Modelling the early steps of transduction in insect olfactory receptor neurons

Olfactory transduction is a multistep process whose basic function is to convert a low energy reaction, the odorant-receptor interaction that may involve a single odorant molecule, into a whole cell electrical response, the receptor potential, which triggers the firing of one or more action potentials. Although much effort has been devoted to the experimental analysis of transduction in olfactory receptor neurons (ORNS), especially in the favorable moth sex-pheromone receptor neuron, its modelling is less advanced. The model we investigated, which takes into account the translocation of pheromone molecules from air to the extracellular space, their deactivation and their interaction with receptors, focuses on the membrane cascade. It involves the interaction of receptors, G-proteins and effector enzymes, whose reaction rates are limited by lateral diffusion in the membrane. The evolutions in time of these species in response to single pulse stimulation of various intensities were compared to one another and to the experimentally measured electrical response. The results obtained suggest that the receptor-to-effector conversion is fast with respect to the receptor response, that it presents a small amplification factor, contrary to the photoreceptor, and that most of the amplification is achieved in the post-effector processes involving the second messenger and ionic channels.     

Fluorinated acyclo-C-nucleoside analogues from glycals in two steps

A convenient two-step strategy is reported for the synthesis of fluorinated optically pure acyclo-C-nucleoside analogues starting from simple glycals. In the first step, benzyl- or p-methoxybenzyl-protected glycals are treated with trifluoroacetic anhydride, bromodifluoroacetyl chloride, trichloroacetyl chloride, and perfluorooctanoyl chloride, respectively, in the presence of Et3N. This one-pot procedure yields 1,2-unsaturated sugars (1,5-anhydro-3,4,6-tri-O-benzyl (or p-methoxybenzyl) 2-deoxy-2-perhalogenoacyl-D-arabino / lyxo-hex-1-enitols 4-9) acylated at C-2. In the second step, a selective ring transformation is induced by treatment of the C-acylated glycals with bis-nucleophiles (hydrazine, phenylhydrazine, o-phenylenediamine, hydroxylamine). In particular, 1,5-anhydro-3,4,6-tri-O-benzyl-2-deoxy-2-trifluoroacetyl-D-arabino-hex-1-enitol (4) and 1,5-anhydro-2-deoxy-2-trifluoroacetyl-3,4,6-tri-O-(p-methoxybenzyl)-D-arabino-hex-1-enitol (8) were reacted with these nucleophiles generating the final C-nucleoside analogues of pyrazole (10, 11, and 12), diazepine (13), and isoxazole (15), respectively, containing a carbohydrate side chain linked to the heterocyclic ring.     

para-aminobenzoate synthesis from chorismate occurs in two steps

Escherichia coli p-aminobenzoate synthase is composed of two nonidentical subunits encoded by pabA and pabB and has been assumed to be the sole enzyme responsible for p-aminobenzoate biosynthesis from chorismate and glutamine. Plasmids were constructed that overproduce the p-aminobenzoate synthase subunits 250-500-fold. Partial purification of the subunits revealed that they form a diffusible intermediate that is subsequently converted to p-aminobenzoate by a second enzyme (Mr = 49,000) temporarily designated enzyme X.     

Marine reserve spillover: Modelling from multiple data sources

The functional form of spillover, measured as a gradient of abundance of fish, may provide insight about processes that control the spatial distribution of fish inside and outside the MPA. In this study, we aimed to infer on spillover mechanism of Diplodus spp. (family Sparidae) from a Mediterranean MPA (Carry-le-Rouet, France) from visual censuses and artisanal fisheries data. From the existing literature, three potential functional forms of spillover such as a linear gradient, an exponential gradient and a logistic gradient are defined. Each functional form is included in a spatial generalized linear mixed model allowing accounting for spatial autocorrelation of data. We select between the different forms of gradients by using a Bayesian model selection procedure. In a first step, the functional form of the spillover for visual census and artisanal fishing data is assessed separately. For both sets of data, our model selection favoured the negative exponential model, evidencing a decrease of the spatial abundance of fish vanishing around 1000 m from the MPA border. We combined both datasets in a joint model by including an observability parameter. This parameter captures how the different sources of data quantify the underlying spatial distribution of the harvested species. This enabled us to demonstrate that the different sampling methods do not affect the estimation of the underlying spatial distribution of Diplodus spp. inside and outside the MPA. We show that data from different sources can be pooled through spatial generalized linear mixed model. Our findings allow to better understand the underlying mechanisms that control spillover of fish from MPA.     

Modelling efficiency in insect olfactory information processing

The olfactory system of insects is essential for the search of food and mates, and weak signals can be detected, amplified and discriminated in a fluctuating environment. The olfactory system also allows for learning and recall of odour memories. Based on anatomical, physiological, and behavioural data from the olfactory system of insects, we have developed a cross-scale dynamical neural network model to simulate the presentation, amplification and discrimination of host plant odours and sex pheromones. In particular, we model how the spatial and temporal patterns of the odour information emerging in the glomeruli of the antennal lobe (AL) rely on the glomerular morphology, the connectivity and the complex dynamics of the AL circuits. We study how weak signals can be amplified, how different odours can be discriminated, based on stochastic (resonance) dynamics and the connectivity of the network. We further investigate the spatial and temporal coding of sex pheromone components and plant volatile compounds, in relation to the glomerular structure, arborizing patterns of the projection neurons (PNs) and timing patterns of the neuronal spiking activity.     

Extracting binary signals from microarray time-course data

This article presents a new method for analyzing microarray time courses by identifying genes that undergo abrupt transitions in expression level, and the time at which the transitions occur. The algorithm matches the sequence of expression levels for each gene against temporal patterns having one or two transitions between two expression levels. The algorithm reports a P-value for the matching pattern of each gene, and a global false discovery rate can also be computed. After matching, genes can be sorted by the direction and time of transitions. Genes can be partitioned into sets based on the direction and time of change for further analysis, such as comparison with Gene Ontology annotations or binding site motifs. The method is evaluated on simulated and actual time-course data. On microarray data for budding yeast, it is shown that the groups of genes that change in similar ways and at similar times have significant and relevant Gene Ontology annotations.     

Purification of glutathione reductase from gerbil liver in two steps

A new method for the isolation of glutathione reductase which successively utilizes chromatography on 2'-5'-ADP-Sepharose 4B and DEAE-Sepharose CL 6B, is described. With these two steps, it was possible to purify to homogeneity the glutathione reductase from gerbil liver. Some molecular properties of the purified enzyme are reported.     

Modelling larval movement data from individual bioassays

We consider modelling the movements of larvae using individual bioassays in which data are collected at a high‐frequency rate of five observations per second. The aim is to characterize the behaviour of the larvae when exposed to attractant and repellent compounds. Mixtures of diffusion processes, as well as Hidden Markov models, are proposed as models of larval movement. These models account for directed and localized movements, and successfully distinguish between the behaviour of larvae exposed to attractant and repellent compounds. A simulation study illustrates the advantage of using a Hidden Markov model rather than a simpler mixture model. Practical aspects of model estimation and inference are considered on extensive data collected in a study of novel approaches for the management of cabbage root fly.     

Extracellular recording of spatiotemporal patterning in response to odors in the olfactory epithelium by microelectrode arrays

In olfactory biosensors, microelectronic sensor chips combined with biological olfactory cells are a promising platform for odor detection. In our investigation, olfactory epithelium stripped from rat was fixed on the surface of microelectrode arrays (MEAs). Electrophysiological activities of olfactory receptor neurons in intact epithelium were measured in the form of extracellular potentials. Based on multi-channel recording performance of MEA and structural and functional integrality of native olfactory epithelium, the spatiotemporal analysis was carried out to study the extracellular activity pattern of neurons in the tissue. The variation of spatiotemporal patterns corresponding to different odors displayed the signals firing image characteristic intuitionally. It is an effective method in the form of patterns for monitoring the state of tissue both in time and space domain, promoting the platform for olfactory sensing mechanism research.     

Rostro-caudal patterning of receptor-expressing olfactory neurones in the rat nasal cavity

The rostro-caudal extent of odorant receptor expression zones in the rat olfactory epithelium was analysed by means of in situ hybridization. Three broad non-overlapping zones were identified that extended along almost the entire anterior-posterior axis; each zone was composed of several separate bands running anterior to posterior throughout the olfactory epithelium. Superimposed onto these broad zones was the expression area of a particular receptor subtype (OR37); it was restricted to a small region of the epithelial sheet with a high density of reactive neurones in the centre and declining numbers towards the periphery of the region. A quantitative evaluation of the reactive cells revealed that, despite their diferent distribution patterns, all receptor subtypes were expressed in an equal number of neurones.     

Response of olfactory receptor neurons in honeybees to odorants and their binary mixtures

Recordings were made from single sensilla placodea of the worker honeybee (Apis mellifera). The sensilla were stimulated with one of two sets of four compounds and their binary mixtures, at two dosage levels. Aromatic compounds comprised one set, and saturated n-octane derivatives comprised the other set. Correlation, principal component, and cluster analyses indicate that responses to binary mixtures are not linear combinations of responses to the component compounds. The first principal component indicated that neuronal units had either more excitatory or more inhibitory responses to all odorants than would be expected from a model where inhibitory and excitatory responses are randomly distributed among the neuronal units. When compared to the responses to the component odorants, synergistic responses to binary odors occurred more often than would be expected by chance. Clear inhibitory responses to binary odors were less prevalent. This study agrees with an earlier study employing aromatic odorants in that most of the aromatic odorants each had groups of receptor neurons that were relatively selective for it, and each odorant had a distinctly different number of receptor neurons selective for it. Among the octane derivatives, receptor neurons were selective for the level of oxidation of the functional group or its site of attachment, rather than specific compounds.     

A local influence approach applied to binary data from a psychiatric study

Recently, a lot of concern has been raised about assumptions needed in order to fit statistical models to incomplete multivariate and longitudinal data. In response, research efforts are being devoted to the development of tools that assess the sensitivity of such models to often strong but always, at least in part, unverifiable assumptions. Many efforts have been devoted to longitudinal data, primarily in the selection model context, although some researchers have expressed interest in the pattern-mixture setting as well. A promising tool, proposed by Verbeke et al. (2001, Biometrics 57, 43-50), is based on local influence (Cook, 1986, Journal of the Royal Statistical Society, Series B 48, 133-169). These authors considered the Diggle and Kenward (1994, Applied Statistics 43, 49-93) model, which is based on a selection model, integrating a linear mixed model for continuous outcomes with logistic regression for dropout. In this article, we show that a similar idea can be developed for multivariate and longitudinal binary data, subject to nonmonotone missingness. We focus on the model proposed by Baker, Rosenberger, and DerSimonian (1992, Statistics in Medicine 11, 643-657). The original model is first extended to allow for (possibly continuous) covariates, whereafter a local influence strategy is developed to support the model-building process. The model is able to deal with nonmonotone missingness but has some limitations as well, stemming from the conditional nature of the model parameters. Some analytical insight is provided into the behavior of the local influence graphs.     

Modelling the sensitivity of cells in the anteroventral cochlear nucleus to spatiotemporal discharge patterns.

This study investigates a potential mechanism for the processing of acoustic information that is encoded in the spatiotemporal discharge patterns of auditory nerve (AN) fibres. Recent physiological evidence has demonstrated that some low-frequency cells in the anteroventral cochlear nucleus (AVCN) are sensitive to manipulations of the phase spectrum of complex sounds (Carney 1990b). These manipulations result in systematic changes in the spatiotemporal discharge patterns across groups of low-frequency AN fibres having different characteristic frequencies (CFS). One interpretation of these results is that these neurons in the AVCN receive convergent inputs from AN fibres with different CFS, and that the cells perform a coincidence detection or cross-correlation upon their inputs. This report presents a model that was developed to test this interpretation.