Project

Discipline

Influenza vaccine; Lymph node macrophages; Immune complex; IgG-mediated immune suppression; Epitope masking; Antigen transport; Intravital two-photon microscopy

Lead
Il presente progetto ha lo scopo di chiarificare i meccanismi con cui agiscono gli anticorpi, che sono fra le più importanti molecole del sistema immunitario.
Lay summary
Sebbene il legame di un anticorpo con il suo specifico bersaglio spesso aumenta la risposta immunitaria contro l’antigene, la presenza di risposte inibitorie è anch’essa un fenomeno comune. Tale processo, definito immunosoppressione anticorpo-mediata (antibody-mediated immune suppression o AMIS), è stato sfruttato con successo in alcune applicazioni cliniche, come la somministrazione di anticorpi specifici contro RhD in gestanti negative, che impedisce loro di diventare immunizzate contro gli eritrociti RhD positivi del feto. Tuttavia, il meccanismo immunologico che porta all’inibizione rimane incompreso. In questo progetto applicheremo la più moderna tecnologia di imaging in vivo per studiare il ruolo che svolgono in tale processo le principali cellule fagocitiche del linfonodo. Ci attendiamo di comprendere il meccanismo molecolare che spinge un anticorpo ad agire come stimolatore piuttosto che come soppressore della risposta immunitaria. Comprendere come l’inibizione della risposta immunitaria funzioni renderà possibile lo sviluppo di migliori e più efficaci strategie vaccinali e, al contempo, faciliterà la comprensione e lo sviluppo di nuove terapie contro le malattie autoimmuni causate da auto-anticorpi.

Direct link to Lay Summary

Last update: 12.10.2017

A trainable clustering algorithm based on shortest paths from density peaks

Author	Pizzagalli, Diego Ulisse; Gonzalez, Santiago Fernandez; Krause, Rolf
Publication date	30.10.2019
Persistent Identifier (PID)	10.1126/sciadv.aax3770
Repository	Sciences advances - supplementary materials
Abstract

Clustering is a technique to analyze empirical data, with a major application for biomedical research. Essentially, clustering finds groups of related points in a dataset. However, results depend on both metrics for point-to-point similarity and rules for point-to-group association. Non-appropriate metrics and rules can lead to artifacts, especially in case of multiple groups with heterogeneous structure. In this work, we propose a clustering algorithm that evaluates the properties of paths between points (rather than point-to-point similarity) and solves a global optimization problem, finding solutions not obtainable by methods relying on local choices. Moreover, our algorithm is trainable. Hence, it can be adapted and adopted for specific datasets and applications by providing examples of valid and invalid paths to train a path classifier. We demonstrate its applicability to identify heterogeneous groups in challenging synthetic datasets, segment highly nonconvex immune cells in confocal microscopy images, and classify arrhythmic heartbeats in electrocardiographic signals.

Active participation

Number	Title	Start	Funding scheme

Although the binding of an antigen to a specific immunoglobulin often enhances the antibody response against this antigen, the presence of inhibitory responses is also a common phenomenon. Amongst the latter, the best characterized is the IgG-mediated humoral suppression against large particulate antigens. This process, referred to as antibody-mediated immune suppression (AMIS), has been successfully utilized in clinical applications, such as the administration of specific IgGs to RhD negative mother, which prevents them from becoming immunized against RhD+ fetal erythrocytes. However, the immunological mechanism behind the IgG-mediated immune suppression remains poorly understood. We have developed a passive immunisation protocol that involves the administration of anti-influenza IgG antibodies prior to vaccination, namely H36-7 and FI6, which bind to two different epitopes of the viral HA molecule. Interestingly, these antibodies result in different degrees of suppression of the primary antibody responses to the UV-inactivated influenza vaccine, which was found to be complete in the case of H36-7, but only partial with FI6. Remarkably, the inhibition of the humoral response coincided with a reduction in the initial inflammatory reaction measured in the draining lymph node (LN) at 12 h p.v. and a lower activation of the LN-resident dendritic cells (LNDC).On the basis of our preliminary findings, we propose to study the role that the major phagocytic populations in the LN (LN resident macrophages and LNDC) have on the AMIS, using state-of-the-art in vivo imaging technology, molecular and cellular techniques and the generation of new transgenic mouse models. In addition, we wish to investigate the specific role of the Fc?R and the complement system in immune suppression, and the mechanism through which the AMIS reaction affects the humoural responses to viral epitopes that are not recognized by the administered IgG. We will also characterize the role of RIG-I in the initiation of the type I IFN response following vaccination, and how the formation of immune complexes affects the activation of this pathway.Antibody-mediated immune suppression may represent a powerful tool to modulate adverse immune responses in conditions in which self-antibody-mediated autoimmune diseases present serious health implications. Understanding the mechanism of AMIS may contribute to the discovery of new therapies for such immunological conditions. In addition, understanding the immune response to different type of antigens, can, in turn, inform better vaccine design strategies to develop long-term protective humoral immunity to influenza virus.