Biology subjects

Zimmermann, C.

Publications and source records attributed to Zimmermann, C..

10 recordsLinked to original sources

bioRxiv2025

TU_MyCo-Vision: A Deep Learning Tool for Detection of Cell Morphologies in Fungal Microscopic Images

Morphological switching in response to environmental stimuli is a well-known phenomenon in fungi, leading to diverse morphotypes. Microscopic observation remains a widely used approach to study these phenotypes. However, variation in sample preparation and operators skill can limit the scale of sample processing or introduce bias. Although several image-based cell detection tools have been developed, most are tailored to specific applications or limited to a particular taxon. To address the need for a tool applicable to the polymorphic, yeast-like fungus Aureobasidium pullulans, and with potential applicability to other taxa, we developed TU_MyCo-Vision, an Ultralytics YOLO (You Only Look Once) based object detection tool for identifying 13 fungal morphotypes in bright-field microscopic images. The tool integrates a YOLOv11m-based object detector trained on a custom dataset of 1,504 annotated images and a standalone graphical user interface that enables downstream data analysis and visualization of results. The best-performing model (Zulu_s3) achieved a mean precision of 73.4%, a recall of 66.5%, a mean average precision at 50% IoU (mAP@50) of 73.5%, and a mean average precision at varying IoU thresholds between 50 to 90% IoU (mAP@50-95) of 54.5% across all 13 classes. The single-group analysis pipeline was validated on a 90-image test set, generating six quantitative summaries, including absolute counts, relative and mean relative abundance plots, stacked bar plots, and clustered heatmaps. Multi-group evaluation on previously unseen datasets comprising Candida albicans, Komagataella phaffii, and Aspergillus niger spores demonstrated the tools potential applicability to other genera. TU_MyCo-Vision is distributed as a fully packaged, cross-platform executable, eliminating the need for environment setup or manual installation of dependencies. Built entirely on open-source frameworks, it provides a foundational and potentially extensible solution for automated fungal morphology detection and analysis. Author SummaryWe developed TU_MyCo-Vision to address challenges in fungal microscopic imaging. Fungi, such as Aureobasidium pullulans, display a remarkable ability to switch cell shapes (up to thirteen in this species alone) depending on their environment. While microscopy remains a popular method for observing these changes, manual analysis is limited by individual expertise and the number of images that can be processed, often making results subjective and difficult to scale. To overcome these challenges, we built an Ultralytics YOLOv11-based cell detector that can automatically detect and categorize thirteen fungal cell shapes from brightfield microscopic images. We designed TU_MyCo-Vision to be accessible, with a simple graphical user interface, integrated data analysis suite, and distribution as a standalone application for both Windows and macOS, so it can be used even by those with limited computational skills. Our tool demonstrated strong performance, achieving over 73% precision. Importantly, it also worked well on images from other fungal species, showing potential to be further developed as a general fungal cell morphology tool. We hope TU_MyCo-Vision will contribute to making standardized, high-throughput phenotyping of fungi accessible to a broader community.

microbiology↗

bioRxiv2025

Genome sequencing and physiological characterization of three Neoarthrinium moseri strains

Fungi play essential ecological roles and have been utilized by humans for diverse applications such as industrial enzyme production or as sources of bioactive compounds. Recent research has highlighted the Amphisphaeriales order (Ascomycota) as promising producers of secondary metabolites of pharmaceutical importance. Within this family, the recently established genus Neoarthrinium includes species such as N. brasiliensis, N. lithocarpicola, N. moseri, N. trachycarpi, and N. urticae. Existing literature has primarily focused on the taxonomy and phylogeny of Neoarthrinium, leaving its physiology, ecology, and metabolic potential unexplored. This study presents the first investigation of the metabolic and genomic potential of N. moseri. We describe the isolation of two South-Asian N. moseri strains and the genome sequencing of these strains alongside the Colombian ex-type strain for the species. Comparative genome analysis reveals an exceptionally high number of biosynthetic gene clusters (BGCs), surpassing those of many other fungi in the Amphisphaeriales order. Additionally, the genome of N. moseri contains a diverse repertoire of carbohydrate-active enzymes (CAZymes), supporting its hypothesized ecological role as a phyllosphere fungus (putatively an endophyte and/or saprotroph). Ecophysiological assays, including BIOLOG phenotyping, demonstrate its ability to utilize a broad range of carbon sources, emphasizing ecological versatility. This study highlights N. moseri as a promising candidate for secondary metabolite discovery, providing foundational insights into the metabolic and genomic potential of the Neoarthrinium genus and related fungi.

microbiology↗

bioRxiv2025

In vivo activation of the dia BGC allows consolidation of the biosynthetic pathways of diaporthin, dichlorodiaporthin, diaporthinic acid, and diaporthinol

Fungal secondary metabolites exhibit remarkable chemical diversity and biological activity, making them valuable sources of bioactive compounds. A group of polyketides, with a similar core structure, have been isolated previously from different fungi - the phytotoxins diaporthin and orthosporin, the mediocre antimicrobial dichlorodiaporthin, as well as diaporthinol and diaporthinic acid. Previous studies in Aspergillus oryzae suggest that diaporthin and orthosporin originate from a different biosynthetic gene cluster than dichlorodiaporthin, while the biosynthetic routes for diaporthinic acid and diaporthinol have not yet been identified. In this study, we successfully activated the dia biosynthetic gene cluster in Trichoderma reesei via transcription factor overexpression, leading to the identification of diaporthinic acid as the primary metabolite. Structural elucidation using NMR confirmed its identity, while bioactivity assays revealed no significant antimicrobial effects. Further, diaporthin, orthosporin, dichlorodiaporthin, and diaporthinol, as well as an isomer of alternariol were attributed to the same cluster. Gene deletion experiments demonstrated that Dia1, Dia4, and Dia5 are essential for diaporthinic acid biosynthesis, with Dia4 likely catalyzing the oxidation of dichlorodiaporthin yielding diaporthinic acid. Dia2 and Dia3 were found to be dispensable, challenging previous in vitro findings for the biosynthesis of dichlorodiaporthin. These findings provide new insights into the biosynthetic network of the dia BGC, expanding our understanding of natural product biosynthesis in filamentous fungi.

biochemistry↗

bioRxiv2024

Discovery of a novel antifungal compound, ilicicolin K, through genetic activation of the ilicicolin biosynthetic pathway in Trichoderma reesei

In the quest to discover novel antifungal agents and new antifungal production processes, we investigated the biosynthetic gene cluster (BGC) for ilicicolin H in the fungus Trichoderma reesei. While the BGC is silent under standard cultivation conditions, we achieved to activate it by over-expressing its transcription factor TriliR. Successful BGC activation was confirmed by RT-qPCR, proteomic and metabolomic analyses. Metabolomic profiling upon BGC expression revealed high-yield production of the supposed main product ilicicolin H. To elucidate the functionality of this BGC, we employed a combination of overexpression and deletions of individual biosynthetic gene cluster constituents. Deletion of triliA, encoding for the core polyketide synthase TriliA, completely ceased product formation, as expected. In contrast to previous heterologous expression experiments, we could demonstrate that the epimerase TriliE is necessary for the formation of ilicicolin H in the native host. While we hardly observed any of the previously reported side- or shunt products associated with heterologous ilicicolin H expression, we discovered a novel member of the ilicicolin family using a metabolomic molecular networking approach. This new compound, which we termed ilicicolin K, is expressed in substantial amounts in the genetically engineered Trichoderma reesei, enabling us to elucidate its structure by NMR. The structure of ilicicolin K is similar to that of ilicicolin H but differs by an additional hydroxylation and an intramolecular etherification of the hydroxyl group at the pyridone towards the tyrosine moiety of the molecule. Initial tests of ilicicolin K showed antifungal activity against Saccharomyces cerevisiae and Aspergillus nidulans with a similar minimum inhibitory concentration as ilicicolin H.

biochemistry↗

bioRxiv2022

3D pose estimation enables virtual head-fixation in freely moving rats

The impact of spontaneous movements on neuronal activity has created the need to quantify behavior. We present a versatile framework to directly capture the 3D motion of freely definable body points in a marker-free manner with high precision and reliability. Combining the tracking with neural recordings revealed multiplexing of information in the motor cortex neurons of freely moving rats. By integrating multiple behavioral variables into a model of the neural response, we derived a virtual head-fixation for which the influence of specific body movements was removed. This strategy enabled us to analyze the behavior of interest (e.g., front paw movements). Thus, we unveiled an unexpectedly large fraction of neurons in the motor cortex with tuning to the paw movements, which was previously masked by body posture tuning. Once established, our framework can be efficiently applied to large datasets while minimizing the experimental workload caused by animal training and manual labeling.

neuroscience↗

bioRxiv2021

Kel1 is a phosphorylation-regulated noise suppressor of the pheromone signaling pathway

Mechanisms have evolved that allow cells to detect signals and generate an appropriate response. The accuracy of these responses relies on the ability of cells to discriminate between signal and noise. How cells filter noise in signaling pathways is not well understood. Here, we analyze noise suppression in the yeast pheromone signaling pathway and show that the poorly characterized protein Kel1 serves as a major noise suppressor and prevents cell death. At the molecular level, Kel1 prevents spontaneous activation of the pheromone response by inhibiting membrane recruitment of Ste5 and Far1. Only a hypophosphorylated form of Kel1 suppresses signaling, reduces noise and prevents pheromone-associated cell death, and our data indicate that the MAPK Fus3 contributes to Kel1 phosphorylation. Taken together, Kel1 serves as a phospho-regulated suppressor of the pheromone pathway to reduce noise, inhibit spontaneous activation of the pathway, regulate mating efficiency, and to prevent pheromone-associated cell death.

cell biology↗

bioRxiv2020

A new perspective on the evolution of the interaction between the Vg/VGLL1-3 proteins and the TEAD transcription factors

The most downstream elements of the Hippo pathway, the TEAD transcription factors, are regulated by several cofactors, such as Vg/VGLL1-3. Earlier findings on human VGLL1 and here on human VGLL3 show that these proteins interact with TEAD via a conserved amino acid motif called the TONDU domain. Surprisingly, our studies reveal that the TEAD-binding domain of Drosophila Vg and of human VGLL2 is more complex and contains an additional structural element, an {Omega}-loop, that contributes to TEAD binding and in vivo function. To explain this unexpected structural difference between proteins from the same family, we propose that, after the genome-wide duplications at the origin of vertebrates, the {Omega}-loop present in an ancestral VGLL gene has been lost in some VGLL variants. These findings illustrate how structural and functional constraints can guide the evolution of transcriptional cofactors to preserve their ability to compete with other cofactors for binding to transcription factors.

biochemistry↗

bioRxiv2020

FreiPose: A Deep Learning Framework for Precise Animal Motion Capture in 3D Spaces

The increasing awareness of the impact of spontaneous movements on neuronal activity has raised the need to track behavior. We present FreiPose, a versatile learning-based framework to directly capture 3D motion of freely definable points with high precision (median error < 3.5% body length, 41.9% improvement compared to state-of-the-art) and high reliability (82.8% keypoints within < 5% body length error boundary, 72.0% improvement). The versatility of FreiPose is demonstrated in two experiments: (1) By tracking freely moving rats with simultaneous electrophysiological recordings in motor cortex, we identified neuronal tuning to behavioral states and individual paw trajectories. (2) We inferred time points of optogenetic stimulation in rat motor cortex from the measured pose across individuals and attributed the stimulation effect automatically to body parts. The versatility and accuracy of FreiPose open up new possibilities for quantifying behavior of freely moving animals and may lead to new ways of setting up experiments.

neuroscience↗

bioRxiv2017

Mechanical mapping of spinal cord development and repair in living zebrafish larvae using Brillouin microscopy

The mechanical properties of biological tissues are increasingly recognized as important factors in developmental and pathological processes. Most existing mechanical measurement techniques either necessitate destruction of the tissue for access or provide insufficient spatial resolution. Here, we show for the first time a systematic application of confocal Brillouin microscopy to quantitatively map the mechanical properties of spinal cord tissues during biologically relevant processes in a contact-free and non-destructive manner. Living zebrafish larvae were mechanically imaged in all anatomical planes, during development and after spinal cord injury. These experiments revealed that Brillouin microscopy is capable of detecting the mechanical properties of distinct anatomical structures without interfering with the animals natural development. The Brillouin shift within the spinal cord increased during development and transiently decreased during the repair processes following spinal cord transection. By taking into account the refractive index distribution, we explicitly determined the apparent longitudinal modulus and viscosity of different larval zebrafish tissues. Importantly, mechanical properties differed between tissues in situ and in excised slices. The presented work constitutes the first step towards an in vivo assessment of spinal cord tissue mechanics during regeneration, provides a methodical basis to identify key determinants of mechanical tissue properties and allows to test their relative importance in combination with biochemical and genetic factors during developmental and regenerative processes.

biophysics↗

bioRxiv2017

Cerebellar Degeneration Affects Cortico-Cortical Connectivity In Motor Learning Networks

The cerebellum plays an important role in motor learning as part of a cortico-striato-cerebellar network. Patients with cerebellar degeneration typically show impairments in different aspects of motor learning, including implicit motor sequence learning. How cerebellar dysfunction affects interactions in this cortico-striato-cerebellar network is poorly understood. The present study investigated the effect of cerebellar degeneration on activity in causal interactions between cortical and subcortical regions involved in motor learning. We found that cerebellar patients showed learning-related increase in activity in two regions known to be involved in learning and memory, namely parahippocampal cortex and cerebellar Crus I. The cerebellar activity increase was observed in non-learners of the patient group whereas learners showed an activity decrease. Dynamic causal modelling analysis revealed that modulation of M1 to cerebellum and putamen to cerebellum connections were significantly more negative for sequence compared to random blocks in controls, replicating our previous results, and did not differ in patients. In addition, a separate analysis revealed a similar effect in connections from SMA and PMC to M1 bilaterally. Again, neural network changes were associated with learning performance in patients. Specifically, learners showed a negative modulation from right SMA to right M1 that was similar to controls, whereas this effect was close to zero in non-learners. These results highlight the role of cerebellum in motor learning and demonstrate the functional role cerebellum plays as part of the cortico-striato-cerebellar network.

neuroscience↗