmons and molecules, has received enormous interest in fundamental research and found numerous technological applications. Plasmonic metamaterials, which offer rich opportunities to control the light intensity, field polarization, and local density of electromagnetic states on subwavelength scales, provide a versatile platform to enhance and tune light-molecule interactions. A variety of applications, including spontaneous emission enhancement, optical modulation, optical sensing, and photoactuated nanochemistry, have been reported by exploiting molecular interactions with plasmonic metamaterials. In this paper, we provide a comprehensive overview of the developments of molecular plasmonics with metamaterials. After a brief introduction to the optical properties of plasmonic metamaterials and relevant fabrication approaches, we discuss light-molecule interactions in plasmonic metamaterials in both weak and strong coupling regimes. We then highlight the exploitation of molecules in metamaterials for applications ranging from emission control and optical modulation to optical sensing. The role of hot carriers generated in metamaterials for nanochemistry is also discussed. Perspectives on the future development of molecular plasmonics with metamaterials conclude the review. The use of molecules in combination with designer metamaterials provides a rich playground both to actively control metamaterials using molecular interactions and, in turn, to use metamaterials to control molecular processes.