TY  - JOUR
A1  - Eder, Sascha
A1  - Hollmann, Claudia
A1  - Mandasari, Putri
A1  - Wittmann, Pia
A1  - Schumacher, Fabian
A1  - Kleuser, Burkhard
A1  - Fink, Julian
A1  - Seibel, Jürgen
A1  - Schneider-Schaulies, Jürgen
A1  - Stigloher, Christian
A1  - Beyersdorf, Niklas
A1  - Dembski, Sofia
T1  - Synthesis and characterization of ceramide-containing liposomes as membrane models for different T cell subpopulations
JF  - Journal of Functional Biomaterials
N2  - A fine balance of regulatory (T\(_{reg}\)) and conventional CD4\(^+\) T cells (T\(_{conv}\)) is required to prevent harmful immune responses, while at the same time ensuring the development of protective immunity against pathogens. As for many cellular processes, sphingolipid metabolism also crucially modulates the T\(_{reg}\)/T\(_{conv}\) balance. However, our understanding of how sphingolipid metabolism is involved in T cell biology is still evolving and a better characterization of the tools at hand is required to advance the field. Therefore, we established a reductionist liposomal membrane model system to imitate the plasma membrane of mouse T\(_{reg}\) and T\(_{conv}\) with regards to their ceramide content. We found that the capacity of membranes to incorporate externally added azide-functionalized ceramide positively correlated with the ceramide content of the liposomes. Moreover, we studied the impact of the different liposomal preparations on primary mouse splenocytes in vitro. The addition of liposomes to resting, but not activated, splenocytes maintained viability with liposomes containing high amounts of C\(_{16}\)-ceramide being most efficient. Our data thus suggest that differences in ceramide post-incorporation into T\(_{reg}\) and T\(_{conv}\) reflect differences in the ceramide content of cellular membranes.
KW  - liposome
KW  - ceramide
KW  - cell membrane model
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-286130
SN  - 2079-4983
VL  - 13
IS  - 3
ER  - 
TY  - JOUR
A1  - Haack, Stephanie
A1  - Baiker, Sarah
A1  - Schlegel, Jan
A1  - Sauer, Markus
A1  - Sparwasser, Tim
A1  - Langenhorst, Daniela
A1  - Beyersdorf, Niklas
T1  - Superagonistic CD28 stimulation induces IFN‐γ release from mouse T helper 1 cells in vitro and in vivo
JF  - European Journal of Immunology
N2  - Like human Th1 cells, mouse Th1 cells also secrete IFN‐γ upon stimulation with a superagonistic anti‐CD28 monoclonal antibody (CD28‐SA). Crosslinking of the CD28‐SA via FcR and CD40‐CD40L interactions greatly increased IFN‐γ release. Our data stress the utility of the mouse as a model organism for immune responses in humans.
KW  - CD28
KW  - Th1 cells
KW  - cytokine release
KW  - interferon γ
KW  - Superagonistic antibody
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-239028
VL  - 51
IS  - 3
SP  - 738
EP  - 741
ER  - 
TY  - JOUR
A1  - Breitenbach, Tim
A1  - Liang, Chunguang
A1  - Beyersdorf, Niklas
A1  - Dandekar, Thomas
T1  - Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks
JF  - PLoS Computational Biology
N2  - Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network’s nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the network’s nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220385
VL  - 15
ER  -