Biology subjects

Gonzalez, S. F.

Publications and source records attributed to Gonzalez, S. F..

6 recordsLinked to original sources

bioRxiv2026

Thymic Treg-derived T follicular regulatory cells prevent catastrophic humoral autoimmunity in response to TLR7-driven inflammation

T follicular regulatory cells (TFR) are a follicle-resident subset of regulatory T cells (TREG) that limit germinal center (GC) responses and enforce humoral tolerance. Although TFR are known to focus antibody responses to foreign antigens, how GC-specific regulation is maintained during inflammation remains unclear. Here, TLR7-driven inflammation unmasked a critical, non-redundant role for TFR in preserving immune tolerance. Selective loss of TFR caused severe autoimmunity and increased mortality, driven by inflammation-induced expansion of autoreactive B and T cell clones and epitope spreading. Autoreactivity resolved upon cessation of inflammation in TFR-sucicient mice but persisted in their absence. Mechanistically, TFR limited the establishment and expansion of spontaneous GCs in response to inflammation, and responding TFR displayed transcriptional, phenotypic, and clonal features of thymic TREG. This suggests that whereas TFH upregulate FoxP3 to shut down end-stage GCs, it is thymic TREG-derived TFR that safeguard GC integrity under inflammatory stress to prevent lethal autoimmunity.

immunology↗

bioRxiv2025

Dual Role of Plasmacytoid Dendritic Cells in Humoral and CD8⁺ T Cell Memory Post COVID-19 mRNA Vaccination

The Pfizer-BioNTech coronavirus vaccine (BNT162b2), one of the first nanoparticle-based vaccines approved by the World Health Organisation (WHO), demonstrated 95% efficacy in preventing against Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, the precise mechanism of action underlying its effectiveness remains poorly understood. This study investigated the early immune responses in the draining lymph node (dLN) and its role in mediating antiviral protection following vaccination. Here, we focused on the involvement of antigen-presenting cells (APCs) in adaptive immunity. In this study, we demonstrated that the Pfizer-BioNTech coronavirus vaccine is rapidly transported to the dLN and is primarily captured by leukocytes that initiate the expression of the viral antigenic spike protein. Notably, we demonstrated that plasmacytoid dendritic cells (pDCs) are key orchestrators of the inflammatory and humoral response, as their specific depletion led to impaired antibody production and diminished neutralization capacity. Furthermore, single-cell transcriptomic analysis revealed an interaction between pDCs and CD8+ T cells that facilitates T cell activation. In vivo experiments confirmed that pDCs expressing the viral spike protein directly engage with CD8+ T cells, promoting their differentiation and expansion. Moreover, the absence of pDCs affected the formation of antigen-specific memory T cells. Overall, these findings highlight that pDCs are essential players in mediating both adaptive and humoral responses to the Pfizer-BioNTech coronavirus vaccine, providing insights into the mechanistic functioning of mRNA vaccines and establishing a novel role for pDCs as professional APCs.

immunology↗

bioRxiv2025

Serial intravital microscopy reveals temporal dynamics of autoreactive germinal centers in the spleen

The spleen plays a key role in clearing blood-borne infections and is involved in autoimmune and hematological disorders. It undergoes extensive remodeling during inflammation and immune reactions, but its localization in the peritoneal cavity has hampered studies of these dynamic changes. Here, we establish and validate a protocol for serial 2-photon microscopy of the murine spleen to capture dynamic processes in the living animal. As a proof-of-principle, we elucidate the expansion and contraction of autoreactive germinal centers (GCs) induced by epicutaneous application of the small-molecule TLR7 agonist resiquimod (R848). Leveraging a biocompatible abdominal imaging window, intravital labeling techniques, and fluorescent reporters, we follow GCs up to 180 {micro}m below the capsule for more than 2 weeks by tracking follicular dendritic cell (FDC) networks. This was accomplished without appreciable perturbation of normal physiology, paving the way for a deeper understanding of the biology of the spleen and its associated disease states. HighlightAn abdominal imaging window allowing the study of dynamic processes in the spleen of live mice over the course of several weeks.

immunology↗

bioRxiv2025

Tattoo ink induces inflammation in the draining lymph node and impairs the immune response against a COVID-19 vaccine

Despite safety concerns regarding the toxicity of tattoo ink, no studies have reported the consequences of tattooing on the immune response. In this work, we have characterized the transport and accumulation of different tattoo inks in the lymphatic system using a murine model. Upon quick lymphatic drainage, we observed that macrophages mainly capture the ink in the lymph node (LN). An initial inflammatory reaction at local and systemic levels follows ink capture. Notably, the inflammatory process is maintained over time as we observed clear signs of inflammation in the draining LN two months following tattooing. In addition, the capture of ink by macrophages was associated with the induction of apoptosis in both human and murine models. Furthermore, the ink accumulated in the LN altered the immune response against a COVID-19 vaccine. We observed a reduced antibody response following vaccination with a mRNA-based SARS-CoV-2 vaccine, which was associated with a decreased expression of the Spike protein in macrophages in the draining LN. Considering the unstoppable trend of tattooing in the population, our results are crucial in informing the toxicology programs, policymakers, and the general public regarding the potential risk of the tattooing practice associated with an altered immune response.

immunology↗

bioRxiv2022

ADeS: a deep learning based Apoptosis Detection System for live cell imaging.

Intravital microscopy has revolutionized live cell imaging by allowing the study of spatial-temporal cell dynamics in living animals. However, the complexity of the data generated by this technology has limited the development of effective computational tools to identify and quantify cell processes. Amongst them, apoptosis is a crucial form of regulated cell death involved in tissue homeostasis and host defense. Live-cell imaging enabled the study of apoptosis at the cellular level, enhancing our understanding of its spatial-temporal regulation. However, at present, no computational method can deliver robust detection of apoptosis in microscopy time-lapses. To overcome this limitation, we developed ADeS, a deep learning-based apoptosis detection system that employs the principle of activity recognition. We trained ADeS on extensive datasets containing more than 10,000 apoptotic instances collected both in vitro and in vivo, achieving a classification accuracy above 98% and outperforming state-of-the-art solutions. ADeS is the first method capable of detecting the location and duration of multiple apoptotic events in full microscopy time-lapses, surpassing human performance in the same task. We demonstrated the effectiveness and robustness of ADeS across various imaging modalities, cell types, and staining techniques. Finally, we employed ADeS to quantify cell survival in vitro and tissue damage in vivo, demonstrating its potential application in toxicity assays, treatment evaluation, and inflammatory dynamics. Our findings suggest that ADeS is a valuable tool for the accurate detection and quantification of apoptosis in live-cell imaging and, in particular, intravital microscopy data, providing insights into the complex spatial-temporal regulation of this process.

bioinformatics↗

bioRxiv2019

Semi-supervised machine learning facilitates cell colocalization and tracking in intravital microscopy

2-photon intravital microscopy (2P-IVM) is a key technique to investigate cell migration and cell-to-cell interactions in organs and tissues of living organisms. Focusing on immunology, 2P-IVM allowed recording videos of leukocytes during the immune response, highlighting unprecedented mechanisms of the immune system. However, the automatic analysis of the acquired videos remains challenging and poorly reproducible. In fact, both manual curation of results and tuning of bioimaging software parameters among different experiments, are required. One of the most difficult tasks for a user is transferring to a computer the knowledge on what a cell is and how it should appear with respect to the background, other objects, or other cell types. This is possibly due to the low specificity of acquisition channels which may include multiple cell populations and the presence of similar objects in the background. In this work, we propose a method based on semi-supervised machine learning to facilitate colocalization. In line with recently proposed approaches for pixel classification, the method requires the user to draw some lines on the cells of interest and some line on the other objects/background. These lines embed knowledge, not only on which pixel belongs to a class or which pixel belongs to another class but also on how pixels in the same object are connected. Hence, the proposed method exploits the information from the lines to create an additional imaging channel that is specific for the cells fo interest. The usage of this method increased tracking accuracy on a dataset of challenging 2P-IVM videos of leukocytes. Additionally, it allowed processing multiple samples of the same experiment keeping the same mathematical model.

systems biology↗