Biology subjects

Pongratz, G.

Publications and source records attributed to Pongratz, G..

3 recordsLinked to original sources

bioRxiv2020

TLR9-activated B cells improve their regulatory function by endogenously produced catecholamines

The sympathetic nervous system (SNS) contributes to immune balance by promoting anti-inflammatory B cells. However, whether B cells possess a self-regulating mechanism by which they modulate regulatory B cell (Breg) function is not well understood. In this study, we investigated the ability of B cells to synthesize catecholamines upon stimulation with different B cell activators. We found, that expression of the enzymes required to generate catecholamines, is upregulated by TLR9. TLR-9-specific expression of tyrosine hydroxylase (TH) correlated with upregulation of adrenergic receptors, enhanced IL-10 production, and with an overexpression of the co-inhibitory ligands PD-L1 and FasL. Moreover, concomitant stimulation of {beta}1-3-adrenergic receptors together with a BCR/TLR9 stimulus enhances the anti-inflammatory potential of Bregs to suppress CD4 T cells, a crucial population in the pathogenesis of autoimmune diseases, like rheumatoid arthritis. In conclusion, our data show that B cells possess autonomous mechanisms to modulate their regulatory function. These findings help to better understand the function of Bregs in autoimmune diseases and the interplay of sympathetic nervous system and B cell function.

immunology↗

bioRxiv2020

Rescue Ebola Patients in silico

Ebola, one of the most pathogenic and lethal viruses, repeatedly leads to severe outbreaks with large numbers of casualties. By integration of data of fatal, non-fatal and asymptomatic cases, we developed a mathematical model of the immune response to Ebola infections and found that TNF- can explain subsequent cytokine responses and allows to quantitatively stratify patients into survivors and fatal cases. The model further suggests that antibodies provide the key resolving mechanism in survivors while IFN-{gamma} is the key defense mechanism in fatal cases. Exogenous IFN-{gamma} and inhibition of excessive inflammation have the potential to rescue fatal Ebola infections in silico. In view of the high mortality of this disease, limited real life studies, and the unforeseeable next outbreak, our in silico analysis is meant as a guide for future research by the determination of the most efficient strategies for Ebola treatment.

systems biology↗

bioRxiv2018

Introduction and validation of a new semi-automated method to determine sympathetic fiber density in target tissues.

In recent years, the role of sympathetic nervous fibers in chronic inflammation has become increasingly evident. At the onset of inflammation, sympathetic activity is increased in the affected tissue. However, sympathetic fibers are largely absent from chronically inflamed tissue. Apparently, there is a very dynamic relationship between sympathetic innervation and the immune system in areas of inflammation, and hence a rapid and easy method for quantification of nerve fiber density of target organs is of great value to answer potential research questions. Currently, nervous fiber densities are either determined by tedious manual counting, which is not suitable for high throughput approaches, or by expensive automated processes relying on specialized software and high-end microscopy equipment. Usually, tyrosine hydroxylase (TH) is used as the marker for sympathetic fibers. In order to overcome the current quantification bottleneck with a cost-efficient alternative, an automated process was established and compared to the classic manual approach of counting TH-positive sympathetic fibers. Since TH is not exclusively expressed on sympathetic fibers, but also in a number of catecholamine-producing cells, a prerequisite for automated determination of fiber densities is to reliably distinct between cells and fibers. Therefore, an additional staining using peripherin exclusively expressed in nervous fibers as a secondary marker was established. Using this novel approach, we studied the spleens from a syndecan-3 knockout (SDC3KO) mouse line, and demonstrated equal results on SNS fiber density for both manual and automated counts (Manual counts: wt: 22.57 +/- 11.72 fibers per mm2; ko: 31.95 +/- 18.85 fibers per mm2; p = 0.0498; Automated counts: wt: 31.6 +/- 18.98 fibers per mm2; ko: 45.49 +/- 19.65 fibers per mm2; p = 0.01868). In conclusion, this new and simple method can be used as a high-throughput approach to reliably and quickly quantify SNS nerve fiber density in target tissues.

neuroscience↗