Biology subjects

Blum, A.

Publications and source records attributed to Blum, A..

8 recordsLinked to original sources

bioRxiv2026

Teatime for Triticum: (how) can the presence of plants slow down decomposition?

Decomposition of organic matter is a key process in soils contributing to carbon and nutrient cycling. To identify management strategies for agroecosystems that reduce nutrient losses while maximizing plant growth, it is important to understand which parameters determine decomposition rates. This study therefore investigated how the presence of winter wheat (Triticum aestivum var. Asory) affects decomposition in a controlled Ecotron setup with two soil types with varying organic matter content across three simulated climates (2013, 2068, 2085). Using the tea bag index, interstitial soil pore water analyses, microbial biomass quantification, bacterial and fungal gene abundance, and soil respiration measurements, we tested the hypotheses that plant exudates would enhance decomposition rate and microbial biomass, while plant nitrogen uptake would deplete soil nitrate, potentially mitigated by fertilization. Contrary to expectations, decomposition rates were lower in planted than in unplanted soils, suggesting resource competition between plants and microbes. No significant differences were observed in microbial biomass or respiration due to plant presence, and fertilization effects on nitrate or microbial mineralization were undetectable, likely due to rapid turnover of organic molecules including uptake by plants and microbes. Mechanistically, fungi and soil humidity were more important for decomposition than bacteria or temperature. The findings corroborate climate impacts on decomposition but also indicate microbial resilience and highlight the potential of management strategies like cover crops, adjusted planting dates and crop residual management which can contribute to healthy soils by sustaining carbon and nutrient cycling.

ecology↗

bioRxiv2024

Low-input soil management increases yield and decreases CO2-emissions but aggravates risk of nitrate leaching and diseases in winter wheat cropping systems under climate change

Empirical data is key to anticipate the impact of climate change on cropping systems and develop land management strategies that are sustainable while ensuring food security. Here, the combined effects of projected increases in temperature, atmospheric CO2-concentrations, solar irradiation and altered precipitation patterns on winter wheat cropping systems were investigated using an Ecotron. Experimental plant-soil systems were subjected to three different climatic conditions representing a gradient of ongoing climate change implementing the weather patterns of the years 2013, 2068, and 2085 respectively. The wheat plants were grown in two differentially manged agricultural soil types: one with long-term low organic matter (OM) inputs and the other one with long-term high OM inputs. In the low OM system, the risk for plant diseases and nitrate leaching was increased, but it outperformed the high OM system with higher yields and lower CO2-emissions. Developing high-yielding cropping systems leveraging the CO2-fertilisation effect without sacrificing environmental health will therefore require further refined of management practices to improve nutrient cycling and reduce greenhouse gas emissions. One possibility is adapting crop rotations and cover crops to the shorter wheat cycle observed in the future climates to replenish soil nutrients and break disease cycles. Further, in both here studied soil types the wheat plants developed natural coping mechanisms against environmental stressors, such as enhanced root growth and increased levels of proline and silicon. Unravelling the molecular mechanisms that trigger such inherent plant defences is a further interesting target for breeding future crops. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/626142v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@fefc32org.highwire.dtl.DTLVardef@5f6757org.highwire.dtl.DTLVardef@1799ca4org.highwire.dtl.DTLVardef@11aec5c_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2024

Whole Genome 3D Blood Biopsy Profiling of Canine Cancers: Development and Validation of EpiSwitch Multi-Choice Array-Based Diagnostic Test.

Veterinary oncology has a critical need for an accurate, specific, and sensitive non-invasive (blood) biomarker assay to assess multiple canine oncological indications early to better inform therapeutic interventions. Extended from clinical applications in human oncology, here we report on a novel 3D genomics approach to identify systemic blood biomarkers for canine diffuse large B-cell lymphoma (DLBCL), T-zone lymphoma (TZL), hemangiosarcoma (HSA), histiocytic sarcoma, osteosarcoma, and canine malignant melanoma, in a single assay format that encompasses multiple classes and phenotypes of cancer. In the validation of the independent test cohort the 3D whole-genome profiling in peripheral blood demonstrated high sensitivity and specificity for lymphomas and sarcomas as a class, with accuracy >80%; and high sensitivity and specificity for individual indications, with accuracy >89%. This study demonstrates a 3D genomic approach can be used to develop a non-invasive, blood-based test for multiple choice diagnosis of canine oncological indications. The modular EpiSwitch(R) Specific Canine Blood (EpiSwitch SCB) test promises to help veterinary specialists to diagnose the disease, make more informed treatment decisions, better utilize alternative effective treatments, minimize or avoid unnecessarily toxicity, and efficiently manage costs and resources.

molecular biology↗

bioRxiv2023

VAMP2/Munc18-1 domain 3a interaction controls the nanoscale reorganization underpinning vesicular priming

SNARE-mediated secretory vesicle (SV) exocytosis underpins neuronal communication. Munc18-1 orchestrates SNARE complex formation by controlling the opening of syntaxin-1A. How the SV-plasma membrane interface becomes fusion-competent at the nanoscale level is poorly understood. Here, we propose that the interaction of Munc18-1 with VAMP2 during vesicular docking triggers nanoscale re-organization which renders the SV-plasma membrane interface fusion-competent. We identified and mutated key residues in Munc18-1 domain 3a (A297 and T304) hypothesised to impair its interaction with VAMP2. Munc18-1A297H, and to a lesser extent Munc18-1T304H, constrained SVs on the plasma membrane and reduced stimulated secretion, under re-expression conditions in Munc18-1/2 double knockout neurosecretory cells. Moreover, the de-clustering of Munc18-1 in response to activity was lost for both mutants. The interaction of VAMP2 with the Munc18-1 domain 3a therefore controls the re-organization of the nanoscale environment of the docked SV-plasma membrane interface, fostering syntaxin-1A opening and Munc18-1 release to ensure that SNARE assembly only occurs within the confinement of docked vesicles.

neuroscience↗

bioRxiv2023

Identification of tumor-specific MHC ligands through improved biochemical isolation and incorporation of machine learning

Isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for TCR-T immunotherapies. However, as many targets of high tumor-specificity are only presented at low abundance on the cell surface of tumor cells, the efficient isolation of these peptides is crucial for their successful detection. Here, we demonstrate how different isolation strategies, which consider hydrophobicity and post-translational modifications, can improve the detection of MHC ligands, including cysteinylated MHC ligands from cancer germline antigens or point-mutated neoepitopes. Furthermore, we developed a novel MHC class I ligand prediction algorithm (ARDisplay-I) that outperforms the current state-of-the-art and facilitates the assignment of peptides to the correct MHC allele. The model has other applications, such as the identification of additional MHC ligands not detected from mass spectrometry or determining whether the MHC ligands can be presented on the cell surface via MHC alleles not included in the study. The implementation of these strategies can augment the development of T cell receptor-based therapies (i.a. TIL1-derived T cells, genetically engineered T cells expressing tumor recognizing receptors or TCR-mimic antibodies) by facilitating the identification of novel immunotherapy targets and by enriching the resources available in the field of computational immunology. SignificanceThis study demonstrates how the isolation of different tumor-specific MHC ligands can be optimized when considering their hydrophobicity and post-translational modification status. Additionally, we developed a novel machine-learning model for the probability prediction of the MHC ligands presentation on the cell surface. The algorithm can assign these MHC ligands to their respective MHC alleles which is essential for the design of TCR-T immunotherapies.

immunology↗

bioRxiv2023

ARDitox: platform for the prediction of TCRs potential off-target binding

Cellular immunotherapies, such as those utilizing T lymphocytes expressing native or engineered T cell receptors (TCRs), have already demonstrated therapeutic efficacy. However, some high-affinity TCRs have also proved to be fatal due to off-target immunotoxicity. This process occurs when the immune system acts against epitopes found on both tumor cells and healthy tissues. Moreover, some TCRs can be cross-reactive to epitopes with highly dissimilar sequences. To address this issue, we developed ARDitox, a novel in silico method based on computational immunology and artificial intelligence (AI) for predicting and analyzing potential off-target binding. We tested the performance of ARDitox in silico on different cases found in the literature where TCRs were used to target cancer-related antigens, as well as on a set of TCRs targeting a viral epitope. ARDitox was able to identify previously reported cross-reactive epitopes in line with the data available in the literature. In addition, we investigated a TCR targeting an HLA-A*02:01-restricted immunodominant epitope from the glioblastoma-associated antigen NLGN4X, identifying a cross-reactive ADH1A epitope that would not be detected in murine models. In conclusion, our in silico approach is a powerful tool that identifies potential off-target epitopes, complementing preclinical studies in developing safer cell therapies targeting tumor(- associated) antigens.

immunology↗

bioRxiv2022

Synaptotagmin 1 mediates toxicity of botulinum neurotoxin type A

The extreme neurotoxicity of botulinum neurotoxins (BoNTs), broadly used as a therapeutics, is mediated by their direct binding to two plasma membrane receptors: polysialogangliosides (PSGs) and serotype-dependently either synaptotagmin 1/2 (Syt1/2) or synaptic vesicle glycoprotein 2 (SV2). Here, we demonstrate that although BoNT/A serotype binds directly to PSG and SV2, its neurotoxicity depends on Syt1. Using single-molecule superresolution microscopy of pathological concentrations of BoNT/A holotoxins, we demonstrate that the toxin binds to a preassembled PSG-Syt1 complex that forms nanoclusters with SV2 on the plasma membrane of hippocampal neurons. This coincidental interaction controls the selective endocytic targeting of BoNT/A into synaptic vesicles, leading to incapacitation of neuronal communication. Our results suggest that Syt1-SV2 plasma membrane nanoclusters may acts as a common target for various BoNT serotypes. One-Sentence SummaryBoNT/A hijacks an intrinsic tripartite PSG-Syt1-SV2 endocytic sorting mechanism to incapacitate neuronal communication

neuroscience↗

bioRxiv2020

A dominant-negative SOX18 mutant disrupts multiple regulatory layers essential to transcription factor activity.

Few genetically dominant mutations involved in human disease have been fully explained at the molecular level. In cases where the mutant gene encodes a transcription factor, the dominant-negative mode of action of the mutant protein is particularly poorly understood. Here, we studied the genome-wide mechanism underlying a dominant-negative form of the SOX18 transcription factor (SOX18RaOp) responsible for both the classical mouse mutant Ragged opossum and the human genetic disorder Hypotrichosis-Lymphedema-Telangiectasia-Renal Syndrome. Combing three single-molecule imaging assays in living cells, we found that SOX18RaOp disrupts the system through an accumulation of molecular interferences which impair several functional properties of the wild-type SOX18 protein, including its chromatin-binding dynamics. The dominant-negative effect is further amplified by recruiting the interactome of its wild-type counterpart, which perturbs regulatory nodes such as SOX7 and MEF2C. Our findings explain in unprecedented detail the multi-layered process that underpins the molecular etiology of dominant-negative transcription factor function.

cell biology↗