Biology subjects

Wagner, P.

Publications and source records attributed to Wagner, P..

7 recordsLinked to original sources

bioRxiv2026

Biochemical Characterization of Fatty Acid Thioesterase Target Site Mutants and their Implication on Herbicide Resistance

Herbicide resistance threatens effective weed control in modern agriculture, particularly in grass weeds such as Alopecurus myosuroides and Lolium multiflorum. Cinmethylin is a pre-emergence herbicide with a novel mode of action that inhibits plastidial fatty acid thioesterases (FATs), enzymes essential for fatty acid biosynthesis. Although no cases of field resistance to cinmethylin have been reported, its resistance risk has not been fully assessed. In this study, we biochemically characterized defined amino acid substitutions in FAT A and FAT B to evaluate their effects on cinmethylin inhibition profile. Some substitutions in FAT A reduced inhibition in vitro, with mutations at residue R171 causing the largest shifts in sensitivity. However, these highly resistant variants required multiple specific nucleotide polymorphisms and are therefore predicted to be unlikely to arise in weed populations. In FAT B, sensitivity shifts were generally moderate. Importantly, most substitutions that reduced cinmethylin sensitivity also impaired enzymatic activity, suggesting limited viability in planta. Overall, these results indicate that while theoretical target-site resistance mechanisms exist, the practical risk of rapid resistance evolution to cinmethylin is low, supporting its value for integrated grass weed management

biochemistry↗

bioRxiv2026

Saturating hepatic clearance drives elevated cfDNA and fragment shortening in cancer

Liquid biopsy studies consistently report both elevated circulating cell-free DNA (cfDNA) concentrations and shortened fragment lengths in cancer. These features are often attributed to tumor-specific processes, despite tumor-derived cfDNA frequently constituting less than 1% of the total. Here, we consider an alternative explanation: Saturation of cfDNA clearance, which prolongs cfDNA circulation time, increases exposure to plasma nucleases and is expected to produce similar fragmentomic signatures independent of tumor burden. By combining a mechanistic model of cfDNA fragmentation with analyses of two independent cancer patient cohorts, and publicly available clearance-perturbation experiments, we demonstrate that elevated cfDNA levels are accompanied by a characteristic leftward shift in fragment length distributions consistent with impaired hepatic clearance. This fragmentation signature becomes more pronounced at higher cfDNA concentrations, is independent of circulating tumor DNA (ctDNA) fraction, is reproducible under experimentally reduced clearance, and is independently prognostic of patient survival. Together, these results identify saturating clearance as a central determinant of cfDNA abundance and fragment length, re-framing cancer-associated fragmentomic patterns as systemic consequences of clearance dynamics rather than tumor burden alone. More broadly, they highlight the value of mechanistic modeling of clearance processes in extracting clinically meaningful signals from cfDNA fragmentation data.

cancer biology↗

bioRxiv2025

Pathological α-Synuclein Perturbs Nuclear Integrity

Pathological aggregates of -synuclein are a hallmark of a group of neurodegenerative disorders collectively termed synucleinopathies. The physiological function of -synuclein, and the detrimental effects of the pathological variants of -synuclein have been widely debated, but recent evidence has suggested an emerging consensus on a critical role for -synuclein in regulating synaptic function. However, a controversial role for -synuclein in nuclear function in both normal and pathogenic states has been proposed, and the degree to which -synuclein localizes within the nucleus and subsequent impact on the nucleus are poorly understood. To begin to address this controversy, we employed synucleinopathy murine and cell culture models, as well as postmortem human Lewy Body Dementia tissue to elucidate the extent to which pathological -synuclein localizes within the nuclear compartments, and the downstream consequences of this localization. We observed pathological aggregation of -synuclein within the nucleus in both murine models and human postmortem Lewy Body Dementia cortex via quantitative super resolution microscopy. In both mouse and human brain tissue the presence of -synuclein in the nucleus correlated with abnormal morphology of nuclei. This pathological accumulation of -synuclein in the nucleus was not observed in control mice, human tissue without pathology, or control cells. We subsequently examined the mechanistic consequences of pathological accumulation of -synuclein in the nucleus. Synucleinopathy models displayed increased levels of the DNA damage marker 53BP1. Furthermore, cells with pathological -synuclein exhibited elevated markers of nuclear envelope damage and abnormal expression of nuclear envelope repair markers. Our cell culture data also suggests altered RNA localization in response to pathological -synuclein accumulation within the nucleus. Lastly, we show that nuclear Lewy-like pathology leads to increased sensitivity to nuclear targeted toxins. Taken together, these results rigorously illustrate nuclear localization of pathological -synuclein with super resolution methodology and provide novel insight into the ensuing impact on nuclear integrity and function.

neuroscience↗

bioRxiv2024

Gαolf Regulates Biochemical Signaling in Neurons Associated with Movement Control and Initiation

The heterotrimeric G-protein subunit, Golf, acts to transduce extracellular signals through G-protein coupled receptors (GPCRs) and stimulates adenylyl cyclase mediated production of the second messenger cyclic adenosine monophosphate. Numerous mutations in the GNAL gene, which encodes Golf, have been identified as causative for an adult-onset dystonia. These mutations disrupt GPCR signaling cascades in in vitro assays through several mechanisms, and this disrupted signaling is hypothesized to lead to dystonic motor symptoms in patients. However, the cells and circuits that mutations in GNAL corrupt are not well understood. Published patterns of Golf expression outside the context of the striatum are sparse, conflicting, often lack cell type specificity, and may be confounded by expression of the close GNAL homolog of GNAS. Here, we use RNAScope in-situ hybridization to quantitatively characterize Gnal mRNA expression in brain tissue from wildtype C57BL/6J adult mice. We observed widespread expression of Gnal puncta throughout the brain, suggesting Golf is expressed in more brain structures and neuron types than previously accounted for. We quantify transcripts at a single cell level, and use neuron type specific markers to further classify and understand patterns of GNAL expression. Our data suggests that brain regions classically associated with motor control, initiation, and regulation show the highest expression of GNAL, with Purkinje Cells of the cerebellum showing the highest expression of any neuron type examined. Subsequent conditional Gnal knockout in Purkinje cells led to markedly decreased intracellular cAMP levels and downstream cAMP-dependent enzyme activation. Our work provides a detailed characterization of Gnal expression throughout the brain and the biochemical consequences of loss of Golf signaling in vivo in neurons that highly express Gnal.

neuroscience↗

bioRxiv2023

Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition

Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform on cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones end up over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases, but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.

cancer biology↗

bioRxiv2022

Cancer prevalence is remarkably low in turtles and is correlated with life history traits in birds, mammals, and squamates

Identifying species with unusually low cancer prevalence can provide new insights into cancer resistance. Most studies have focused on mammals, but the genetic, physiological, and ecological diversity among vertebrates can influence cancer susceptibility. We used necropsies from over a thousand species of amphibians, birds, crocodilians, mammals, squamates, and turtles to investigate relationships between cancer prevalence, intrinsic cancer risk, body mass, and lifespan. Previous studies often relied on species averages, leading to inaccurate interpretations. Our innovative statistical approach uses raw cancer data and resampling to improve accuracy. We found remarkably low cancer prevalence in turtles, high prevalence in squamates and mammals, and lower-than-expected prevalence based on lifespan and body mass in multiple groups. Our results show lifespan influences neoplasia and malignancy transformation rates in mammals, while body mass affects neoplasia prevalence in amphibians and squamates. These data reveal a complex relationship between life history traits and cancer risk, identifying vertebrates with potential novel cancer resistance mechanisms. STATEMENT OF SIGNIFICANCEBiodiversity is an untapped natural resource for understanding cancer. Our study reveals a wide divergence in cancer prevalence among vertebrate groups, with notably low rates in turtles and high rates in squamates and mammals. These findings can lead to new breakthroughs in understanding the biology of cancer.

evolutionary biology↗

bioRxiv2019

Universal Deep Sequence Models for Protein Classification

MotivationInferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification tasks are tailored to single classification tasks and rely on handcrafted features such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple finetuning step.\n\nResultsWe put forward a universal deep sequence model that is pretrained on unlabeled protein sequences from Swiss-Prot and finetuned on protein classification tasks. We apply it to three prototypical tasks, namely enzyme class prediction, gene ontology prediction and remote homology and fold detection. The proposed method performs on par with state-of-the-art algorithms that were tailored to these specific tasks or, for two out of three tasks, even outperforms them. These results stress the possibility of inferring protein properties from the sequence alone and, on more general grounds, the prospects of modern natural language processing methods in omics.\n\nAvailabilitySource code is available under https://github.com/nstrodt/UDSMProt.\n\nContactfirstname.lastname@hhi.fraunhofer.de

synthetic biology↗