Biology subjects

Nickel, M.

Publications and source records attributed to Nickel, M..

8 recordsLinked to original sources

bioRxiv2025

Targeted long-read RNA sequencing reveals the complexity of CLN3 transcription and the consequences of the most common 1-kb deletion in patients with juvenile CLN3 disease

Most genes are not yet fully annotated, and the extent of their transcript diversity and the roles and significance of specific isoforms is not understood. This information is therefore lacking for disease genes. The CLN3 gene underlies classic juvenile CLN3 disease, also known as juvenile neuronal ceroid lipofuscinosis, a rare paediatric neurodegenerative disorder. The most common cause of this biallelic disorder is a 1-kb intragenic deletion that removes two internal coding exons (exons 7 and 8). Here, we report findings from the first long-read RNA sequencing targeting CLN3 in blood samples derived from control individuals and from patients clinically and genetically diagnosed with juvenile CLN3 disease. We find that CLN3 transcription is complex, with >80 different transcripts encoding >35 different open reading frames (ORF) of different lengths, and no dominantly expressed transcript. The 1-kb deletion has direct consequences on this. This is consistent across patients, with total loss of some transcripts including those encoding the canonical 438 amino acid protein and other significant smaller isoforms. The highest expressed disease transcripts include those lacking exons 7 and 8 and encoding a 181 amino acid protein isoform, and other novel isoforms that lack additional exons and encode longer ORFs. The different effects on transcription of other CLN3 disease-causing variants are revealed in single patients. Together, these findings confirm the complexity of transcription at the CLN3 locus, reveal the impact of the 1-kb deletion and other variants on isoform abundance, and highlight the importance of understanding the contribution of these isoforms to CLN3 function in health and disease. Moreover, they impact the future design and development of personalised therapeutics and the design and generation of disease models. Finally, they underline the importance of full annotation for disease genes.

genetics↗

bioRxiv2023

Molecular profiling of sponge deflation reveals an ancient relaxant-inflammatory response

A hallmark of animals is the coordination of whole-body movement. Neurons and muscles are central to this, yet coordinated movements also exist in sponges that lack these cell types. Sponges are sessile animals with a complex canal system for filter-feeding. They undergo whole-body movements resembling "contractions" that lead to canal closure and water expulsion. Here, we combine 3D optical coherence microscopy, pharmacology, and functional proteomics to elucidate anatomy, molecular physiology, and control of these movements. We find them driven by the relaxation of actomyosin stress fibers in epithelial canal cells, which leads to whole-body deflation via collapse of the incurrent and expansion of the excurrent system, controlled by an Akt/NO/PKG/A pathway. A concomitant increase in reactive oxygen species and secretion of proteinases and cytokines indicate an inflammation-like state reminiscent of vascular endothelial cells experiencing oscillatory shear stress. This suggests an ancient relaxant-inflammatory response of perturbed fluid-carrying systems in animals. HighlightsO_LISponge deflation is driven by tension release in actomyosin stress fibers of epithelial pinacocytes C_LIO_LIAkt kinase/Nitric oxide/Protein kinase G/A regulate actomyosin relaxation C_LIO_LIAgitation-induced deflation coincides with an inflammatory state C_LIO_LIThe sponge relaxant-inflammatory response is evolutionary related to similar responses in the vertebrate vascular system C_LI

molecular biology↗

bioRxiv2022

Body-plan reorganization in a sponge correlates with microbiome change

Mounting evidence suggests that animals and their associated bacteria interact via intricate molecular mechanisms, and it is hypothesized that disturbances to the microbiome can influence animal development. Sponges diverged from other animals more than 750 MYA and represent one of the earliest branching animal phyla that exhibit symbiotic relationships with diverse bacteria. Over 41 microbial phyla have been found in association with sponges, forming a holobiont that is integral to aquatic ecosystems worldwide. Sponge-associated microbes contain an enriched set of proteins bearing eukaryotic-like domains, and their metabolism supports the host with nutrients. This indicates strong physiological interconnections in the holobiont, which are thought to be modulated by sponge immunity and pattern-recognition proteins. Despite the hypothesized tight physiological integration and ancient origin of the sponge holobiont, the effect of changes in the symbiotic community on the sponge metabolism and morphogenesis remains poorly understood. Here, we show that the loss of a key microbial sponge symbiont correlates with a stark body plan reorganization of the sponge host. This reorganization is coupled with broad transcriptomic changes and includes the modulation of signaling pathways known to be involved in morphogenesis and innate immune response in sponges and other animals. This study provides a combined genetic, physiological, and morphological assessment of the effect of changes in the microbiome on sponge post-embryonic development and homeostasis. The drastic microbiome reorganization and the correlated response observed in the sponge host provide evidence for a coupling between sponge transcriptomic state and the state of its microbiome. Our results suggest that sponges use molecular mechanisms to respond to changes in their microbiome and that the ability to sense and respond to microbiome perturbations has deep evolutionary origins among animals.

genomics↗

bioRxiv2021

Temporal-spectral signaling of sensory information and expectations in the cerebral processing of pain

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individuals expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas. These brain areas generate evoked potentials and oscillatory responses at different latencies and frequencies. Recent evidence has provided first insights into how oscillatory responses at different frequencies signal predictions and prediction errors. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. We therefore built upon a neuroimaging study which investigated the spatial signalling of sensory information, predictions and predictions errors in the processing of pain (Geuter et al., 2017). To complement and extend this study, we applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.

neuroscience↗

bioRxiv2020

Dynamics of brain function in chronic pain patients assessed by microstate analysis of resting-state electroencephalography

Chronic pain is a highly prevalent and severely disabling disease, which is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of brain activity during the resting-state. However, brain activity varies over time and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography (EEG) data of 101 patients suffering from chronic pain and 88 age- and gender-matched healthy controls. Microstate analysis describes EEG activity as a sequence of a limited number of topographies termed microstates, which remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, described resting-state brain activity in both groups and conditions. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in healthy participants. This difference was consistently found in eyes-open and eyes-closed EEG recordings. No evidence for differences in other microstates was found. As microstate D has been previously related to attentional networks and functions, abnormalities of microstate D might relate to dysfunctional attentional processes in chronic pain. These findings add to the understanding of the pathophysiology of chronic pain and might eventually contribute to the development of an EEG-based biomarker of chronic pain.

neuroscience↗

bioRxiv2019

Profiling cellular diversity in sponges informs animal cell type and nervous system evolution

The evolutionary origin of metazoan cell types such as neurons, muscles, digestive, and immune cells, remains unsolved. Using whole-body single-cell RNA sequencing in a sponge, an animal without nervous system and musculature, we identify 18 distinct cell types comprising four major families. This includes nitric-oxide sensitive contractile cells, digestive cells active in macropinocytosis, and a family of amoeboid-neuroid cells involved in innate immunity. We uncover presynaptic genes in an amoeboid-neuroid cell type, and postsynaptic genes in digestive choanocytes, suggesting asymmetric and targeted communication. Corroborating this, long neurite-like extensions from neuroid cells directly contact and enwrap choanocyte microvillar collars. Our data indicate a link between neuroid and immune functions in sponges, and suggest that a primordial neuro-immune system cleared intruders and controlled ciliary beating for feeding.

developmental biology↗

bioRxiv2019

Poincare Maps for Analyzing Complex Hierarchies in Single-Cell Data

The need to understand cell developmental processes spawned a plethora of computational methods for discovering hierarchies from scRNAseq data. However, existing techniques are based on Euclidean geometry, a suboptimal choice for modeling complex cell trajectories with multiple branches. To overcome this fundamental representation issue we propose Poincare maps, a method that harness the power of hyperbolic geometry into the realm of single-cell data analysis. Often understood as a continuous extension of trees, hyperbolic geometry enables the embedding of complex hierarchical data in only two dimensions while preserving the pairwise distances between points in the hierarchy. This enables direct exploratory analysis and the use of our embeddings in a wide variety of downstream data analysis tasks, such as visualization, clustering, lineage detection and pseudo-time inference. When compared to existing methods --unable to address all these important tasks using a single embedding-- Poincare maps produce state-of-the-art two-dimensional representations of cell trajectories on multiple scRNAseq datasets. More specifically, we demonstrate that Poincare maps allow in a straightforward manner to formulate new hypotheses about biological processes unbeknown to prior methods. Significance statementThe discovery of hierarchies in biological processes is central to developmental biology. We propose Poincare maps, a new method based on hyperbolic geometry to discover continuous hierarchies from pairwise similarities. We demonstrate the efficacy of our method on multiple single-cell datasets on tasks such as visualization, clustering, lineage identification, and pseudo-time inference.

bioinformatics↗

bioRxiv2019

Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography

Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically and comprehensively exploited the potential of electroencephalography (EEG) to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4 - 8 Hz) and gamma (> 60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results implicate increased theta and gamma synchrony in frontal brain areas in the pathophysiology of chronic pain. While substantial challenges concerning accuracy, specificity and validity of potential EEG-based disease markers remain to be overcome, our study identifies abnormal frontal synchrony at theta and gamma frequencies as promising targets for non-invasive brain stimulation and/or neurofeedback approaches.

neuroscience↗