Biology subjects

Schaefer, D.

Publications and source records attributed to Schaefer, D..

5 recordsLinked to original sources

bioRxiv2026

Engineering Functional CLA-Targeting CAR Approaches for Pancreatic Ductal Adenocarcinoma

Pancreatic cancer remains a highly lethal malignancy with limited therapeutic options. Chimeric antigen receptor (CAR) therapy has revolutionized the treatment of hematological cancers but still faces major limitations in solid tumors, particularly due to the scarcity of tumor-specific targets. Cutaneous lymphocyte antigen (CLA) recently emerged as a promising PDAC target due to its high tumor expression and limited presence in healthy tissues. However, previously reported CLA-directed CAR constructs lacked antitumor functionality. Here, we investigated multiple strategies to generate functional CLA-targeting CAR approaches. We first hypothesized that impaired activity resulted from fratricide caused by CLA expression on activated T cells. CLA knockout was successfully achieved through deletion of fucosyltransferase-7, but not by knockout of the major CLA carrier backbones CD162, CD44 or CD43, suggesting additional CLA carriers or compensatory regulation. As CLA knockout alone did not restore CAR-mediated killing, we explored whether insufficient binding affinity limited CAR activity. Affinity maturation was performed in silico and in vitro using yeast surface display, identifying 39 candidate mutations, although none restored cytotoxicity. We finally switched to an AdCAR strategy using anti-biotin CAR T cells combined with biotinylated anti-CLA scFv-Fc adapters. This approach enabled efficient, concentration-dependent cytotoxicity with both CLA-targeting binders. Additionally, we identified a dynamic, cell density-dependent regulation of CLA expression. Finally, glycan profiling of CLA binders further revealed broader-than-expected glycan interactions, suggesting a potentially wider definition of the CLA family. Overall, our findings establish CLA as a functional PDAC immunotherapy target while revealing unexpected complexity in its regulation and molecular presentation.

immunology↗

bioRxiv2026

Combinatorial adapter targeting enables AND-gate activation of AdCAR T cells in pancreatic cancer but reveals donor-dependent activation thresholds

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy with limited therapeutic options, underscoring the need for innovative treatments. Chimeric antigen receptor (CAR) therapy has transformed hematologic malignancies but faces key challenges in solid tumors, particularly on-target/off-tumor toxicity and antigen heterogeneity. Adapter CAR (AdCAR) platforms offer enhanced control by decoupling antigen recognition from CAR activation, enabling controllable, reversible, and multi-antigen targeting. Recent studies suggest AdCARs can function as an AND-gate using combinations of adapter molecules at controlled surface densities. This defines activation thresholds, termed the Surface Activation Matrix, that restricts full activation to tumor cells overexpressing the target antigen combination, thereby reducing off-tumor toxicity. In this study, we evaluated its applicability to PDAC using adapters targeting CD318, TSPAN8 and CD66c. We systematically evaluated single and combinatorial adapter dosing in co-culture assays with AsPC1 cells, in a donor-dependent manner. Low concentrations of individual adapters were non-cytotoxic, whereas combining them at identical sub-threshold doses restored potent tumor killing, demonstrating that AdCAR activation depends on cumulative adapter density rather than total amount. However, the activation threshold required for AND-gate cytotoxicity varied between donors, highlighting the need for patient-specific titration to achieve selective tumor killing. These findings validate that AdCAR T cell activity in PDAC can be finely tuned through adapter concentration and combinatorial targeting, enabling selective tumor recognition while minimizing on-target/off-tumor toxicity. This flexible, safety-oriented strategy supports targeting heterogeneous PDAC tumors, though donor-dependent variability remains a critical consideration for clinical implementation.

immunology↗

bioRxiv2020

Landscape management for grassland multifunctionality

Land-use intensification has contrasting effects on different ecosystem services, often leading to land-use conflicts. While multiple studies have demonstrated how landscape-scale strategies can minimise the trade-off between agricultural production and biodiversity conservation, little is known about which land-use strategies maximise the landscape-level supply of multiple ecosystem services (landscape multifunctionality), a common goal of stakeholder communities. We combine comprehensive data collected from 150 German grassland sites with a simulation approach to identify landscape compositions, with differing proportions of low-, medium-, and high-intensity grasslands, that minimise trade-offs between the six main grassland ecosystem services prioritised by local stakeholders: biodiversity conservation, aesthetic value, productivity, carbon storage, foraging, and regional identity. Results are made accessible through an online tool that provides information on which compositions best meet any combination of user-defined priorities (https://neyret.shinyapps.io/landscape_composition_for_multifunctionality/). Results show that an optimal landscape composition can be identified for any pattern of ecosystem service priorities. However, multifunctionality was similar and low for all landscape compositions in cases where there are strong trade-offs between services (e.g. aesthetic value and fodder production), where many services were prioritised, and where drivers other than land use played an important role. We also found that if moderate service levels are deemed acceptable, then strategies in which both high and low intensity grasslands are present can deliver landscape multifunctionality. The tool presented can aid informed decision-making by predicting the impact of future changes in landscape composition, and by allowing for the relative roles of stakeholder priorities and biophysical trade-offs to be understood by scientists and practitioners alike. HighlightsO_LIAn online tool identifies optimal landscape compositions for desired ecosystem services C_LIO_LIWhen the desired services are synergic, the optimum is their common best landscape composition C_LIO_LIWhen the desired services trade-off, a mix of grassland intensity is most multifunctional C_LIO_LISuch tools could support decision-making processes and aid conflict resolution C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/208199v5_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@3273f6org.highwire.dtl.DTLVardef@5b3a5aorg.highwire.dtl.DTLVardef@153f526org.highwire.dtl.DTLVardef@103cbea_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2019

Comparative evaluation of Aspergillus niger strains for endogenous pectin depolymerization capacity and suitability for D-galacturonic acid production

Pectinaceous agricultural residues rich in O_SCPLOWDC_SCPLOW-galacturonic acid (O_SCPLOWDC_SCPLOW-GalA), such as sugar beet pulp, are considered as promising feedstocks for waste-to-value conversions. Aspergillus niger is known for its strong pectinolytic activity. However, while specialized strains for production of citric acid or proteins are openly available, this is not the case for the production of pectinases. We therefore systematically compared the pectinolytic capabilities of six A. niger strains (ATCC 1015, ATCC 11414, NRRL 3122, CBS 513.88, NRRL 3, N402) using controlled batch cultivations in stirred-tank bioreactors. A. niger ATCC 11414 showed the highest polygalacturonase activity, specific protein secretion and a suitable morphology. Furthermore, O_SCPLOWDC_SCPLOW-GalA release from sugar beet pulp was 75% higher compared to the standard lab strain A. niger N402. Our study therefore presents a robust initial strain selection to guide future process improvement of O_SCPLOWDC_SCPLOW-GalA production from agricultural residues and identifies the most suitable base strain for further genetic optimizations.

bioengineering↗

bioRxiv2019

The results of biodiversity-ecosystem functioning experiments are realistic

A large body of research shows that biodiversity loss can reduce ecosystem functioning, thus providing support for the conservation of biological diversity1-4. Much of the evidence for this relationship is drawn from biodiversity-ecosystem functioning experiments (hereafter: biodiversity experiments), in which biodiversity loss is simulated by randomly assembling communities of varying species diversity, and ecosystem functions are measured5-9. This random assembly has led some ecologists to question the relevance of biodiversity experiments to real-world ecosystems, where community assembly may often be non-random and influenced by external drivers, such as climate or land-use intensification10-18. Despite these repeated criticisms, there has been no comprehensive, quantitative assessment of how experimental and real-world plant communities really differ, and whether these differences invalidate the experimental results. Here, we compare data from two of the largest and longest-running grassland biodiversity experiments globally (Jena Experiment, Germany; BioDIV, USA) to related real-world grassland plant communities in terms of their taxonomic, functional, and phylogenetic diversity and functional-trait composition. We found that plant communities of biodiversity experiments have greater variance in these compositional features than their real-world counterparts, covering almost all of the variation of the real-world communities (82-96%) while also containing community types that are not currently observed in the real world. We then re-analysed a subset of experimental data that included only ecologically-realistic communities, i.e. those comparable to real-world communities. For ten out of twelve biodiversity-ecosystem functioning relationships, biodiversity effects did not differ significantly between the full dataset of biodiversity experiments and the ecologically-realistic subset of experimental communities. This demonstrates that the results of biodiversity experiments are largely insensitive to the inclusion/exclusion of unrealistic communities. By bridging the gap between experimental and real-world studies, these results demonstrate the validity of inferences from biodiversity experiments, a key step in translating their results into specific recommendations for real-world biodiversity management.

ecology↗