Biology subjects

Schubert, T.

Publications and source records attributed to Schubert, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Super-resolution STED imaging in the inner and outer whole-mount mouse retina

Since its invention in 1994, super-resolution microscopy has become a popular tool for advanced imaging of biological structures, allowing visualisation of subcellular structures at a spatial scale below the diffraction limit. Thus, it is not surprising that recently, different super-resolution techniques are being applied in neuroscience, e.g. to resolve the clustering of neurotransmitter receptors and protein complex composition in presynaptic terminals. Still, the vast majority of these experiments were carried out either in cell cultures or very thin tissue sections, while there are only a few examples of super-resolution imaging in thick (> ~50 m) biological samples. In that context, the mammalian whole-mount retina has rarely been studied with super-resolution microscopy. Here, we aimed at establishing a stimulated-emission-depletion (STED) microscopy protocol for imaging whole-mount retina. To this end, we developed sample preparation including horizontal slicing of retinal tissue, an immunolabeling protocol with STED-compatible fluorophores and optimised the STED microscopes settings. We labelled subcellular structures in somata, dendrites, and axons of retinal ganglion cells in the inner mouse retina. Under optimal conditions, we achieved a mean lateral spatial resolution of ~120 nm (using the full width of half-maximum as a proxy) for the thinnest filamentous structures in our preparation and a resolution enhancement of two or higher compared to conventional confocal images. When combined with horizontal slicing of the retina, these settings allowed us visualisation of putative GABAergic horizontal cell synapses in the outer retina with a similar resolution. Taken together, we successfully established a STED protocol for reliable super-resolution imaging in the whole-mount mouse retina, which enables investigating, for instance, protein complex composition and cytoskeletal ultrastructure at retinal synapses in health and disease.

neuroscience↗

bioRxiv2022

Impact of single mutations on binding kinetics oftriplex forming oligos revealed by fluorescence proximitysensing in heliX(R) biosensor

The sequence specific association of RNA with DNA via formation of RNA/DNA triple helices is relevant for regulation of gene expression, repair mechanisms, and chromatin organization. Formation of such RNA/DNA triplexes requires poly-purine sequences, which allow for Hoogsteen base-paring in addition to Watson-Crick pairing in the major groove of DNA. Binding of triplex forming oligos (TFOs) is sequence-specific and understanding sequence dependencies is key for the development of targeted tools for gene therapy. Here, we highlight a direct approach for determining binding kinetics and binding constants for TFOs using the state-of-the-art heliX(R)biosensor tool. With this, we provide key insights into the binding kinetics of RNA and DNA TFOs to a triplex targeting site (TTS)-containing DNA double helix measured in real-time. Dependent on the introduced base, point mutations in one position of a triplex forming oligo (TFO) can change the dissociation constant (KD) by several orders of magnitude or just by one log, affecting primarily the dissociation rate. Furthermore, we demonstrate that the heliX(R)biosensor assay is also well-suited for detection of rather weak triplex formation. The weakest binding we could identify was 140 M, for a TFO, which other studies considered as non-binding.

biophysics↗

bioRxiv2022

Spike desensitisation as a mechanism for high-contrast selectivity in retinal ganglion cells

In the vertebrate retina, several dozens of parallel channels relay information about the visual world to the brain. These channels are represented by the different types of retinal ganglion cells (RGCs), whose responses are rendered selective for distinct sets of visual features by various mechanisms. These mechanisms can be roughly grouped into synaptic interactions and cell-intrinsic mechanisms, with the latter including dendritic morphology as well as ion channel complement and distribution. Here, we investigate how strongly ion channel complement can shape RGC output by comparing two mouse RGC types, the well-described ON alpha cell and a little-studied ON cell that is EGFP-labelled in the Igfbp5 mouse line and displays an unusual selectivity for high-contrast stimuli. Using patch-clamp recordings and computational modelling we show that in ON Igfbp5 cells - but not in the ON alpha cells - a higher activation threshold and a pronounced slow inactivation of the voltage-gated Na+ channels are responsible for the distinct contrast tuning and transient responses of ON Igfbp5 RGCs, respectively. This study provides an example for the powerful role that the last stage of retinal processing can play in shaping RGC responses. SIGNIFICANCE STATEMENTHere, we investigated, how voltage-gated sodium channels contribute to shaping the light responses of mouse retinal ganglion cells. Using single-cell electrophysiology and computational modelling, we studied a ganglion cell type that displays highly transient responses and an unusual selectivity for visual high-contrast stimuli. We found that the cells characteristic responses were largely determined by intrinsic mechanisms, notably, a high activation threshold and a pronounced slow inactivation of its voltage-gated sodium channels. Therefore, our study demonstrates how sodium channels at the last stage of retinal signal processing can contribute to shape retinal output to higher visual areas the brain; it also adds a rare example for how channel complement can be directly linked to feature selectivity.

neuroscience↗

bioRxiv2022

The bacterial lectin LecA from P. aeruginosa alters membrane organization by dispersing ordered domains

The assembly and dynamic reorganization of plasma membrane nanodomains (also known as "lipid rafts") play key roles in host cell infection by human pathogens (e.g. viruses and bacteria). Viruses and bacteria can trigger the reorganization of lipid rafts which leads to membrane invaginations and downstream signaling that promote infection. Such reorganizations can be induced by interactions of bacterial or viral carbohydrate proteins (so-called lectins) with lipid raft glycosphingolipids (GSLs). Here, we studied the GSL globotriaosylceramide (Gb3) which is a key receptor involved in the cellular uptake of the gram-negative bacterium P. aeruginosa. The bacterial surface lectin LecA targets Gb3 and promotes bacterial invasion via the "lipid zipper" mechanism. However, the impact of LecA on the organization of membrane nanodomains is unknown yet. We mimicked of the plasma membrane using supported lipid bilayers (SLBs) that contained liquid-ordered (Lo, "raft-like", enriched in sphingolipids and GSLs) and liquid-disordered (Ld, "non-raft-like" enriched in DOPC) lipid domains. Upon interaction with LecA, the Lo domains in the SLBs reshaped and dispersed. Moreover, deformation of SLBs was observed as LecA formed membrane multilayers on SLBs surface. We further dissected this process to reveal the impact of Gb3 structure, bilayer composition and LecA valence on the Lo reorganization.

biophysics↗

bioRxiv2022

Connecting the Dots: PHF13 and cohesin promote polymer-polymer phase separation of chromatin into chromosomes

How interphase chromatin compacts into mitotic chromosomes has eluded researchers for over a century. Here we show that PHF13, a tightly regulated H3K4me epigenetic reader, and cohesin, a mediator of chromatin architecture, cooperate to drive polymer-polymer-phase-separation (PPPS) and higher order compaction of chromatin into chromosomes. PHF13 interacts with cohesin, shows similar dynamics during mitosis, and their co-depletion dramatically impairs mitotic condensation. Mechanistically, we demonstrate that PHF13 stabilizes cohesin chromatin interactions and that itself oligomerizes, resulting in a polymer with increased chromatin avidity and the ability to bridge neighboring and distant nucleosomes. Consistently, molecular dynamic simulations modelling the ability of PHF13 and cohesin to drive chromatin phase separations recapitulated our in vivo observations and are in line with 2-step condensation models.

cell biology↗

bioRxiv2022

Efficient coding of natural scenes improves neural system identification

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically-plausible filters. We found these results to be consistent for retinal responses to different stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. In summary, our results support the hypothesis that efficiently encoding environmental inputs can improve system identification models of early visual processing.

neuroscience↗

bioRxiv2021

Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience

Integrating data from multiple experiments is common practice in systems neuroscience but it requires inter-experimental variability to be negligible compared to the biological signal of interest. This requirement is rarely fulfilled; systematic changes between experiments can drastically affect the outcome of complex analysis pipelines. Modern machine learning approaches designed to adapt models across multiple data domains offer flexible ways of removing inter-experimental variability where classical statistical methods often fail. While applications of these methods have been mostly limited to single-cell genomics, in this work, we develop a theoretical framework for domain adaptation in systems neuroscience. We implement this in an adversarial optimization scheme that removes inter-experimental variability while preserving the biological signal. We compare our method to previous approaches on a large-scale dataset of two-photon imaging recordings of retinal bipolar cell responses to visual stimuli. This dataset provides a unique benchmark as it contains biological signal from well-defined cell types that is obscured by large inter-experimental variability. In a supervised setting, we compare the generalization performance of cell type classifiers across experiments, which we validate with anatomical cell type distributions from electron microscopy data. In an unsupervised setting, we remove inter-experimental variability from data which can then be fed into arbitrary downstream analyses. In both settings, we find that our method achieves the best trade-off between removing inter-experimental variability and preserving biological signal. Thus, we offer a flexible approach to remove inter-experimental variability and integrate datasets across experiments in systems neuroscience. Code available at https://github.com/eulerlab/rave.

neuroscience↗

bioRxiv2021

Center-surround interactions underlie bipolar cell motion sensing in the mouse retina

Motion is a critical aspect of vision. We studied the representation of motion in mouse retinal bipolar cells and found, surprisingly, that some bipolar cells possess motion-sensing capabilities that rely on their center-surround receptive fields. Using a glutamate sensor, we directly observed motion-sensitive bipolar cell synaptic output, which was strongest for local motion and dependent on the motions origin. We characterized bipolar cell receptive fields and found that there are motion and non-motion sensitive bipolar cell types, the majority being motion sensitive. Next, we used these bipolar cell receptive fields along with connectomics to design biophysical models of downstream cells. The models and experiments demonstrated that bipolar cells pass motion-sensitive excitation to starburst amacrine cells through direction-specific signals mediated by bipolar cells center-surround receptive field structure. As bipolar cells provide excitation to most amacrine and ganglion cells, their motion sensitivity may contribute to motion processing throughout the visual system.

neuroscience↗

bioRxiv2021

Minimal genetically encoded tags for fluorescent protein labeling in living neurons

Modern light microscopy, including super-resolution techniques, brought about a demand for small labeling tags that bring the fluorophore closer to the target. This challenge can be addressed by labeling unnatural amino acids (UAAs) with click chemistry. UAAs are site-specifically incorporated into a protein of interest by genetic code expansion. If the UAA carries a strained alkene or alkyne moiety it can be conjugated to a tetrazine-bearing fluorophore via a strain-promoted inverse-electron-demand Diels-Alder cycloaddition (SPIEDAC), a variant of bioorthogonal click chemistry. The minimal size of the incorporated tag and the possibility to couple the fluorophores directly to the protein of interest with single-residue precision make SPIEDAC live-cell labeling unique. However, until now, this type of labeling has not been used in complex, non-dividing cells, such as neurons. Using neurofilament light chain as a target protein, we established SPIEDAC labeling in living primary neurons and applied it for fixed-cell, live-cell, dual-color pulse--chase and super-resolution microscopy. We also show that SPIEDAC labeling can be combined with CRISPR/Cas9 genome engineering for tagging endogenous NFL. Due to its versatile nature and compatibility with advanced microscopy techniques, we anticipate that SPIEDAC labeling will contribute to novel discoveries in neurobiology.

neuroscience↗

bioRxiv2020

GNS561, a clinical-stage PPT1 inhibitor, has powerful antitumor activity against hepatocellular carcinoma via modulation of lysosomal functions

Background & AimsHepatocellular carcinoma (HCC) is the most frequent primary liver cancer. Autophagy inhibitors have been extensively studied in cancer but, to date, none has reached efficacy in clinical trials. Approach & ResultsTo explore the antitumor effects of GNS561, a new autophagy inhibitor, we first achieved in vitro assays using various human cancer cell lines. Having demonstrated that GNS561 displayed high liver tropism using mass spectrometry imaging, the potency of GNS561 on tumor was evaluated in vivo in two HCC models (human orthotopic patient-derived xenograft mouse model and diethylnitrosanime-induced cirrhotic immunocompetent rat model). Oral administration of GNS561 was well tolerated and decreased tumor growth in these two models. GNS561 mechanism of action was assessed in an HCC cell line, HepG2. We showed that due to its lysosomotropic properties, GNS561 could reach and inhibited its enzyme target, palmitoyl-protein thioesterase 1, resulting in lysosomal unbound Zn2+ accumulation, impairment of cathepsin activity, blockage of autophagic flux, altered location of mTOR, lysosomal membrane permeabilization, caspase activation and cell death. ConclusionsGNS561, currently tested in a global Phase 1b/2a clinical trial against primary liver cancer, represents a promising new drug candidate and a hopeful therapeutic strategy in cancer treatment. With an estimated 782,000 deaths in 2018, hepatocellular carcinoma (HCC) stands as the most common primary liver cancer and constitutes the fourth leading cause of cancer-related death worldwide (1). The rising incidence of HCC, the high worldwide mortality rate, and limited therapeutic options at advanced stages, make HCC a significant unmet medical need. Autophagy-related lysosomal cell death, either alone or in connection with several other cell death pathways, has been recognized as a major target for cancer therapy (2). Dysregulated autophagic-lysosomal activity and mTOR signaling were shown to allow cancer cells to become resistant to the cellular stress induced by chemotherapy and targeted therapy (3). Recently, several lysosome-specific inhibitors were shown to target palmitoyl-protein thioesterase 1 (PPT1), resulting in the modulation of protein palmitoylation and autophagy, and antitumor activity in melanoma and colon cancer models (4, 5). Chloroquine (CQ) and hydroxychloroquine (HCQ) have been used for more than 50 years to prevent and treat malarial infections and autoimmune diseases. Based on the lysosomotropic properties and the capacity for autophagy inhibition, these molecules have been proposed as active drugs in cancer (6-9). Over 40 clinical trials have been reported to evaluate the activity of both CQ or HCQ as single agent or in combination with chemotherapy in several tumor types (6-8. However, the required drug concentrations to inhibit autophagy were not achieved in humans, leading to inconsistent results in cancer clinical trials (5, 10). This prompted research to identify novel compounds with potent inhibitory properties against autophagy for cancer therapy. We previously reported that GNS561 was efficient in intrahepatic cholangiocarcinoma (iCCA) by inhibiting late-stage autophagy (11). In this study, we investigated the mechanism of action of GNS561. We identified lysosomal PPT1 as a target of GNS561. Exposure to GNS561 induced lysosomal accumulation of unbound zinc ion (Zn2+), inhibition of PPT1 and cathepsin activity, blockage of autophagic flux and mTOR displacement. Interestingly, these effects resulted in lysosomal membrane permeabilization (LMP) and caspase activation that led to cancer cell death. This mechanism was associated with dose-dependent inhibition of cancer cell proliferation and tumor growth inhibition in two HCC in vivo models. These data establish PPT1 and lysosomes as major targets for cancer cells and led to the development of a clinical program investigating the effects of GNS561 in patients with advanced HCC.

cancer biology↗

bioRxiv2020

Retinal mechanisms of saccadic suppression and their role in processing sequential stimuli

Visual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such suppression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find that sequential stimuli, such as those that naturally occur during saccades, trigger three independent suppressive mechanisms in the retina. The main suppressive mechanism is triggered by contrast-reversing sequential stimuli and originates within the receptive field center of ganglion cells. It does not involve inhibition or other known suppressive mechanisms such as saturation or adaptation. Instead, it relies on temporal filtering of the inherently slow response of cone photoreceptors coupled with downstream nonlinearities. Two further mechanisms of suppression are present predominantly in ON ganglion cells and originate in the receptive field surround, highlighting a novel disparity between ON and OFF ganglion cells. The mechanisms uncovered here likely play a role in shaping the retinal output following eye movements and other natural viewing conditions where sequential stimulation is ubiquitous.

neuroscience↗

bioRxiv2020

In Silico Driven Prediction of MAPK14 Off-Targets Reveals Unrelated Proteins with High Accuracy

During the discovery and development of new drugs, candidates with undesired and potentially harmful side-effects can arise at all stages, which poses significant scientific and economic risks. Most of such phenotypic side-effects can be attributed to binding of the drug candidate to unintended proteins, so-called off-targets. The early identification of potential off-targets is therefore of utmost importance to mitigate any downstream risks. We showcase how the combination of knowledge-based in silico off-target screening and state-of-the-art biophysics can be applied to rapidly identify off-targets for a MAPK14 inhibitor. Out of 13 predicted off-targets, six proteins were confirmed to interact with the inhibitor in vitro, which translates to an exceptional hit rate of 46%. For two proteins, affinities in the lower micromolar range were obtained: The kinase IRE1 and the Hematopoietic Prostaglandin D Synthase, which is entirely unrelated to MAPK14 and is involved in different cell-regulatory processes. The whole off-target identification/validation pipeline can be completed as fast as within two months, excluding delivery times of proteins. These results emphasize how computational off-target screening in combination with MicroScale Thermophoresis can effectively reduce downstream development risks in a very competitive time frame and at low cost.

bioinformatics↗

bioRxiv2020

Focus Your Screening Library: Rapid Identification of Novel PDE2 Inhibitors with in silico Driven Library Prioritization and MicroScale Thermophoresis

Accelerated development of lead structures is of high interest to the pharmaceutical industry in order to decrease development times and costs. We showcase how an intelligent combination of AI-based drug screening with state-of-the-art biophysics drives the rapid identification of novel inhibitor structures with high chemical diversity for cGMP-dependent 3,5-cyclic phosphodiesterase (PDE2). The starting point was an off-the-shelve chemical library of two million drug-like compounds. In a single in silico reduction step, we short-listed 125 compounds - the focused library - as potential binders to PDE2 and tested their binding behavior in vitro using MicroScale Thermophoresis (MST). Of this focused library, seven compounds indicated binding to PDE2, translating to a hit rate of 6%. Three of these compounds have affinities in the lower micromolar range. The compound with the highest affinity showed a KD of 10 {micro}M and is thus an excellent starting point for further medicinal chemistry optimization. The results show how innovative and structure-driven in silico approaches and biophysics can be used to accelerate drug discovery and to obtain new molecular scaffolds at a fraction of the costs and time - compared with standard high-throughput screening.

bioinformatics↗

bioRxiv2019

Identifying Novel Targets by using Drug-binding Site Signature: A Case Study of Kinase Inhibitors

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. We have developed "iDTPnd", a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive and a negative structural signature that captures the weakly conserved structural features of drug binding sites. To facilitate assessment of unintended targets iDTPnd also provides a docking-based interaction score and its statistical significance. We were able to confirm the interaction of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity and specificity of 52% and 55% respectively. We have validated 10 predicted novel targets, using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450 or MHC Class I molecules can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein-small molecule interactions, when sufficient drug-target 3D data are available.

bioinformatics↗

bioRxiv2019

Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling

In the outer plexiform layer (OPL) of the mouse retina, two types of cone photoreceptors (cones) provide input to more than a dozen types of cone bipolar cells (CBCs). This transmission is modulated by a single horizontal cell (HC) type, the only interneuron in the outer retina. Horizontal cells form feedback synapses with cones and feedforward synapses with CBCs. However, the exact computational role of HCs is still debated. Along with performing global signaling within their laterally coupled network, HCs also provide local, cone-specific feedback. Specifically, it has not been clear which synaptic structures HCs use to provide local feedback to cones and global forward signaling to CBCs.\n\nHere, we reconstructed in a serial block-face electron microscopy volume the dendritic trees of five HCs as well as cone axon terminals and CBC dendrites to quantitatively analyze their connectivity. In addition to the fine HC dendritic tips invaginating cone axon terminals, we also identified \"bulbs\", short segments of increased dendritic diameter on the primary dendrites of HCs. These bulbs are located well below the cone axon terminal base and make contact to other cells mostly identified as other HCs or CBCs. Using immunolabeling we show that HC bulbs express vesicular gamma-aminobutyric acid transporters and co-localize with GABA receptor {gamma}2 subunits. Together, this suggests the existence of two synaptic strata in the mouse OPL, spatially separating cone-specific feedback and feedforward signaling to CBCs. A biophysics-based computational model of a HC dendritic branch supports the hypothesis that the spatial arrangement of synaptic contacts allows simultaneous local feedback and global feedforward signaling.

neuroscience↗

bioRxiv2019

Neural circuits in the mouse retina support color vision in the upper visual field

Color vision is essential to the survival of most animals. Its neural basis lies in the retina, where chromatic signals from different photoreceptor types sensitive to distinct wavelengths are locally compared by neural circuits. Mice, like most mammals, are generally dichromatic and have two cone photoreceptor types. However, in the ventral retina most cones display the same spectral preference, impairing spectral comparisons necessary for color vision. This conflicts with behavioral evidence showing that mice can discriminate colors only in the corresponding upper visual field. Here, we systematically investigated the neural circuits underlying mouse color vision across three processing stages of the retina by recording the output of cones, bipolar and ganglion cells using two-photon imaging. Surprisingly, we found that across all retinal layers most color-opponent cells were located in the ventral retina. This started at the level of the cone output, where color-opponency was mediated by horizontal cells and likely involving rod photoreceptors. Next, bipolar cells relayed the chromatic information to ganglion cells in the inner retina, where type-specific, non-linear center-surround interactions resulted in specific color-opponent output channels to the brain. This suggests that neural circuits in the mouse retina are specifically tuned to extract color information from the upper visual field, aiding robust detection of aerial predators and ensuring the animals survival.

neuroscience↗

bioRxiv2019

The temporal structure of the inner retina at a single glance

The retina decomposes visual stimuli into parallel channels that encode different features of the visual environment. Central to this computation is the synaptic processing in a dense and thick layer of neuropil, the so-called inner plexiform layer (IPL). Here, different types of bipolar cells stratifying at distinct depths relay the excitatory feedforward drive from photoreceptors to amacrine and ganglion cells. Current experimental techniques for studying processing in the IPL do not allow imaging the entire IPL simultaneously in the intact tissue. Here, we extend a two-photon microscope with an electrically tunable lens allowing us to obtain optical vertical slices of the IPL, which provide a complete picture of the response diversity of bipolar cells at a \"single glance\". The nature of these axial recordings additionally allowed us to isolate and investigate batch effects, i.e. inter-experimental variations resulting in systematic differences in response speed. As a proof of principle, we developed a simple model that disentangles biological from experimental causes of variability, and allowed us to recover the characteristic gradient of response speeds across the IPL with higher precision than before. Our new framework will make it possible to study the computations performed in the central synaptic layer of the retina more efficiently.

neuroscience↗

bioRxiv2019

Systematic spatio-temporal mapping reveals divergent cell death pathways in three mouse models of hereditary retinal degeneration

Calcium (Ca2+) dysregulation has been linked to neuronal cell death, including in hereditary retinal degeneration. Ca2+ dysregulation is thought to cause rod and cone photoreceptor cell death. Spatial and temporal heterogeneities in retinal disease models have hampered validation of this hypothesis. We examined the role of Ca2+ in photoreceptor degeneration, assessing the activation pattern of Ca2+-dependent calpain proteases, generating spatio-temporal maps of the entire retina in the cpfl1 mouse model for primary cone degeneration, and in the rd1 and rd10 models for primary rod degeneration. We used Gaussian process models to distinguish the temporal sequences of degenerative molecular processes from other variability sources. In the rd1 and rd10 models, spatio-temporal pattern of increased calpain activity matched the progression of primary rod degeneration. High calpain activity coincided with activation of the calpain-2 isoform but not with calpain-1, suggesting differential roles for both calpain isoforms. Primary rod loss was linked to upregulation of apoptosis-inducing factor (AIF), although only a minute fraction of cells showed activity of the apoptotic marker caspase-3. After primary rod degeneration concluded, caspase-3 activation appeared in cones, suggesting apoptosis as the dominant mechanism for secondary cone loss. Gaussian process models highlighted calpain activity as a key event during primary rod photoreceptor cell death. Our data suggests a causal link between Ca2+ dysregulation and primary, non-apoptotic degeneration of photoreceptors and a role for apoptosis in secondary degeneration of cones, highlighting the importance of the spatial and temporal location of key molecular events, which may guide the evaluation of new therapies.

neuroscience↗