The Hybrid Drive: a chronic implant device combining tetrode arrays with silicon probes for layer-resolved ensemble electrophysiology in freely moving mice.

Objective. Understanding the function of brain cortices requires simultaneous investigation at multiple spatial and temporal scales and to link neural activity to an animal's behavior. A major challenge is to measure within- and across-layer information in actively behaving animals, in particular in mice that have become a major species in neuroscience due to an extensive genetic toolkit. Here we describe the Hybrid Drive, a new chronic implant for mice that combines tetrode arrays to record within-layer information with silicon probes to simultaneously measure across-layer information.Approach. The design of our device combines up to 14 tetrodes and 2 silicon probes, that can be arranged in custom arrays to generate unique areas-specific (and multi-area) layouts.Main results. We show that large numbers of neurons and layer-resolved local field potentials can be recorded from the same brain region across weeks without loss in electrophysiological signal quality. The drive's lightweight structure (≈3.5 g) leaves animal behavior largely unchanged, compared to other tetrode drives, during a variety of experimental paradigms. We demonstrate how the data collected with the Hybrid Drive allow state-of-the-art analysis in a series of experiments linking the spiking activity of CA1 pyramidal layer neurons to the oscillatory activity across hippocampal layers.Significance. Our new device fits a gap in the existing technology and increases the range and precision of questions that can be addressed about neural computations in freely behaving mice.

Mouse visual cortex contains a region of enhanced spatial resolution.

The representation of space in mouse visual cortex was thought to be relatively uniform. Here we reveal, using population receptive-field (pRF) mapping techniques, that mouse visual cortex contains a region in which pRFs are considerably smaller. This region, the "focea," represents a location in space in front of, and slightly above, the mouse. Using two-photon imaging we show that the smaller pRFs are due to lower scatter of receptive-fields at the focea and an over-representation of binocular regions of space. We show that receptive-fields of single-neurons in areas LM and AL are smaller at the focea and that mice have improved visual resolution in this region of space. Furthermore, freely moving mice make compensatory eye-movements to hold this region in front of them. Our results indicate that mice have spatial biases in their visual processing, a finding that has important implications for the use of the mouse model of vision.

Vision: Depth perception in climbing mice.

Depth perception helps animals interact with a three-dimensional world. A new study presents a novel paradigm for studying depth perception in naturally climbing mice and links their behavior to binocular disparity signals in primary visual cortical neurons.

Two Distinct Types of Eye-Head Coupling in Freely Moving Mice.

Animals actively interact with their environment to gather sensory information. There is conflicting evidence about how mice use vision to sample their environment. During head restraint, mice make rapid eye movements coupled between the eyes, similar to conjugate saccadic eye movements in humans. However, when mice are free to move their heads, eye movements are more complex and often non-conjugate, with the eyes moving in opposite directions. We combined head and eye tracking in freely moving mice and found both observations are explained by two eye-head coupling types, associated with vestibular mechanisms. The first type comprised non-conjugate eye movements, which compensate for head tilt changes to maintain a similar visual field relative to the horizontal ground plane. The second type of eye movements was conjugate and coupled to head yaw rotation to produce a "saccade and fixate" gaze pattern. During head-initiated saccades, the eyes moved together in the head direction but during subsequent fixation moved in the opposite direction to the head to compensate for head rotation. This saccade and fixate pattern is similar to humans who use eye movements (with or without head movement) to rapidly shift gaze but in mice relies on combined head and eye movements. Both couplings were maintained during social interactions and visually guided object tracking. Even in head-restrained mice, eye movements were invariably associated with attempted head motion. Our results reveal that mice combine head and eye movements to sample their environment and highlight similarities and differences between eye movements in mice and humans.

A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice.

Breakthroughs in understanding the neural basis of natural behavior require neural recording and intervention to be paired with high-fidelity multimodal behavioral monitoring. An extensive genetic toolkit for neural circuit dissection, and well-developed neural recording technology, make the mouse a powerful model organism for systems neuroscience. However, most methods for high-bandwidth acquisition of behavioral data in mice rely upon fixed-position cameras and other off-animal devices, complicating the monitoring of animals freely engaged in natural behaviors. Here, we report the development of a lightweight head-mounted camera system combined with head-movement sensors to simultaneously monitor eye position, pupil dilation, whisking, and pinna movements along with head motion in unrestrained, freely behaving mice. The power of the combined technology is demonstrated by observations linking eye position to head orientation; whisking to non-tactile stimulation; and, in electrophysiological experiments, visual cortical activity to volitional head movements.

Growing Protein Crystals with Distinct Dimensions Using Automated Crystallization Coupled with In Situ Dynamic Light Scattering.

The automated crystallization device is a patented technique1 especially developed for monitoring protein crystallization experiments with the aim to precisely maneuver the nucleation and crystal growth towards desired sizes of protein crystals. The controlled crystallization is based on sample investigation with in situ Dynamic Light Scattering (DLS) while all visual changes in the droplet are monitored online with the help of a microscope coupled to a CCD camera, thus enabling a full investigation of the protein droplet during all stages of crystallization. The use of in situ DLS measurements throughout the entire experiment allows a precise identification of the highly supersaturated protein solution transitioning to a new phase - the formation of crystal nuclei. By identifying the protein nucleation stage, the crystallization can be optimized from large protein crystals to the production of protein microcrystals. The experimental protocol shows an interactive crystallization approach based on precise automated steps such as precipitant addition, water evaporation for inducing high supersaturation, and sample dilution for slowing induced homogeneous nucleation or reversing phase transitions.

The fine art of integral membrane protein crystallisation.

Integral membrane proteins are among the most fascinating and important biomolecules as they play a vital role in many biological functions. Knowledge of their atomic structures is fundamental to the understanding of their biochemical function and key in many drug discovery programs. However, over the years, structure determination of integral membrane proteins has proven to be far from trivial, hence they are underrepresented in the protein data bank. Low expression levels, insolubility and instability are just a few of the many hurdles one faces when studying these proteins. X-ray crystallography has been the most used method to determine atomic structures of membrane proteins. However, the production of high quality membrane protein crystals is always very challenging, often seen more as art than a rational experiment. Here we review valuable approaches, methods and techniques to successful membrane protein crystallisation.

Absence of 11-keto reduction of cortisone and 11-ketotestosterone in the model organism zebrafish.

Zebrafish are widely used as model organism. Their suitability for endocrine studies, drug screening and toxicity assessements depends on the extent of conservation of specific genes and biochemical pathways between zebrafish and human. Glucocorticoids consist of inactive 11-keto (cortisone and 11-dehydrocorticosterone) and active 11ß-hydroxyl forms (cortisol and corticosterone). In mammals, two 11ß-hydroxysteroid dehydrogenases (11ß-HSD1 and 11ß-HSD2) interconvert active and inactive glucocorticoids, allowing tissue-specific regulation of glucocorticoid action. Furthermore, 11ß-HSDs are involved in the metabolism of 11-oxy androgens. As zebrafish and other teleost fish lack a direct homologue of 11ß-HSD1, we investigated whether they can reduce 11-ketosteroids. We compared glucocorticoid and androgen metabolism between human and zebrafish using recombinant enzymes, microsomal preparations and zebrafish larvae. Our results provide strong evidence for the absence of 11-ketosteroid reduction in zebrafish. Neither human 11ß-HSD3 nor the two zebrafish 11ß-HSD3 homologues, previously hypothesized to reduce 11-ketosteroids, converted cortisone and 11-ketotestosterone (11KT) to their 11ß-hydroxyl forms. Furthermore, zebrafish microsomes were unable to reduce 11-ketosteroids, and exposure of larvae to cortisone or the synthetic analogue prednisone did not affect glucocorticoid-dependent gene expression. Additionally, a dual-role of 11ß-HSD2 by inactivating glucocorticoids and generating the main fish androgen 11KT was supported. Thus, due to the lack of 11-ketosteroid reduction, zebrafish and other teleost fish exhibit a limited tissue-specific regulation of glucocorticoid action, and their androgen production pathway is characterized by sustained 11KT production. These findings are of particular significance when using zebrafish as a model to study endocrine functions, stress responses and effects of pharmaceuticals.

Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation.

Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far-ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or "priors." In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available.

Fast and robust estimation of spectro-temporal receptive fields using stochastic approximations.

BACKGROUND: The receptive field (RF) represents the signal preferences of sensory neurons and is the primary analysis method for understanding sensory coding. While it is essential to estimate a neuron's RF, finding numerical solutions to increasingly complex RF models can become computationally intensive, in particular for high-dimensional stimuli or when many neurons are involved. NEW METHOD: Here we propose an optimization scheme based on stochastic approximations that facilitate this task. The basic idea is to derive solutions on a random subset rather than computing the full solution on the available data set. To test this, we applied different optimization schemes based on stochastic gradient descent (SGD) to both the generalized linear model (GLM) and a recently developed classification-based RF estimation approach. RESULTS AND COMPARISON WITH EXISTING METHOD: Using simulated and recorded responses, we demonstrate that RF parameter optimization based on state-of-the-art SGD algorithms produces robust estimates of the spectro-temporal receptive field (STRF). Results on recordings from the auditory midbrain demonstrate that stochastic approximations preserve both predictive power and tuning properties of STRFs. A correlation of 0.93 with the STRF derived from the full solution may be obtained in less than 10% of the full solution's estimation time. We also present an on-line algorithm that allows simultaneous monitoring of STRF properties of more than 30 neurons on a single computer. CONCLUSIONS: The proposed approach may not only prove helpful for large-scale recordings but also provides a more comprehensive characterization of neural tuning in experiments than standard tuning curves.

Latest methods of fluorescence-based protein crystal identification.

Successful protein crystallization screening experiments are dependent upon the experimenter being able to identify positive outcomes. The introduction of fluorescence techniques has brought a powerful and versatile tool to the aid of the crystal grower. Trace fluorescent labeling, in which a fluorescent probe is covalently bound to a subpopulation (<0.5%) of the protein, enables the use of visible fluorescence. Alternatively, one can avoid covalent modification and use UV fluorescence, exploiting the intrinsic fluorescent amino acids present in most proteins. By the use of these techniques, crystals that had previously been obscured in the crystallization drop can readily be identified and distinguished from amorphous precipitate or salt crystals. Additionally, lead conditions that may not have been obvious as such under white-light illumination can be identified. In all cases review of the screening plate is considerably accelerated, as the eye can quickly note objects of increased intensity.

Systematic analysis of protein-detergent complexes applying dynamic light scattering to optimize solutions for crystallization trials.

Detergents are widely used for the isolation and solubilization of membrane proteins to support crystallization and structure determination. Detergents are amphiphilic molecules that form micelles once the characteristic critical micelle concentration (CMC) is achieved and can solubilize membrane proteins by the formation of micelles around them. The results are presented of a study of micelle formation observed by in situ dynamic light-scattering (DLS) analyses performed on selected detergent solutions using a newly designed advanced hardware device. DLS was initially applied in situ to detergent samples with a total volume of approximately 2 µl. When measured with DLS, pure detergents show a monodisperse radial distribution in water at concentrations exceeding the CMC. A series of all-trans n-alkyl-ß-D-maltopyranosides, from n-hexyl to n-tetradecyl, were used in the investigations. The results obtained verify that the application of DLS in situ is capable of distinguishing differences in the hydrodynamic radii of micelles formed by detergents differing in length by only a single CH2 group in their aliphatic tails. Subsequently, DLS was applied to investigate the distribution of hydrodynamic radii of membrane proteins and selected water-insoluble proteins in presence of detergent micelles. The results confirm that stable protein-detergent complexes were prepared for (i) bacteriorhodopsin and (ii) FetA in complex with a ligand as examples of transmembrane proteins. A fusion of maltose-binding protein and the Duck hepatitis B virus X protein was added to this investigation as an example of a non-membrane-associated protein with low water solubility. The increased solubility of this protein in the presence of detergent could be monitored, as well as the progress of proteolytic cleavage to separate the fusion partners. This study demonstrates the potential of in situ DLS to optimize solutions of protein-detergent complexes for crystallization applications.

Ligand-based pharmacophore modeling and virtual screening for the discovery of novel 17ß-hydroxysteroid dehydrogenase 2 inhibitors.

17ß-Hydroxysteroid dehydrogenase 2 (17ß-HSD2) catalyzes the inactivation of estradiol into estrone. This enzyme is expressed only in a few tissues, and therefore its inhibition is considered as a treatment option for osteoporosis to ameliorate estrogen deficiency. In this study, ligand-based pharmacophore models for 17ß-HSD2 inhibitors were constructed and employed for virtual screening. From the virtual screening hits, 29 substances were evaluated in vitro for 17ß-HSD2 inhibition. Seven compounds inhibited 17ß-HSD2 with low micromolar IC50 values. To investigate structure-activity relationships (SAR), 30 more derivatives of the original hits were tested. The three most potent hits, 12, 22, and 15, had IC50 values of 240 nM, 1 µM, and 1.5 µM, respectively. All but 1 of the 13 identified inhibitors were selective over 17ß-HSD1, the enzyme catalyzing conversion of estrone into estradiol. Three of the new, small, synthetic 17ß-HSD2 inhibitors showed acceptable selectivity over other related HSDs, and six of them did not affect other HSDs.

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.

Preliminary crystallographic analysis of a cruciferin protein from seeds of Moringa oleifera.

A 55 kDa cruciferin protein has been purified and characterized from seeds of Moringa oleifera plant. Protein blast of N-terminal amino-acid sequence showed 60 % sequence similarity with cruciferin from Brassica napus. The M. oleifera protein has been crystallized applying the sitting drop method using 5 % polyethylene glycol 8,000, 38.5 % 3-methyl-1,5-pentanediol and 0.1 M sodium cacodylate pH 6.5. The crystals belonged to the P6322 hexagonal space group with cell dimensions, a = b = 98.4, c = 274.3 Å. Initial diffraction data have been collected to a resolution of 6 Å.

Temporal variability of spectro-temporal receptive fields in the anesthetized auditory cortex.

Temporal variability of neuronal response characteristics during sensory stimulation is a ubiquitous phenomenon that may reflect processes such as stimulus-driven adaptation, top-down modulation or spontaneous fluctuations. It poses a challenge to functional characterization methods such as the receptive field, since these often assume stationarity. We propose a novel method for estimation of sensory neurons' receptive fields that extends the classic static linear receptive field model to the time-varying case. Here, the long-term estimate of the static receptive field serves as the mean of a probabilistic prior distribution from which the short-term temporally localized receptive field may deviate stochastically with time-varying standard deviation. The derived corresponding generalized linear model permits robust characterization of temporal variability in receptive field structure also for highly non-Gaussian stimulus ensembles. We computed and analyzed short-term auditory spectro-temporal receptive field (STRF) estimates with characteristic temporal resolution 5-30 s based on model simulations and responses from in total 60 single-unit recordings in anesthetized Mongolian gerbil auditory midbrain and cortex. Stimulation was performed with short (100 ms) overlapping frequency-modulated tones. Results demonstrate identification of time-varying STRFs, with obtained predictive model likelihoods exceeding those from baseline static STRF estimation. Quantitative characterization of STRF variability reveals a higher degree thereof in auditory cortex compared to midbrain. Cluster analysis indicates that significant deviations from the long-term static STRF are brief, but reliably estimated. We hypothesize that the observed variability more likely reflects spontaneous or state-dependent internal fluctuations that interact with stimulus-induced processing, rather than experimental or stimulus design.

Formation of threohydrobupropion from bupropion is dependent on 11ß-hydroxysteroid dehydrogenase 1.

Bupropion is widely used for treatment of depression and as a smoking-cessation drug. Despite more than 20 years of therapeutic use, its metabolism is not fully understood. While CYP2B6 is known to form hydroxybupropion, the enzyme(s) generating erythro- and threohydrobupropion have long remained unclear. Previous experiments using microsomal preparations and the nonspecific inhibitor glycyrrhetinic acid suggested a role for 11ß-hydroxysteroid dehydrogenase 1 (11ß-HSD1) in the formation of both erythro- and threohydrobupropion. 11ß-HSD1 catalyzes the conversion of inactive glucocorticoids (cortisone, prednisone) to their active forms (cortisol, prednisolone). Moreover, it accepts several other substrates. Here, we used for the first time recombinant 11ß-HSD1 to assess its role in the carbonyl reduction of bupropion. Furthermore, we applied human, rat, and mouse liver microsomes and a selective inhibitor to characterize species-specific differences and to estimate the relative contribution of 11ß-HSD1 to bupropion metabolism. The results revealed 11ß-HSD1 as the major enzyme responsible for threohydrobupropion formation. The reaction was stereoselective and no erythrohydrobupropion was formed. Human liver microsomes showed 10 and 80 times higher activity than rat and mouse liver microsomes, respectively. The formation of erythrohydrobupropion was not altered in experiments with microsomes from 11ß-HSD1-deficient mice or upon incubation with 11ß-HSD1 inhibitor, indicating the existence of another carbonyl reductase that generates erythrohydrobupropion. Molecular docking supported the experimental findings and suggested that 11ß-HSD1 selectively converts R-bupropion to threohydrobupropion. Enzyme inhibition experiments suggested that exposure to bupropion is not likely to impair 11ß-HSD1-dependent glucocorticoid activation but that pharmacological administration of cortisone or prednisone may inhibit 11ß-HSD1-dependent bupropion metabolism.

Carbonyl reduction of triadimefon by human and rodent 11ß-hydroxysteroid dehydrogenase 1.

11ß-Hydroxysteroid dehydrogenase 1 (11ß-HSD1) catalyzes the conversion of inactive 11-oxo glucocorticoids (endogenous cortisone, 11-dehydrocorticosterone and synthetic prednisone) to their potent 11ß-hydroxyl forms (cortisol, corticosterone and prednisolone). Besides, 11ß-HSD1 accepts several other substrates. Using rodent liver microsomes and the unspecific inhibitor glycyrrhetinic acid, it has been proposed earlier that 11ß-HSD1 catalyzes the reversible conversion of the fungicide triadimefon to triadimenol. In the present study, recombinant human, rat and mouse enzymes together with a highly selective 11ß-HSD1 inhibitor were applied to assess the role of 11ß-HSD1 in the reduction of triadimefon and to uncover species-specific differences. To further demonstrate the role of 11ß-HSD1 in the carbonyl reduction of triadimefon, microsomes from liver-specific 11ß-HSD1-deficient mice were employed. Molecular docking was applied to investigate substrate binding. The results revealed important species differences and demonstrated the irreversible 11ß-HSD1-dependent reduction of triadimefon. Human liver microsomes showed 4 and 8 times higher activity than rat and mouse liver microsomes. The apparent Vmax/Km of recombinant human 11ß-HSD1 was 5 and 15 times higher than that of mouse and rat 11ß-HSD1, respectively, indicating isoform-specific differences and different expression levels for the three species. Experiments using inhibitors and microsomes from 11ß-HSD1-deficient mice indicated that 11ß-HSD1 is the major if not only enzyme responsible for triadimenol formation. The IC50 values of triadimefon and triadimenol for cortisone reduction suggested that exposure to these xenobiotica unlikely impairs the 11ß-HSD1-dependent glucocorticoid activation. However, elevated glucocorticoids during stress or upon pharmacological administration likely inhibit 11ß-HSD1-dependent metabolism of triadimefon in humans.

Structural optimization of 2,5-thiophene amides as highly potent and selective 17ß-hydroxysteroid dehydrogenase type 2 inhibitors for the treatment of osteoporosis.

Inhibition of 17ß-HSD2 is an attractive mechanism for the treatment of osteoporosis. We report here the optimization of human 17ß-HSD2 inhibitors in the 2,5-thiophene amide class by varying the size of the linker (n equals 0 and 2) between the amide moiety and the phenyl group. While none of the phenethylamides (n = 2) were active, most of the anilides (n = 0) turned out to moderately or strongly inhibit 17ß-HSD2. The four most active compounds showed an IC50 of around 60 nM and a very good selectivity toward 17ß-HSD1, 17ß-HSD4, 17ß-HSD5, 11ß-HSD1, 11ß-HSD2 and the estrogen receptors α and ß. The investigated compounds inhibited monkey 17ß-HSD2 moderately, and one of them showed good inhibitory activity on mouse 17ß-HSD2. SAR studies allowed a first characterization of the human 17ß-HSD2 active site, which is predicted to be considerably larger than that of 17ß-HSD1.

Structure of the recombinant BPTI/Kunitz-type inhibitor rShPI-1A from the marine invertebrate Stichodactyla helianthus.

The BPTI/Kunitz-type inhibitor family includes several extremely potent serine protease inhibitors. To date, the inhibitory mechanisms have only been studied for mammalian inhibitors. Here, the first crystal structure of a BPTI/Kunitz-type inhibitor from a marine invertebrate (rShPI-1A) is reported to 2.5 Šresolution. Crystallization of recombinant rShPI-1A required the salt-induced dissociation of a trypsin complex that was previously formed to avoid intrinsic inhibitor aggregates in solution. The rShPI-1A structure is similar to the NMR structure of the molecule purified from the natural source, but allowed the assignment of disulfide-bridge chiralities and the detection of an internal stabilizing water network. A structural comparison with other BPTI/Kunitz-type canonical inhibitors revealed unusual ϕ angles at positions 17 and 30 to be a particular characteristic of the family. A significant clustering of ϕ and ψ angle values in the glycine-rich remote fragment near the secondary binding loop was additionally identified, but its impact on the specificity of rShPI-1A and similar molecules requires further study.