Whole-body integration of gene expression and single-cell morphology.

Animal bodies are composed of cell types with unique expression programs that implement their distinct locations, shapes, structures, and functions. Based on these properties, cell types assemble into specific tissues and organs. To systematically explore the link between cell-type-specific gene expression and morphology, we registered an expression atlas to a whole-body electron microscopy volume of the nereid Platynereis dumerilii. Automated segmentation of cells and nuclei identifies major cell classes and establishes a link between gene activation, chromatin topography, and nuclear size. Clustering of segmented cells according to gene expression reveals spatially coherent tissues. In the brain, genetically defined groups of neurons match ganglionic nuclei with coherent projections. Besides interneurons, we uncover sensory-neurosecretory cells in the nereid mushroom bodies, which thus qualify as sensory organs. They furthermore resemble the vertebrate telencephalon by molecular anatomy. We provide an integrated browser as a Fiji plugin for remote exploration of all available multimodal datasets.

Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish.

The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations.

A virtual reality system to analyze neural activity and behavior in adult zebrafish.

Virtual realities are powerful tools to analyze and manipulate interactions between animals and their environment and to enable measurements of neuronal activity during behavior. In many species, however, optical access to the brain and/or the behavioral repertoire are limited. We developed a high-resolution virtual reality for head-restrained adult zebrafish, which exhibit cognitive behaviors not shown by larvae. We noninvasively measured activity throughout the dorsal telencephalon by multiphoton calcium imaging. Fish in the virtual reality showed regular swimming patterns and were attracted to animations of conspecifics. Manipulations of visuo-motor feedback revealed neurons that responded selectively to the mismatch between the expected and the actual visual consequences of motor output. Such error signals were prominent in multiple telencephalic areas, consistent with models of predictive processing. A virtual reality system for adult zebrafish therefore provides opportunities to analyze neuronal processing mechanisms underlying higher brain functions including decision making, associative learning, and social interactions.

Neuronal computations in the olfactory system of zebrafish.

The main olfactory system encodes information about molecules in a combinatorial fashion by distributed spatiotemporal activity patterns. As activity propagates from sensory neurons to the olfactory bulb and to higher brain areas, odor information is processed by multiple transformations of these activity patterns. This review discusses neuronal computations associated with such transformations in the olfactory system of zebrafish, a small vertebrate that offers advantages for the quantitative analysis and manipulation of neuronal activity in the intact brain. The review focuses on pattern decorrelation in the olfactory bulb and on the readout of multiplexed sensory representations in the telencephalic area Dp, the homolog of the olfactory cortex. These computations are difficult to study in larger species and may provide insights into general information-processing strategies in the brain.

Amygdala interneuron subtypes control fear learning through disinhibition.

Learning is mediated by experience-dependent plasticity in neuronal circuits. Activity in neuronal circuits is tightly regulated by different subtypes of inhibitory interneurons, yet their role in learning is poorly understood. Using a combination of in vivo single-unit recordings and optogenetic manipulations, we show that in the mouse basolateral amygdala, interneurons expressing parvalbumin (PV) and somatostatin (SOM) bidirectionally control the acquisition of fear conditioning--a simple form of associative learning--through two distinct disinhibitory mechanisms. During an auditory cue, PV(+) interneurons are excited and indirectly disinhibit the dendrites of basolateral amygdala principal neurons via SOM(+) interneurons, thereby enhancing auditory responses and promoting cue-shock associations. During an aversive footshock, however, both PV(+) and SOM(+) interneurons are inhibited, which boosts postsynaptic footshock responses and gates learning. These results demonstrate that associative learning is dynamically regulated by the stimulus-specific activation of distinct disinhibitory microcircuits through precise interactions between different subtypes of local interneurons.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

A model for estimating the lifelong exposure to PM2.5 and NO2 and the application to population studies.

Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO2) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO2 for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts.

Lifelong exposure to multiple stressors through different environmental pathways for European populations.

Traditional exposure studies provide valuable insights for epidemiology, toxicology, and risk assessment. Throughout their lives, individuals are exposed to thousands of stressors in the environment which are not static, but influenced by environmental, temporal, spatial, and even socio-demographic factors. Existing exposure studies have usually focused on specific stressors for a constrained period of time. In response, the concept of the exposome has been raised, which is defined as the totality of exposure experienced from conception until death. The EU FP7-ENVIRONMENT research project HEALS was launched with the aim of incorporating a series of novel technologies, data analysis, and modelling tools to efficiently support exposome studies in Europe. The authors have developed a framework of modelling tools for estimating the long-term external exposure of selected population groups to multiple stressors through different pathways. As the starting point, the stressors, including electromagnetic fields (EMF) and ultraviolet light (UV) through dermal uptake, phthalates (DEHP, DIDP, and DINP) through inhalation, as well as chromium, mercury, and lead through food intake, have been selected. The simulation for multiple stressors has been realised by developing a probabilistic model that integrates the micro-environment approach, time-activity patterns, and a life course trajectory model. The methodology has been applied to a selected sample of subjects enrolled in the Italian Twin Registry (ITR). The results show that long-term exposures to multiple stressors are affected by factors including age, gender, geographical location, and education level. The methods developed in this paper extended the temporal and spatial scales of exposure modelling in Europe. Moreover, the application of our methods provided a novel approach and crucial input data for future work on environment-wide association studies.

Rapid olfactory discrimination learning in adult zebrafish.

The zebrafish is a model organism to study olfactory information processing, but efficient behavioral procedures to analyze olfactory discrimination and memory are lacking. We devised an automated odor discrimination task for adult zebrafish based on olfactory conditioning of feeding behavior. Presentation of a conditioned odor (CS+), but not a neutral odor (CS-) was followed by food delivery at a specific location. Fish developed differential behavioral responses to CS+ and CS- within a few trials. The behavioral response to the CS+ was complex and included components reminiscent of food search such as increased swimming speed and water surface sampling. Appetitive behavior was therefore quantified by a composite score that combined measurements of multiple behavioral parameters. Robust discrimination behavior was observed in different strains, even when odors were chemically similar, and learned preferences could overcome innate odor preferences. These results confirm that zebrafish can rapidly learn to make fine odor discriminations. The procedure is efficient and provides novel opportunities to dissect the neural mechanisms underlying olfactory discrimination and memory.

Neuronal filtering of multiplexed odour representations.

Neuronal activity patterns contain information in their temporal structure, indicating that information transfer between neurons may be optimized by temporal filtering. In the zebrafish olfactory bulb, subsets of output neurons (mitral cells) engage in synchronized oscillations during odour responses, but information about odour identity is contained mostly in non-oscillatory firing rate patterns. Using optogenetic manipulations and odour stimulation, we found that firing rate responses of neurons in the posterior zone of the dorsal telencephalon (Dp), a target area homologous to olfactory cortex, were largely insensitive to oscillatory synchrony of mitral cells because passive membrane properties and synaptic currents act as low-pass filters. Nevertheless, synchrony influenced spike timing. Moreover, Dp neurons responded primarily during the decorrelated steady state of mitral cell activity patterns. Temporal filtering therefore tunes Dp neurons to components of mitral cell activity patterns that are particularly informative about precise odour identity. These results demonstrate how temporal filtering can extract specific information from multiplexed neuronal codes.

Olfactory pattern classification by discrete neuronal network states.

The categorial nature of sensory, cognitive and behavioural acts indicates that the brain classifies neuronal activity patterns into discrete representations. Pattern classification may be achieved by abrupt switching between discrete activity states of neuronal circuits, but few experimental studies have directly tested this. We gradually varied the concentration or molecular identity of odours and optically measured responses across output neurons of the olfactory bulb in zebrafish. Whereas population activity patterns were largely insensitive to changes in odour concentration, morphing of one odour into another resulted in abrupt transitions between odour representations. These transitions were mediated by coordinated response changes among small neuronal ensembles rather than by shifts in the global network state. The olfactory bulb therefore classifies odour-evoked input patterns into many discrete and defined output patterns, as proposed by attractor models. This computation is consistent with perceptual phenomena and may represent a general information processing strategy in the brain.

Public health impacts of city policies to reduce climate change: findings from the URGENCHE EU-China project.

BACKGROUND: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments. METHODS: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys. RESULTS: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied. CONCLUSIONS: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries.

Universal Route to Polycyclic Aromatic Hydrocarbon Analysis in Foodstuff: Two-Dimensional Heart-Cut Liquid Chromatography-Gas Chromatography-Mass Spectrometry.

Analysis of polycyclic aromatic hydrocarbons (PAHs) in complex foodstuff is associated with complicated and work-intensive sample preparation. Chromatographic interference has to be faced in many situations. The scope of the current work was the development of a highly efficient two-dimensional heart-cut LC-LC-GC-MS method. Detection was performed with a time-of-flight mass spectrometer (TOF-MS) to allow for a comprehensive evaluation of the obtained data in terms of cleanup efficiency. Additionally, routine detection was performed with single quadrupole MS. An easy and quick generic sample preparation protocol was realized as a first step. During method development, focus was given to optimizing HPLC cleanup for complex foodstuff. Silica-, polymeric-, and carbon-based HPLC phases were tested. Coupling of silica gel to π-electron acceptor modified silica gel showed the best cleanup properties. A four rotary valve configuration allowed the usage of a single binary HPLC pump. Screening of several fatty and nonfatty food matrices showed the absence of unwanted matrix compounds in the cleaned-up PAH fraction down to the low picogram range using TOF-MS. Limits of quantitation (LOQ) were below 0.1 µg/kg for all EU priority PAHs. Recovery rates ranged from 82 to 111%. Validation data fully complied with EU Regulation 836/2011. Sample preparation was possible in 20 min. Interlacing of HPLC and GC allowed an average method runtime of 40 min per sample.

Molecular organization of neuronal cell types and neuromodulatory systems in the zebrafish telencephalon.

The function of neuronal networks is determined not only by synaptic connectivity but also by neuromodulatory systems that broadcast information via distributed connections and volume transmission. To understand the molecular constraints that organize neuromodulatory signaling in the telencephalon of adult zebrafish, we used transcriptomics and additional approaches to delineate cell types, to determine their phylogenetic conservation, and to map the expression of marker genes at high granularity. The combinatorial expression of GPCRs and cell-type markers indicates that all neuronal cell types are subject to modulation by multiple monoaminergic systems and distinct combinations of neuropeptides. Individual cell types were associated with multiple (typically >30) neuromodulatory signaling networks but expressed only a few diagnostic GPCRs at high levels, suggesting that different neuromodulatory systems act in combination, albeit with unequal weights. These results provide a detailed map of cell types and brain areas in the zebrafish telencephalon, identify core components of neuromodulatory networks, highlight the cell-type specificity of neuropeptides and GPCRs, and begin to decipher the logic of combinatorial neuromodulation.

Dopaminergic modulation of mitral cells and odor responses in the zebrafish olfactory bulb.

In the olfactory bulb, the modulatory neurotransmitter dopamine (DA) is coexpressed with GABA by local interneurons, but its role in odor processing remains obscure. We examined functions of DA mediated by D2-like receptors in the olfactory bulb of adult zebrafish by pharmacology, whole-cell recordings, calcium imaging, and optogenetics. Bath application of DA had no detectable effect on odorant-evoked sensory input. DA directly hyperpolarized mitral cells (MCs) via D2-like receptors and slightly increased their response gain. Consistent with this effect on input-output functions of MCs, small odorant responses were suppressed, whereas strong responses were enhanced in the presence of DA. These effects increased the root-mean-square contrast of population activity patterns but did not reduce their correlations. Optical stimulation of interneurons expressing channelrhodopsin-2 evoked fast GABAergic inhibitory currents in mitral cells but failed to activate D2 receptor-mediated currents when stimuli were short. Prolonged stimulus trains, however, activated a slow hyperpolarizing current that was blocked by an antagonist of D2-like receptors. GABA and DA are therefore both released from interneurons by electrical activity and hyperpolarize MCs, but D2-dependent dopaminergic effects occur on slower timescales. Additional effects of DA may be mediated by D1-like receptors. These results indicate that DA acts on D2-like receptors via asynchronous release and/or volume transmission and implicate DA in the slow adaptation of circuit function. The shift of the membrane potential away from spike threshold could adapt mitral cells to background input without compromising their sensitivity.

Illuminating vertebrate olfactory processing.

The olfactory system encodes information about molecules by spatiotemporal patterns of activity across distributed populations of neurons and extracts information from these patterns to control specific behaviors. Recent studies used in vivo recordings, optogenetics, and other methods to analyze the mechanisms by which odor information is encoded and processed in the olfactory system, the functional connectivity within and between olfactory brain areas, and the impact of spatiotemporal patterning of neuronal activity on higher-order neurons and behavioral outputs. The results give rise to a faceted picture of olfactory processing and provide insights into fundamental mechanisms underlying neuronal computations. This review focuses on some of this work presented in a Mini-Symposium at the Annual Meeting of the Society for Neuroscience in 2012.

Parameterization models for pesticide exposure via crop consumption.

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

Exposure of Individuals in Europe to Air Pollution and Related Health Effects.

Air pollutants, especially PM2.5 and NO2, are associated with adverse health impacts, as shown by numerous epidemiological studies. In these studies, the observed health impacts have been correlated with ambient concentrations, mainly taken from air pollution monitoring stations. However, individuals are harmed by the pollutants in the inhaled air at the places where they stay, and thus, the concentration of pollutants in the inhaled air is obviously a better indicator for health impacts than the ambient concentration at a monitoring station. Furthermore, the current method for estimating the occurrence of chronic diseases uses annual average concentrations as indicator. However, according to current hypotheses, chronic diseases, especially chronic mortality, develop through the exposure to pollutants over many years, maybe up to a full lifetime. Thus in this study, a methodology and a computer-aided probabilistic model system are described for calculating the exposure of a person to PM2.5 and NO2 over the whole lifetime where the person is characterized by attributes such as age, gender, place of residence and work as well as socioeconomic status. The model system contains a "life course trajectory model", which estimates the course of the education and professional development for the past lifetime of a person, whose present socioeconomic status is known. Furthermore, a "time-activity model" estimates at which places (so-called micro-environments) a person with a certain socioeconomic status stayed and how long he stayed there within a certain year. The concentrations of air pollutants in indoor environments are calculated with a "mass-balance model", the outdoor concentrations with "atmospheric models". Finally, the results of these models are combined to estimate the annual average exposure for the life years of individuals and population subgroups. The exposure is then used to estimate and monetize health impacts. The exposures and health impacts for a number of population subgroups in Europe are presented. For instance, a European citizen, who was 70 years old in 2015, has been exposed to around 25 µg/m3 of PM2.5 during his lifetime above the age of 30, which is associated with a reduction of life expectancy of 13.4 days per year of exposure above 30.

A viral toolbox for conditional and transneuronal gene expression in zebrafish.

The zebrafish is an important model in systems neuroscience but viral tools to dissect the structure and function of neuronal circuitry are not established. We developed methods for efficient gene transfer and retrograde tracing in adult and larval zebrafish by herpes simplex viruses (HSV1). HSV1 was combined with the Gal4/UAS system to target cell types with high spatial, temporal, and molecular specificity. We also established methods for efficient transneuronal tracing by modified rabies viruses in zebrafish. We demonstrate that HSV1 and rabies viruses can be used to visualize and manipulate genetically or anatomically identified neurons within and across different brain areas of adult and larval zebrafish. An expandable library of viruses is provided to express fluorescent proteins, calcium indicators, optogenetic probes, toxins and other molecular tools. This toolbox creates new opportunities to interrogate neuronal circuits in zebrafish through combinations of genetic and viral approaches.