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Interactions between cells and the extracellular matrix, mediated by integrin adhesion complexes, play key roles in fundamental cellular processes, including the sensing and transduction of mechanical cues. Here, we investigate systems-level changes in the integrin adhesome in patient-derived cutaneous squamous cell carcinoma cells and identify the actin regulatory protein Mena as a key node in the adhesion complex network. Mena is connected within a subnetwork of actin-binding proteins to the LINC complex component nesprin-2, with which it interacts and co-localises at the nuclear envelope. Moreover, Mena potentiates the interactions of nesprin-2 with the actin cytoskeleton and the nuclear lamina. CRISPR-mediated Mena depletion causes altered nuclear morphology, reduces tyrosine phosphorylation of the nuclear membrane protein emerin and downregulates expression of the immunomodulatory gene PTX3 via the recruitment of its enhancer to the nuclear periphery. We uncover an unexpected role for Mena at the nuclear membrane, where it controls nuclear architecture, chromatin repositioning and gene expression. Our findings identify an adhesion protein that regulates gene transcription via direct signalling across the nuclear envelope.

Monitoring the activity of mice within their home cage is proving to be a powerful tool for revealing subtle and early-onset phenotypes in mouse models. Video-tracking, in particular, lends itself to automated machine-learning technologies that have the potential to improve the manual annotations carried out by humans. This type of recording and analysis is particularly powerful in objective phenotyping, monitoring behaviors with no experimenter intervention. Automated home-cage testing allows the recording of non-evoked voluntary behaviors, which do not require any contact with the animal or exposure to specialist equipment. By avoiding stress deriving from handling, this approach, on the one hand, increases the welfare of experimental animals and, on the other hand, increases the reliability of results excluding confounding effects of stress on behavior. In this study, we show that the monitoring of climbing on the wire cage lid of a standard individually ventilated cage (IVC) yields reproducible data reflecting complex phenotypes of individual mouse inbred strains and of a widely used model of neurodegeneration, the N171-82Q mouse model of Huntington’s disease (HD). Measurements in the home-cage environment allowed for the collection of comprehensive motor activity data, which revealed sexual dimorphism, daily biphasic changes, and aging-related decrease in healthy C57BL/6J mice. Furthermore, home-cage recording of climbing allowed early detection of motor impairment in the N171-82Q HD mouse model. Integrating cage-floor activity with cage-lid activity (climbing) has the potential to greatly enhance the characterization of mouse strains, detecting early and subtle signs of disease and increasing reproducibility in preclinical studies.

Biological function in protein complexes emerges from more than just the sum of their parts: Molecules interact in a range of different subcomplexes and transfer signals/information around internal pathways. Modern proteomic techniques are excellent at producing a parts-list for such complexes, but more detailed analysis demands a network approach linking the molecules together and analyzing the emergent architectural properties. Methods developed for the analysis of networks in social sciences have proven very useful for splitting biological networks into communities leading to the discovery of sub-complexes enriched with molecules associated with specific diseases or molecular functions that are not apparent from the constituent components alone. Here we present the Bioconductor package BioNAR which supports step-by-step analysis of biological/biomedical networks with the aim of quantifying and ranking each of the network’s vertices based on network topology and clustering. Examples demonstrate that while BioNAR is not restricted to proteomic networks, it can predict a protein’s impact within multiple complexes, and enables estimation of the co-occurrence of meta-data, i.e., diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms. The package is available from Bioconductor release 3.16:https://bioconductor.org/packages/release/bioc/html/BioNAR.htmlAuthor BiographiesColin McLean holds a PhD in Experimental Particle Physics from the University of Edinburgh. He is currently a Senior Research Fellow in Health Economics and Data Science at the Institute for Genetics and Cancer at the University of Edinburgh. His research interests include applied network and data science in the biomedical domain.Anatoly Sorokin holds PhD Degree in Biophysics and is a Senior computational biologist in the Biological Systems Unit, Okinawa Institute of Science and Technology. His research interests include graph-based analysis, constraint-base, dynamics and rule-based modelling and application areas include systems biology, bioinformatics and microbiomics. Ian Simpson has a DPhil in Genetics (Oxford 2000) and is currently Director of the UKRI Centre for Doctoral Training in Biomedical Artificial Intelligence and a Reader in Biomedical Informatics in the School of Informatics at The University of Edinburgh. His research interests lie at the boundary between Informatics and Biomedicine and focus on jointly modelling molecular and clinical data to improve our understanding of genetic disease.J Douglas Armstrong holds a PhD in Molecular Genetics (Glasgow 1995) and is currently Professor of Systems Neurobiology at the School of Informatics at Edinburgh University. His research interests focus on structure/function mapping in the brains of model organisms. Oksana Sorokina holds a PhD in Systems Biology (Edinburgh 2010) and is a Senior Researcher at the School of Informatics at Edinburgh University. Her expertise is in the computational analysis of complex datasets primarily proteomics and the integration of genetic and other omic data types to understand molecular complexes at the systems biology level.

As a model organism,Drosophilais uniquely placed to contribute to our understanding of how brains control complex behavior. Not only does it have complex adaptive behaviors, but also a uniquely powerful genetic toolkit, increasingly complete dense connectomic maps of the central nervous system and a rapidly growing set of transcriptomic profiles of cell types. But this also poses a challenge: Given the massive amounts of available data, how are researchers to Find, Access, Integrate and Reuse (FAIR) relevant data in order to develop an integrated anatomical and molecular picture of circuits, inform hypothesis generation, and find reagents for experiments to test these hypotheses? The Virtual Fly Brain (virtualflybrain.org) web application & API provide a solution to this problem, using FAIR principles to integrate 3D images of neurons and brain regions, connectomics, transcriptomics and reagent expression data covering the whole CNS in both larva and adult. Users can search for neurons, neuroanatomy and reagents by name, location, or connectivity,viatext search, clicking on 3D images, search-by-image, and queries by type (e.g., dopaminergic neuron) or properties (e.g., synaptic input in the antennal lobe). Returned results include cross-registered 3D images that can be explored in linked 2D and 3D browsers or downloaded under open licenses, and extensive descriptions of cell types and regions curated from the literature. These solutions are potentially extensible to cover similar atlasing and data integration challenges in vertebrates.

The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the correct isoform onto which mutations should be mapped because there are several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task should be automatized. Here we present our code MoNvIso (Modelling eNvironment for Isoforms), which pinpoints the correct isoform associated with the mutation of interest and builds a structural model of both the wild type isoform and the related variants starting from the name of the gene and the list of mutations of interest.

Supplemental Digital Content is Available in the Text., Endometriosis (ENDO) and interstitial cystitis/bladder pain syndrome (IC/BPS) are chronic pain conditions for which better treatments are urgently needed. Development of new therapies with proven clinical benefit has been slow. We have conducted a review of existing preclinical in vivo models for ENDO and IC/BPS in rodents, discussed to what extent they replicate the phenotype and pain experience of patients, as well as their relevance for translational research. In 1009 publications detailing ENDO models, 41% used autologous, 26% syngeneic, 18% xenograft, and 11% allogeneic tissue in transplantation models. Intraperitoneal injection of endometrial tissue was the subcategory with the highest construct validity score for translational research. From 1055 IC/BPS publications, most interventions were bladder centric (85%), followed by complex mechanisms (8%) and stress-induced models (7%). Within these categories, the most frequently used models were instillation of irritants (92%), autoimmune (43%), and water avoidance stress (39%), respectively. Notably, although pelvic pain is a hallmark of both conditions and a key endpoint for development of novel therapies, only a small proportion of the studies (models of ENDO: 0.5%-12% and models of IC/BPS: 20%-44%) examined endpoints associated with pain. Moreover, only 2% and 3% of publications using models of ENDO and IC/BPS investigated nonevoked pain endpoints. This analysis highlights the wide variety of models used, limiting reproducibility and translation of results. We recommend refining models so that they better reflect clinical reality, sharing protocols, and using standardized endpoints to improve reproducibility. We are addressing this in our project Innovative Medicines Initiative-PainCare/Translational Research in Pelvic Pain.

Summary The neuronal synapse is underpinned by a large and diverse proteome but the molecular evidence is spread across many primary datasets. These data were recently curated into a single dataset describing a landscape of ∼8000 proteins found in studies of mammalian synapses. Here, we describe programmatic access to the dataset via the R/Bioconductor package Synaptome.db, which enables convenient and in-depth data analysis from within the Bioconductor environment. Synaptome.db allows users to obtain the respective gene information, e.g. subcellular localization, brain region, gene ontology, disease association and construct custom protein–protein interaction network models for gene sets and entire subcellular compartments. Availability and implementation The package Synaptome.db is part of Bioconductor since release 3.14, https://bioconductor.org/packages/release/data/annotation/html/synaptome.db.html, it is open source and available under the Artistic license 2.0. The development version is maintained on GitHub (https://github.com/lptolik/synaptome.db). Full documentation including examples is provided in the form of vignettes on the package webpage. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Interactions between cells and the extracellular matrix, mediated by integrin adhesion complexes (IACs), play key roles in cancer progression and metastasis. We investigated systems-level changes in the integrin adhesome during metastatic progression of a patient-derived cutaneous squamous cell carcinoma (cSCC), and found that the actin regulatory protein Mena is enriched in IACs in metastatic cSCC cells. Mena is connected within a subnetwork of actin-binding proteins to the LINC complex component nesprin-2, with which it interacts and co-localises at the nuclear envelope of metastatic cells. Moreover, Mena potentiates the interactions of nesprin-2 with the actin cytoskeleton and the nuclear lamina. CRISPR-mediated Mena depletion causes altered nuclear morphology, reduces tyrosine phosphorylation of the nuclear membrane protein emerin and downregulates expression of the immunomodulatory gene PTX3 via the recruitment of its enhancer to the nuclear periphery. We have uncovered an unexpected novel role for Mena at the nuclear membrane, where it controls the LINC complex, nuclear architecture, chromatin repositioning and cancer gene expression. This is the first description of an adhesion protein regulating gene transcription via direct signalling across the nuclear envelope.Abstract Figure

Genes encoding synaptic proteins are highly associated with neuronal disorders many of which show clinical co-morbidity. We integrated 58 published synaptic proteomic datasets that describe over 8000 proteins and combined them with direct protein-protein interactions and functional metadata to build a network resource that reveals the shared and unique protein components that underpin multiple disorders. All the data are provided in a flexible and accessible format to encourage custom use.

Genes encoding synaptic proteins are highly associated with neuronal disorders many of which show clinical co-morbidity. We integrated 58 published synaptic proteomic datasets that describe over 8000 proteins and combined them with direct protein–protein interactions and functional metadata to build a network resource that reveals the shared and unique protein components that underpin multiple disorders. All the data are provided in a flexible and accessible format to encourage custom use.

Synapses contain highly complex proteomes which control synaptic transmission, cognition and behaviour. Genes encoding synaptic proteins are associated with neuronal disorders many of which show clinical co-morbidity. Our hypothesis is that there is mechanistic overlap that is emergent from the network properties of the molecular complex. To test this requires a detailed and comprehensive molecular network model.We integrated 57 published synaptic proteomic datasets obtained between 2000 and 2019 that describe over 7000 proteins. The complexity of the postsynaptic proteome is reaching an asymptote with a core set of ~3000 proteins, with less data on the presynaptic terminal, where each new study reveals new components in its landscape. To complete the network, we added direct protein-protein interaction data and functional metadata including disease association.The resulting amalgamated molecular interaction network model is embedded into a SQLite database. The database is highly flexible allowing the widest range of queries to derive custom network models based on meta-data including species, disease association, synaptic compartment, brain region, and method of extraction.This network model enables us to perform in-depth analyses that dissect molecular pathways of multiple diseases revealing shared and unique protein components. We can clearly identify common and unique molecular profiles for co-morbid neurological disorders such as Schizophrenia and Bipolar Disorder and even disease comorbidities which span biological systems such as the intersection of Alzheimer’s Disease with Hypertension.

Background: Rodent behavioural assays are widely used to delineate the mechanisms of psychiatric disorders and predict the efficacy of drug candidates. Conventional behavioural paradigms are restricted to short time windows and involve transferring animals from the homecage to unfamiliar apparatus which induces stress. Additionally, factors including environmental perturbations, handling and the presence of an experimenter can impact behaviour and confound data interpretation. To improve welfare and reproducibility these issues must be resolved. Automated homecage monitoring offers a more ethologically relevant approach with reduced experimenter bias. Aim: To evaluate the effectiveness of an automated homecage system at detecting locomotor and social alterations induced by phencyclidine (PCP) in group-housed rats. PCP is an N-methyl-D-aspartate (NMDA) receptor antagonist commonly utilised to model aspects of schizophrenia. Methods: Rats housed in groups of three were implanted with radio frequency identification (RFID) tags. Each homecage was placed over a RFID reader baseplate for the automated monitoring of the social and locomotor activity of each individual rat. For all rats, we acquired homecage data for 24 h following administration of both saline and PCP (2.5 mg/kg). Results: PCP resulted in significantly increased distance travelled from 15 to 60 min post injection. Furthermore, PCP significantly enhanced time spent isolated from cage mates and this asociality occured from 60 to 105 min post treatment. Conclusions: Unlike conventional assays, in-cage monitoring captures the temporal duration of drug effects on multiple behaviours in the same group of animals. This approach could benefit psychiatric preclinical drug discovery through improved welfare and increased between-laboratory replicability.

Social impairment is frequently associated with mitochondrial dysfunction and altered neurotransmission. Although mitochondrial function is crucial for brain homeostasis, it remains unknown whether mitochondrial disruption contributes to social behavioral deficits. Here, we show that Drosophila mutants in the homolog of the human CYFIP1, a gene linked to autism and schizophrenia, exhibit mitochondrial hyperactivity and altered group behavior. We identify the regulation of GABA availability by mitochondrial activity as a biologically relevant mechanism and demonstrate its contribution to social behavior. Specifically, increased mitochondrial activity causes gamma aminobutyric acid (GABA) sequestration in the mitochondria, reducing GABAergic signaling and resulting in social deficits. Pharmacological and genetic manipulation of mitochondrial activity or GABA signaling corrects the observed abnormalities. We identify Aralar as the mitochondrial transporter that sequesters GABA upon increased mitochondrial activity. This study increases our understanding of how mitochondria modulate neuronal homeostasis and social behavior under physiopathological conditions. ispartof: CELL vol:180 issue:6 pages:1178-+ ispartof: location:United States status: published

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

Background The ActualHCA™ system continuously monitors the activity, temperature and behavior of group-housed rats without invasive surgery. The system was validated to detect the contrasting effects of sedative and stimulant test agents (chlorpromazine, clonidine and amphetamine), and compared with the modified Irwin test (mIT) with rectal temperature measurements. Methods Six male Han Wistar rats per group were used to assess each test agent and vehicle controls in separate ActualHCA™ recordings and mIT. The mIT was undertaken at 15, 30 mins, 1, 2, 4 and 24 h post-dose. ActualHCA™ recorded continuously for 24 h post-dose under 3 experimental conditions: dosed during light phase, dark phase, and light phase with a scheduled cage change at the time of peak effects determined by mIT. Results ActualHCA™ detected an increase stimulated activity from the cage change at 1-2 h post-dose which was obliterated by chlorpromazine and clonidine. Amphetamine increased activity up to 4 h post-dose in all conditions. Temperature from ActualHCA™ was affected by all test agents in all conditions. The mIT showed effects on all 3 test agents up to 4 h post-dose, with maximal effects at 1-2 h post-dose. The maximal effects on temperature from ActualHCA™ differed from mIT. Delayed effects on activity were detected by ActualHCA™, but not on mIT. Conclusions Continuous monitoring has the advantage of capturing effects over time that may be missed with manual tests using pre-determined time points. This automated behavioural system does not replace the need for conventional methods but could be implemented simultaneously to improve our understanding of behavioural pharmacology.

Highlights • Automated assessment of mouse home-cage behaviour is robust and reliable. • Analysis over multiple light/dark cycles improves ability to classify behaviours. • Combined RFID and video analysis enables home-cage analysis in group housed animals., An important factor in reducing variability in mouse test outcomes has been to develop assays that can be used for continuous automated home cage assessment. Our experience has shown that this has been most evidenced in long-term assessment of wheel-running activity in mice. Historically, wheel-running in mice and other rodents have been used as a robust assay to determine, with precision, the inherent period of circadian rhythms in mice. Furthermore, this assay has been instrumental in dissecting the molecular genetic basis of mammalian circadian rhythms. In teasing out the elements of this test that have determined its robustness – automated assessment of an unforced behaviour in the home cage over long time intervals – we and others have been investigating whether similar test apparatus could be used to accurately discriminate differences in distinct behavioural parameters in mice. Firstly, using these systems, we explored behaviours in a number of mouse inbred strains to determine whether we could extract biologically meaningful differences. Secondly, we tested a number of relevant mutant lines to determine how discriminative these parameters were. Our findings show that, when compared to conventional out-of-cage phenotyping, a far deeper understanding of mouse mutant phenotype can be established by monitoring behaviour in the home cage over one or more light:dark cycles.

Summary Arc is an activity-regulated neuronal protein, but little is known about its interactions, assembly into multiprotein complexes, and role in human disease and cognition. We applied an integrated proteomic and genetic strategy by targeting a tandem affinity purification (TAP) tag and Venus fluorescent protein into the endogenous Arc gene in mice. This allowed biochemical and proteomic characterization of native complexes in wild-type and knockout mice. We identified many Arc-interacting proteins, of which PSD95 was the most abundant. PSD95 was essential for Arc assembly into 1.5-MDa complexes and activity-dependent recruitment to excitatory synapses. Integrating human genetic data with proteomic data showed that Arc-PSD95 complexes are enriched in schizophrenia, intellectual disability, autism, and epilepsy mutations and normal variants in intelligence. We propose that Arc-PSD95 postsynaptic complexes potentially affect human cognitive function., Graphical Abstract, Highlights • TAP tag and purification of endogenous Arc protein complexes from the mouse brain • PSD95 is the major Arc binding protein, and both assemble into 1.5-MDa supercomplexes • PSD95 is essential for recruitment of Arc to synapses • Mutations and genetic variants in Arc-PSD95 are linked to cognition, Fernández et al. use genetics and proteomics to study the Arc protein in the mouse brain. PSD95 recruits Arc to the synapse and assembles it into signaling complexes with neurotransmitter receptors and other proteins. Arc-PSD95 supercomplexes contain genetic variants previously linked to epilepsy, schizophrenia, intellectual disability, and IQ.

The p140Cap adaptor protein is a scaffold molecule physiologically expressed in few epithelial tissues, such as the mammary gland, and in differentiated neurons. While the role of p140Cap in mammary gland epithelia is not still understood, we already know that a significant subset of breast cancers express p140Cap. In the subgroup of ERBB2-amplified breast cancers, a high p140Cap status predicts a significantly lower probability of developing a distant event and a clear difference in survival. p140Cap is causal in dampening ERBB2-positive tumor cell progression, impairing tumor onset and growth, and counteracting epithelial mesenchymal transition, resulting in decreased metastasis formation. Since only a few p140Cap interacting proteins have been identified in breast cancer and the molecular complexes and pathways underlying the cancer function of p140Cap are largely unknown, we generated a p140Cap interactome from ERBB2-positive breast cancer cells, identifying cancer specific components and those shared with the synaptic interactome. We identified 373 interacting proteins in cancer cells, including those with functions relevant to cell adhesion, protein homeostasis, regulation of cell cycle and apoptosis, which are frequently deregulated in cancer. Within the interactome, we identified 15 communities (clusters) with topology-functional relationships. In neurons, where p140Cap is key in regulating synaptogenesis, synaptic transmission and synaptic plasticity, it establishes an extensive interactome with proteins that cluster to sub complexes located in the postsynaptic density. p140Cap interactors converge on key synaptic processes, including synaptic transmission, actin cytoskeleton remodeling and cell-cell junction organization. Comparing the breast cancer to the synaptic interactome, we found 39 overlapping proteins, a relatively small overlap. However, cell adhesion and remodeling of actin cytoskeleton clearly emerge as common terms in the shared subset. Thus, the functional signature of the two interactomes is primarily determined by organ/tissue and functional specificity, while the overlap provides a list of shared functional terms, which might be linked to both cancer and neurological functions.

Background Neurotrauma patients face major neurological sequelae. The failure in the preclinical-to-clinical translation of candidate therapies could be due to poor evaluation of rodent behaviours after neurotrauma. New Method A home cage automated system was used to study the long term behaviour of individual rats with traumatic brain injury (TBI), spinal cord injury (SCI) and non-CNS injured controls, whilst group-housed in their home cages. Naive rats were used as baseline controls. Automated locomotor activity and body temperature recordings were carried out 24 h /day for 3 days/week during 12 weeks post-injury. Behavioural patterns, including aggression, rearing, grooming, feeding and drinking were analysed from automated video recordings during week 1, 6 and 12. Results SCI animals showed a lower locomotor activity compared to TBI or control animals during light and dark phases. TBI animals showed a higher aggression during the dark phase in the first week post-injury compared to SCI or control animals. Individual grooming and rearing were reduced in SCI animals compared to TBI and control animals in the first week post-injury during the dark phase. No differences in drinking or feeding were detected between groups. Locomotor activity did not differ between naive male and female rats, but body temperature differ between light and dark phases for both. Standard methods Injury severity was compared to standard SCI and TBI behaviour scores (BBB and mNSS, respectively) and histological analysis. Conclusions This study demonstrates the practical benefits of using a non-intrusive automated home cage recording system to observe long term individual behaviour of group-housed SCI and TBI rats.

RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.The RKappa software is an open-source (GLP3 license) package for R, which is freely available online ( https://github.com/lptolik/R4Kappa ).

RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.The RKappa software is an open-source (GLP3 license) package for R, which is freely available online ( https://github.com/lptolik/R4Kappa ).

The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry. Seventy-four percent of proteins showed differential expression and each region displayed a unique compositional signature. These signatures correlated with the anatomical divisions of the brain and their embryological origins. Biochemical pathways controlling plasticity and disease, protein interaction networks and individual proteins involved with cognition all showed differential regional expression. Combining proteomic and connectomic data shows that interconnected regions have specific proteome signatures. Diversity in synapse proteome composition is key feature of mouse and human brain structure., Support was obtained from the Medical Research Council (G0802238), European Union Seventh Framework Programme (FP7 grant agreement No. 604102) and Horizon 2020 (grant agreement No. 72027). We thank T. Le Bihan and L. Imrie at SynthSys, University of Edinburgh, for mass spectrometry sample analysis. The LC-MS QExactive equipment was purchased by a Wellcome Trust Institutional Strategic Support Fund and a strategic award from the Wellcome Trust for the Centre for Immunity, Infection and Evolution (095831/Z/11/Z). Data were extracted from Neuroimaging Informatics Technology Initiative (NIFTI) files using a custom automated script written by J. Roy, MEMEX, Inc. (Burlington, Ontario, Canada). We thank K. Elsegood for laboratory management and D. Maizels for artwork; C.S. Davey, editing.

Adult zebrafish, in contrast to mammals, regenerate neurons in their brain, but the extent and variability of this capacity is unclear. Here we ask whether the loss of various dopaminergic neuron populations is sufficient to trigger their functional regeneration. Both sexes of zebrafish were analyzed. Genetic lineage tracing shows that specific diencephalic ependymo-radial glial (ERG) progenitor cells give rise to new dopaminergic [tyrosine hydroxylase-positive (TH(+))] neurons. Ablation elicits an immune response, increased proliferation of ERG progenitor cells, and increased addition of new TH(+) neurons in populations that constitutively add new neurons (e.g., diencephalic population 5/6). Inhibiting the immune response attenuates neurogenesis to control levels. Boosting the immune response enhances ERG proliferation, but not addition of TH(+) neurons. In contrast, in populations in which constitutive neurogenesis is undetectable (e.g., the posterior tuberculum and locus ceruleus), cell replacement and tissue integration are incomplete and transient. This is associated with a loss of spinal TH(+) axons, as well as permanent deficits in shoaling and reproductive behavior. Hence, dopaminergic neuron populations in the adult zebrafish brain show vast differences in regenerative capacity that correlate with constitutive addition of neurons and depend on immune system activation. SIGNIFICANCE STATEMENT Despite the fact that zebrafish show a high propensity to regenerate neurons in the brain, this study reveals that not all types of dopaminergic neurons are functionally regenerated after specific ablation. Hence, in the same adult vertebrate brain, mechanisms of successful and incomplete regeneration can be studied. We identify progenitor cells for dopaminergic neurons and show that activating the immune system promotes the proliferation of these cells. However, in some areas of the brain this only leads to insufficient replacement of functionally important dopaminergic neurons that later disappear. Understanding the mechanisms of regeneration in zebrafish may inform interventions targeting the regeneration of functionally important neurons, such as dopaminergic neurons, from endogenous progenitor cells in nonregenerating mammals.

Polymerisation of clathrin is a key process that underlies clathrin-mediated endocytosis. Clathrin-coated vesicles are responsible for cell internalization of external substances required for normal homeostasis and life –sustaining activity. There are several hypotheses describing formation of closed clathrin structures. According to one of the proposed mechanisms cage formation may start from a flat lattice buildup on the cellular membrane, which is later transformed into a curved structure. Creation of the curved surface requires rearrangement of the lattice, induced by additional molecular mechanisms. Different potential mechanisms require a modeling framework that can be easily modified to compare between them. We created an extendable rule-based model that describes polymerisation of clathrin molecules and various scenarios of cage formation. Using Global Sensitivity Analysis (GSA) we obtained parameter sets describing clathrin pentagon closure and the emergence/production and closure of large-size clathrin cages/vesicles. We were able to demonstrate that the model can reproduce budding of the clathrin cage from an initial flat array.