Biology subjects

Helmchen, F.

Publications and source records attributed to Helmchen, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Scan field rotation with a K-mirror for fast two-photon imaging along curved planes

In contrast to the curved geometry of biological structures, the imaging plane of conventional microscopes is flat. In principle, axial scanning can adjust the focus to follow curved structures. In resonant scanning microscopes, which are broadly used for video-rate functional imaging, however, such focus adjustment is typically possible at rates faster than the slow (~30 Hz) scan axis but not as fast as the fast (~8000 Hz) resonant axis. The fixed direction of the fast resonant axis therefore constrains how the imaging plane can be tilted or curved using axial scanning, and limits how well it can be aligned with biological structures of interest. Here, we present an optical modification that overcomes this constraint. Specifically, we combine scan field rotation using a K-mirror with fast axial scanning using an electrically tunable lens. We demonstrate the versatility of our approach for calcium imaging by aligning the imaging plane with the curved pyramidal cell layer in mouse hippocampus, increasing the number of simultaneously imaged neurons. In addition, we image dendritic arbors of hippocampal and cortical pyramidal neurons that would otherwise be only partially accessible for fast imaging, and we apply our method to the curved layers of cerebellar Purkinje cells. Furthermore, we demonstrate how scan field rotation can be used to optimally orient a dendritic branch for high-speed subcellular glutamate imaging. Our approach is based on a single module and can therefore be retrofitted to standard two-photon systems. We openly share design specifications, 3D-printed parts, and custom ScanImage-compatible code to facilitate rapid adoption.

neuroscience↗

bioRxiv2026

Cellular Determinants of CA1 Pyramidal Cell Recruitment during Sharp-Wave Ripples

Hippocampal ripples, accompanied by highly synchronous neuronal firing, are critical for immediate offline memory consolidation, learning, and planning. However, the cellular mechanisms that determine which individual neurons are recruited to participate in action potential (AP) firing during ripples remain unclear. We investigated the membrane potential (Vm) dynamics of CA1 pyramidal cells during ripples using whole-cell recordings in awake, head-fixed mice. We found that ripple participation was strongly associated with concurrent membrane-potential depolarization on an event-to-event basis, whereas between-cell differences in overall participation propensity were jointly explained by ripple-associated depolarization and intrinsic excitability. Applying this framework across CA1 cell populations revealed that differences in recruitment between superficial and deep pyramidal cells were primarily driven by ripple-associated depolarization, counteracted by excitability. Differences between place and non-place cells were similarly driven by ripple-associated depolarization, though this effect acted in the same direction as excitability. Finally, we identified the post-ripple LFP rebound as a prominent marker of ripple diversity linked to post-ripple membrane-potential hyperpolarization at the single-neuron level. Together, these findings provide a mechanistic understanding of how CA1 pyramidal cells are selectively recruited during hippocampal ripples.

neuroscience↗

bioRxiv2026

PURELIGHT: a quantitative photon-counting framework unifying intensity and lifetime imaging at video rate across detector technologies

Quantitative fluorescence microscopy requires photon-efficiency, speed and accurate intensity and lifetime measurements. Time-correlated single-photon counting (TCSPC) simultaneously captures intensity and lifetime, but photon pile-up distorts both signals at high count rates, preventing fast acquisitions. Existing corrections discard photons, distort intensity, or require specialized detectors. Here we introduce PURELIGHT, an integrated hardware and software framework that simultaneously recovers undistorted intensities and lifetimes at count rates far beyond conventional pile-up limits. PURELIGHT works with hybrid photodetectors, silicon photomultipliers and photomultiplier tubes while retaining over three times more photons than alternative approaches. Using two-photon imaging, we showcase PURELIGHT's superior accuracy and spatial contrast, demonstrating video-rate subcellular lifetime imaging in awake mice, a unique lifetime-calibrated ratiometric modality and crosstalk-free temporal multiplexing. By removing the limits that have confined TCSPC to low-signal applications, PURELIGHT promotes the adoption of quantitative, photon-efficient microscopy across the life sciences.

neuroscience↗

bioRxiv2026

Layer-specific wide-field calcium imaging of neocortical activity

The mammalian neocortex is highly organized in local microcircuits and through long-range projection patterns between different regions. Since various features of local and long-range connectivity are determined by the cortical layer in which the respective neurons reside, understanding the flow of cortical information within and across layers is essential. Wide-field calcium imaging enables mesoscale functional mapping of genetically identified neurons across cortical areas. However, it has been applied primarily to superficial cortical layers, and systematic comparisons of wide-field signals across cortical layers are scarce. Here, we apply wide-field calcium imaging to different cortical layers using transgenic mouse lines with selective expression of GCaMP6f in layers 2/3, 5, and 6. We address several challenges of layer-specific wide-field imaging and provide possible solutions. First, to improve the registration of functional data to standard atlases, we demonstrate the benefit of layer-specific registration maps that are warped on the basis of the depth-dependent surface projections of the labeled cell populations. These maps help to assign the imaged calcium signals to the specific regions from which they originate. Second, we measure the depth-dependent blurring of wide-field fluorescence signals induced by light scattering and reveal stronger blurring in deep vs. superficial layers, in line with previous theoretical predictions from simulations. We used measured point spread functions to deconvolve single-whisker-evoked calcium signals in the barrel cortex and demonstrate improved signal confinement to individual barrel columns across layers. Finally, we investigate cross-regional functional connectivity during awake resting state periods for distinct layers. We find that mesoscopic functional connectivity is largely conserved between the cortical layers, with subtle differences for key regions of the default mode network (retrosplenial cortex and medial prefrontal cortex). Our approaches facilitate the comprehensive characterization of layer-specific cortico-cortical interactions, expanding wide-field calcium imaging as a powerful tool to investigate the layered organization of distributed brain dynamics.

neuroscience↗

bioRxiv2026

Deep learning enables feature extraction of 3D collagen architecture in cleared fibrotic tissues

Light-sheet fluorescence microscopy enables deep optical sectioning of large, cleared biological tissues. However, effective clearing of collagen-rich tissues remains a persistent technical challenge. Moreover, standardized workflows integrating three-dimensional imaging with computational analysis of collagen architecture are currently unavailable. Here, we present an integrated pipeline combining optimized tissue clearing, volumetric light-sheet imaging, and deep learning-based feature extraction of collagen architecture. Using experimental desmoid tumors as a proxy for collagen-dense tissues, we optimised DISCO-based clearing incorporating Fast Green FCF for collagen labelling. We achieved optical transparency and full 3D visualization of collagen architectures in desmoid tumors, human skin biopsies, and fibrotic mouse lung & liver tissues, including FFPE samples. Using the Benchtop mesoSPIM platform, we acquired high-resolution volumetric datasets and validated multimodal collagen imaging through two-photon microscopy with the Schmidt-Voigt objective. To enable automated feature extraction from these large volumetric datasets, we developed ColNet, a U-Net model for automated collagen fiber segmentation. ColNet demonstrated robust generalization across diverse human and mouse tissues without retraining or hyperparameter adjustment. This integrated workflow provides a foundation for future quantitative assessment of cell-extracellular matrix dynamics in a fibrotic context.

cancer biology↗

bioRxiv2026

Locus coeruleus noradrenaline elicits response profiles distinct from natural arousal in hippocampal neurons and astrocytes

The locus coeruleus (LC)-noradrenaline (NA) system is a central component of the brains response to arousal and stress. Yet how LC activity contributes to the cellular response profiles observed during natural arousal remains unclear. Here, we directly compared natural arousal with selective LC activation in mouse CA1, using physiologically titrated optogenetics, fiber photometry of NA and calcium signals, chronic two-photon imaging, and behavioral monitoring. While natural arousal robustly activated astrocytes, pyramidal cells, and interneurons, direct LC stimulation revealed a striking divergence in cellular response polarity and sensitivity. At levels of LC activation that correspond to arousal and moderate stress, we observed strong and reliable calcium responses in astrocytes, whereas pyramidal neurons and interneurons remained largely unaffected. Only at high-intensity LC stimulation did neurons exhibit a response, characterized by broad population-level inhibition of both pyramidal cells and interneurons, alongside the transient activation of an interneuron subpopulation that occupied distinct laminar positions in CA1. Thus, LC-driven NA release produces cell-specific effects in hippocampal CA1 that are distinct from and, at the population level for neurons even opposite to, cellular dynamics during natural arousal. Together, our results reveal a divergence in how astrocytes and neurons respond to LC-driven NA release and suggest that noradrenergic effects in the hippocampus at moderate levels of arousal and stress are predominantly mediated by astrocytes.

neuroscience↗

bioRxiv2025

Contralesional activity reflects compensation, while brainstem detour pathways support skilled motor recovery after stroke

Large strokes frequently result in lasting motor deficits and trigger extensive reorganization within the brain and spinal cord. Altered neuronal activity in the contralesional hemisphere has been documented in both humans and rodent models, yet its role in functional recovery versus maladaptation remains unresolved. Here, we used chronic wide-field calcium imaging to monitor bilateral cortical activity in mice performing a skilled reach-to-grasp task before and days to weeks after stroke. Strokes produced persistent fine motor impairments, which were only partly alleviated by intensive rehabilitative training. While cortical activity was in particular suppressed in the ipsilesional cortex after stroke, training promoted sustained increases in contralesional sensorimotor activity. However, ridge regression analysis of neural and behavioral data indicated that this activity largely reflected compensatory use of the intact paw rather than recovery of the impaired forelimb. Axonal tracing nevertheless revealed enhanced projections from contralesional motor cortex to ipsilesional brainstem nuclei - including the midbrain and pontine reticular nucleus - specifically in trained animals. These findings identify a rehabilitation-induced corticofugal pathway supporting motor recovery, highlighting a target for neuromodulation strategies in chronic post-stroke impairment.

neuroscience↗

bioRxiv2025

Separable neurocomputational mechanisms underlying multisensory learning

Efficient control of behavior requires multisensory learning from information distributed across senses. However, most neurocomputational studies have focused on unisensory signals. Here, we identify distinct but interacting neurocomputational mechanisms that support learning of multisensory associations. We designed a task in which behaviorally relevant information was available only from combinations of visual cues with either auditory or tactile cues. In 58 participants undergoing fMRI, we dissociated three processes: multisensory statistical learning (SL), modeled as stimulus-locked Shannon surprise; reinforcement learning (RL), modeled as feedback-locked signed reward prediction errors (RPEs); and feedback-locked unsigned RPEs (uRPEs), reflecting surprise about reward outcomes. Behaviorally, response times scaled with Shannon surprise (SL) while accuracy improved with feedback (RL). Model-based fMRI revealed dissociable but complementary networks: RPEs engaged ventral striatum, vmPFC, and left angular gyrus; surprise recruited bilateral angular gyrus, dlPFC, and precuneus; and uRPEs involved insula, dorsomedial prefrontal, and lateral frontoparietal cortices. Several of these regions extend beyond canonical learning circuits and may contribute to learning when behavior depends on information distributed across sensory modalities. All three networks were modality-general, showing comparable strength for audiovisual and visuotactile learning. Notably, left angular gyrus tracked both Shannon surprise and RPE, suggesting its potential role for integrating structural and value information. These findings indicate that the brain engages distinct but complementary systems for structure-based, reward-based, and outcomesurprise computations. By combining behavioral modeling and fMRI with a novel task design, we provide a framework for dissecting the neurocomputational architecture of multisensory learning.

neuroscience↗

bioRxiv2025

aDISCO: A Broadly Applicable Method for 3D Microscopy of Archival Paraffin-Embedded Human Tissues

Human surgery and autopsy specimens are routinely stored as formalin-fixed paraffin-embedded (FFPE) tissue blocks. Diagnoses are based on microscopic examination of two-dimensional sections. Good clinical practice requires that samples be retained for decades, thus giving rise to vast archives of healthy and diseased tissues. While tissue clearing and whole-mount microscopy enable 3D analysis, FFPE human tissue blocks are often unsuitable for clearing and immunolabeling due to their large size, extensive cross-linking, and wax embedding. Here, we introduce archival DISCO (aDISCO), a versatile and robust clearing method designed to overcome these challenges. aDISCO achieves complete clearing and immunolabeling of large samples stored for 15 years or more. We applied aDISCO to human brain, spinal cord, peripheral nerve, skin, muscle, heart, kidney, liver, spleen, colon, and lung, using a broad range of antibodies. To investigate the clinical usefulness of quantitative 3D histology by aDISCO, we performed a case study of focal cortical dysplasia, a neurodevelopmental disease causing epilepsy. Using deep-learning-based analysis, we found disrupted cortical layering and both focal and global neuronal density variations in FCD, features that are likely to be overlooked by conventional histology. In summary, aDISCO delivers large datasets suitable for deep-learning-based processing, enabling the detection of subtle and sparse pathologies in large archival human tissue specimens.

bioengineering↗

bioRxiv2025

Spike inference from calcium imaging data acquired with GCaMP8 indicators

For neuroscience to be reproducible, its key methods must be quantitative and interpretable. Calcium imaging is such a key method, but it records neuronal activity only indirectly and is therefore difficult to interpret. These difficulties arise from the kinetics, nonlinearity, and sensitivity of calcium indicators, but also from the methods used for signal analysis. Here, we evaluate how methods for spike inference can be optimized to interpret data with the recently developed calcium indicator GCaMP8. We find that the indicator linearity of GCaMP8 enables more accurate recovery of high-frequency spiking events and the detection of single action potentials. Ground truth recordings from mouse neocortex show that the most linear calcium variants, GCaMP8s and GCaMP8m - but not GCaMP6, GCaMP7f, or GCaMP8f - robustly detect isolated spikes in pyramidal neurons under realistic noise conditions. In addition, we fine-tune and benchmark existing algorithms for spike inference (CASCADE, OASIS, MLSpike) with GCaMP8 data, investigate spike inference for interneurons, and demonstrate how the fast rise time of GCaMP8 enables low-latency real-time detection of neuronal activity. Together, our study provides tools and guidelines to optimally process calcium signals with GCaMP8 and highlights the key role of linearity in improving the interpretability of calcium imaging.

neuroscience↗

bioRxiv2024

Hierarchy of prediction errors shapes the learning of context-dependent sensory representations

How sensory information is interpreted depends on context, yet the neural mechanisms by which context shapes sensory processing remain poorly understood. To address this question, we developed a computational model constrained by in vivo functional imaging of cortical neurons in mice during reversal learning of a tactile sensory discrimination task. During learning, layer 2/3 somatosensory neurons enhanced their response to reward-predictive stimuli. The model accounted for these observations through selective top-down gain amplification of apical dendritic inputs, accompanied by reduced reward-prediction errors and increased confidence in outcome predictions. Upon rule-reversal, the lateral orbitofrontal cortex, through disinhibitory VIP interneurons, encoded a context-prediction error signaling a loss of confidence. The hierarchy of reward- and context-prediction errors across cortical areas is mirrored in top-down signals modulating apical activity of simulated pyramidal neurons in the primary sensory cortex. The model explains how contextual changes are detected and how reward- and context-prediction error signals, originating in different cortical regions, interact to reshape the sensory representation.

neuroscience↗

bioRxiv2024

Coordinated multi-level adaptations across neocortical areas during task learning

The coordinated changes of neural activity during learning, from single neurons to populations of neurons and their interactions across brain areas, remain poorly understood. To reveal specific learning-related changes, we applied multi-area two-photon calcium imaging in mouse neocortex during training of a sensory discrimination task. We uncovered coordinated adaptations in primary somatosensory area S1 and the anterior (A) and rostrolateral (RL) areas of posterior parietal cortex (PPC). At the single-neuron level, task-learning was marked by increased number and stabilized responses of task neurons. At the population level, responses exhibited increased dimensionality and reduced trial-to-trial variability, paralleled by enhanced encoding of task information. The PPC areas, especially area A, became gradually engaged, opening additional within-area subspaces and inter-area subspaces with S1. Task encoding subspaces gradually aligned with these interaction subspaces. Behavioral errors correlated with reduced neuronal responses, decreased encoding accuracy, and misaligned subspaces. Thus, multi-level adaptations within and across cortical areas contribute to learning-related refinement of sensory processing and decision-making.

neuroscience↗

bioRxiv2024

Pythia: Non-random DNA repair allows predictable CRISPR/Cas9 integration and gene editing

CRISPR-based genome engineering holds enormous promise for basic science and therapeutic applications. Integrating and editing DNA sequences is still challenging in many cellular contexts, largely due to insufficient control of the repair process. We find that repair at the genome-cargo interface is predictable by deep-learning models and adheres to sequence context specific rules. Based on in silico predictions, we devised a strategy of triplet base-pair repeat repair arms that correspond to microhomologies at double-strand breaks (trimologies), which facilitated integration of large cargo (>2 kb) and protected the targeted locus and transgene from excessive damage. Successful integrations occurred in >30 loci in human cells and in in vivo models. Germline transmissible transgene integration in Xenopus, and endogenous tagging of tubulin in adult mice brains demonstrated integration during early embryonic cleavage and in non-dividing differentiated cells. Further, optimal repair arms for single- or double nucleotide edits were predictable, and facilitated small edits in vitro and in vivo using oligonucleotide templates. We provide a design-tool (Pythia, pythia-editing.org) to optimize custom integration, tagging or editing strategies. Pythia will facilitate genomic integration and editing for experimental and therapeutic purposes for a wider range of target cell types and applications.

molecular biology↗

bioRxiv2024

Brain-wide microstrokes affect the stability of memory circuits in the hippocampus

Cognitive deficits affect over 70% of stroke survivors, yet the mechanisms by which multiple small ischemic events contribute to cognitive decline remain poorly understood. In this study, we employed chronic two-photon calcium imaging to longitudinally track the fate of individual neurons in the hippocampus of mice navigating a virtual reality environment, both before and after inducing brain-wide microstrokes. Our findings reveal that, under normal conditions, hippocampal neurons exhibit varying degrees of stability in their spatial memory coding. However, microstrokes disrupted this functional network architecture, leading to cognitive impairments. Notably, the preservation of stable coding place cells, along with the stability, precision, and persistence of the hippocampal network, was strongly predictive of cognitive outcomes. Mice with more synchronously active place cells near important locations demonstrated recovery from cognitive impairment. This study uncovers critical cellular responses and network alterations following brain injury, providing a foundation for novel therapeutic strategies preventing cognitive decline.

neuroscience↗

bioRxiv2024

Investigating microscopic angioarchitecture in the human visual cortex in 3D with angioMASH tissue clearing and labelling

Non-invasive imaging techniques, such as ultra-high field fMRI, are intricately connected to the underlying vasculature and are approaching ever higher resolutions. For the analysis of fMRI signals over cortical depth at such high resolutions, microvascular differences might have to be taken into account. Therefore, a better understanding of the laminar distribution and interareal differences in the cortical vasculature is becoming more important. However, in comparison to cyto- and myeloarchitecture, the study of angioarchitecture has received far less attention and relatively few methods have been described to visualise the vascular network in the human brain. Here we present angioMASH, a method for double labelling angioarchitecture and cytoarchitecture in archival human brain tissue, based on the recently published MASH protocol. The double labelling and optical clearing of thick human brain slices can be accomplished within 16 days. We use this method to acquire multi-resolution 3D datasets of combined cyto- and angioarchitecture in large ([~]30 mm x 10 mm x 3 mm) volumes of human samples covering visual areas V1 and V2. We demonstrate for the first time, that classical angioarchitectonic features can be visualised in the human cortex and in 3D using tissue clearing and light-sheet microscopy. Lastly, we show differences in the vessel density and orientation over cortical depth within and between the two areas. Especially in V1, the vascular density is not homogeneous over cortical depth but shows distinct layering. These layers are also determined by changes in the orientation of the blood vessels from a predominantly radial to a more tangential distribution. In V2, differences in vascular density are less pronounced, but orientation profiles follow a similar trend over cortical depth. We discuss potential consequences of these differences for the interpretation of non-invasive functional imaging modalities such as fMRI or fNIRS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/609648v2_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@f9f841org.highwire.dtl.DTLVardef@1197e29org.highwire.dtl.DTLVardef@a9c9ccorg.highwire.dtl.DTLVardef@ffaefe_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Spike inference from mouse spinal cord calcium imaging data

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a non-supervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms that were designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models re-trained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide re-trained models that can be applied to spinal cord data of variable noise levels and frame rates. Together, our ground-truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system. Significance StatementCalcium imaging is a powerful method for measuring the activity of genetically identified neurons. However, accurate interpretation of calcium transients depends on having a detailed understanding of how neuronal activity correlates with fluorescence. Such calibration recordings have been performed for cerebral cortex but not yet for most other CNS regions and neuron types. Here, we obtained ground truth data in spinal cord by conducting simultaneous calcium and electrophysiology recordings in excitatory and inhibitory neurons. We systematically investigated the transferability of cortical algorithms to spinal neuron subpopulations and generated inference algorithms optimized to excitatory and inhibitory neurons. Our study provides a foundation for the rigorous interpretation of calcium imaging data from spinal cord. Conflict of interest statementThe authors declare no competing financial conflicts of interest.

neuroscience↗

bioRxiv2023

Aberrant hippocampal Ca2+ micro-waves following synapsin-dependent adenoviral expression of Ca2+ indicators

Genetically encoded calcium indicators (GECIs) such as GCaMP are invaluable tools in neuroscience to monitor neuronal activity using optical imaging. The viral transduction of GECIs is commonly used to target expression to specific brain regions, can be conveniently used with any mouse strain of interest without the need for prior crossing with a GECI mouse line and avoids potential hazards due to the chronic expression of GECIs during development. A key requirement for monitoring neuronal activity with an indicator is that the indicator itself minimally affects activity. Here, using common adeno-associated viral (AAV) transduction procedures, we describe spatially confined aberrant Ca2+ micro-waves slowly travelling through the hippocampus following expression of GCaMP6, GCaMP7 or R-CaMP1.07 driven by the synapsin promoter with AAV-dependent gene transfer, in a titre-dependent fashion. Ca2+ micro-waves developed in hippocampal CA1 and CA3, but not dentate gyrus (DG) nor neocortex, were typically first observed at 4 weeks after viral transduction, and persisted up to at least 8 weeks. The phenomenon was robust, observed across laboratories with various experimenters and setups. Our results indicate that aberrant hippocampal Ca2+ micro-waves depend on the promoter and viral titre of the GECI, density of expression as well as the targeted brain region. We used an alternative viral transduction method of GCaMP which avoids this artifact. The results show that commonly used Ca2+-indicator AAV transduction procedures can produce artefactual Ca2+ responses. Our aim is to raise awareness in the field of these artefactual transduction-induced Ca2+ micro-waves and we provide a potential solution. Impact statement: Common AAV transduction procedures induce artefactual spatially confined Ca2+ waves in the hippocampus.

neuroscience↗

bioRxiv2023

A HEV ORF2 protein-mediated mechanism of hepatitis E associated kidney disease.

Hepatitis E virus (HEV) infection, one of the most common forms of hepatitis worldwide, is often associated with extrahepatic, particularly renal, manifestations. However, the underlying mechanisms are incompletely understood. Here, we report the development of a de novo immune complex-mediated glomerulonephritis (GN) in a kidney transplant recipient with chronic hepatitis E. Applying immunostaining, electron microscopy, and mass spectrometry after laser-capture microdissection, we show that GN developed in parallel with increasing glomerular deposition of a noninfectious form of HEV open reading frame 2 (ORF2, capsid) protein secreted in excess. HEV particles or RNA, however, were not detectable. Patients with acute hepatitis E displayed similar but less pronounced deposits. Our results elucidate an immunologic mechanism by which this hepatotropic virus causes variable renal manifestations and establish a link between the HEV ORF2 protein and hepatitis E-associated GN. They directly provide a tool for etiology-based diagnosis of HEV-associated GN as a distinct entity and suggest therapeutic implications.

pathology↗