Emergent properties of cell surface glycosylation in cell-cell communication

Informations projet

GLYCONOISE

N° de convention de subvention: 716024

DOI

10.3030/716024

Projet clôturé

Date de signature de la CE 20 Janvier 2017

Date de début 1 Février 2017

Date de fin 30 Septembre 2023

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 1 499 813,00

Contribution de l’UE

€ 1 499 813,00

Coordonné par

UNIVERSITAT WIEN
Austria

Periodic Reporting for period 5 - GLYCONOISE (Emergent properties of cell surface glycosylation in cell-cell communication)

Période du rapport: 2022-03-01 au 2023-09-30

Résumé du contexte et des objectifs généraux du projet

Every living cell is decorated with a dense fur of glycans. Multicellular organisms make use of this matrix to encode for specific information such as cellular identity, metabolic and activation status, and circadian clock. Cell surface glycans, present on glycoproteins and glycolipids modulate protein localization, their interaction partners and receptor life cycles. Since glycans are secondary gene products and their occurrence and modulation cannot be predicted from analysis of the genome per se, their formation as well as their breakdown is determined by many factors, not limited to gene expression of potentially over 200 enzymes and transporters. Regulatory mechanisms of this fine-tuned interplay arose on many different time scales: very quick alteration of the glycocalyx can be introduced using secreted hydrolases and endo- and exocytosis of glycoproteins. Long-term remodeling of glycans can result from gene expression and histone modifications.

How can such a specially and temporally regulated, complex and stochastic system encode reliable for information that can successfully be decoded by other cells through the use of lectin receptors? Here we address the fundaments of how cell surface exposed sugars in multicellular organisms serve as information storage and how they are decoded. For this we treat this system like a communication channel in which a sender cell conveys a defined message to a receiver cell. This formalism opens the door for cross-disciplinary approaches coming from theoretical physics (i.e. information theory) to aid the analysis of the biological data. A central figure in any communication channel is noise and we will assess the different layers of noise and dissect their origin and influence. We combine insights from atomic resolution understanding the biophysics of protein glycan interaction with experimental assessment of cellular mechanisms addressing these questions: How often does a protein-carbohydrate interaction on a cell surface lead to a productive, biological response? How do lectins and glycans find each other on two-dimensional surfaces? How much information can be transferred through such a communication channel and how does this compare to glycan-independent pathways of cell-cell communication?

Taken together these insights will help us to understand why tumor cells change their cell surface glycans in a similar way. Moreover, we gain insight into fundamental processes in biology that lead to better understanding of how glycosylation became such an essential posttranslational modification present in every living organism. Furthermore, nature uses sugar for specific delivery of cargo to certain cells in the body and with our knowledge on how such system works, we can address molecular drug targeting strategies more efficiently to reduce side effects of novel therapeutics.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

Our research focused on elucidating the role of noise, redundancy, and multivalency in glycan-mediated cell communication, with the aim of understanding fundamental principles underlying biological systems where glycans serve as a primary communication language. For this we first established a glycan-based communication model system. This served as the basis to quantify how noise and redundancy of glycan-recognition receptors during innate immune response using NFkB reporter cell lines work. More specific, we quantified glycan information decoded by individual receptors or combinations thereof, demonstrating modulation of signaling capacity by co-presentation of different glycans.

Moreover, to better understand the reading process of the message encoded in cell surface glycans we advanced single-particle tracking by developing a biophysical method to investigate real-time glycan-receptor recognition dynamics using microscopy. This led to tracked glycan nanoparticles using deep learning methods, revealing insights into receptor engagement dynamics and endolysosomal sorting processes.

Furthermore, we initiated the characterization of glycome heterogeneity on a single level. The heterogeneity of glycans displayed on individual cells is unchartered ground and using machine learning algorithms and lectin probes we paved the way for future research in this direction since glycome variation contributes to cell fate determination, signaling, and communication at single-cell level.

From a methodological standpoint, out work led to several innovative findings. We applied information theory to evaluate cellular signaling at the single-cell level, providing guidelines for computation of channel capacity. Next, our approach for tracking nanoparticles within cells, enhancing tracking accuracy will help understanding the decoding mechanism using machine learning-based tracking methods. Finally, on a biological level, we identified dectin-2 as a "noisy lectin" with implications for host-pathogen interactions and immune response modulation. The advanced understanding of multivalent interactions, receptor diffusivity, and endocytosis dynamics in glycan-lectin interactions, has potential applications in targeted drug delivery and vaccine design.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

Our research has pushed beyond the current understanding of cellular communication based on the glycan encoded information. By developing a model system that mimics this communication process, we've been able to delve deeper into how cells interpret and respond to glycan signals. We were able to quantify the information encoded in these tree-like structure with an accuracy sufficient to now go the next step and perturb these systems and answer more intriguing questions in the field. At the same time, our findings have revealed unexpected interactions between receptors on cell surfaces, shedding new light on how the immune system recognizes pathogens and responds to infections.

Furthermore, our use of advanced microscopy techniques has allowed us to track nanoparticles and how they interact with cell receptors, providing unprecedented insights into the internal processing of these signals. This has led to discoveries regarding how cells internalize and process glycan signals, highlighting the importance of factors such as sugar molecule density and arrangement. However, this research has strong implications for any other delivery of nano-sized material to cells such as LNP-based mRNA vaccines, liposomes and other nanomedicines as well as more fundamental research into viral uptake and routing.

To sum up, we developed method for quantification and characterization of these multivalent low affinity interaction and how they can encode information. Such interactions are of fundamental importance in biology as they build the basis for many selective recognition processes. This will give future reseach the basis to explore the therapeutic implications of our findings, particularly in the development of novel treatments for infections and targeted drug delivery strategies. Overall, our research represents a significant step beyond the current state of the art in glycobiology and cell communication, with the potential to impact various fields, including immunology, biotechnology, and pharmaceuticals.

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