A short-oligonucleotide microarray that allows improved detection of gastrointestinal tract microbial communities

Background  

The human gastrointestinal (GI) tract contains a diverse collection of bacteria, most of which are unculturable by conventional microbiological methods. Increasingly molecular profiling techniques are being employed to examine this complex microbial community. The purpose of this study was to develop a microarray technique based on 16S ribosomal gene sequences for rapidly monitoring the microbial population of the GI tract.     

Honeybee communication: a signal for danger

Scout honeybees recruit other bees to visit a newly discovered food source through the famous 'waggle dance'. Now a new study reports that other nest mates can induce the dancer to stop advertising, if they have experienced danger at that location.     

Complex binding interactions between multicomponent mixtures and odorant receptors in the olfactory organ of the Caribbean spiny lobster Panulirus argus

Our study was designed to examine how components of complex mixtures caninhibit the binding of other components to receptor sites in the olfactorysystem of the spiny lobster Panulirus argus. Biochemical binding assayswere used to study how two- to six-component mixtures inhibit binding ofthe radiolabeled odorants taurine, L-glutamate andadenosine-5'-monophosphate to a tissue fraction rich in dendritic membraneof olfactory receptor neurons. Our results indicate that binding inhibitionby mixtures can be large and is dependent on the nature of the odorantligand and on the concentration and composition of the mixture. The bindinginhibition by mixtures of structurally related components was generallypredicted using a competitive binding model and binding inhibition data forthe individual components. This was not the case for binding inhibition bymost mixtures of structurally unrelated odorants. The binding inhibitionfor these mixtures was generally smaller than that for one or more of theircomponents, indicating that complex binding interactions between componentscan reduce their ability to inhibit binding. The magnitude of bindinginhibition was influenced more by the mixture's precise composition than bythe number of components in it, since mixtures with few components weresometimes more inhibitory than mixtures with more components. Thesefindings raise the possibility that complex binding interactions betweencomponents of a mixture and their receptors may shape the output ofolfactory receptor neurons to complex mixtures.     

Complex memories in honeybees: can there be more than two?

Foraging honeybees are likely to learn visual and chemical cues associated with many different food sources. Here, we explore how many such sources can be memorized and recalled. Marked bees were trained to visit two (or three) sugar feeders, each placed at a different outdoor location and carrying a different scent. We then tested the ability of the bees to recall these locations and fly to them, when the training scents were blown into the hive, and the scents and food at the feeders were removed. When trained on two feeder locations, each associated with a different scent, the bees could correctly recall the location associated with each scent. However, this ability broke down when the number of scents and feeder locations was increased to three. Performance was partially restored when each of the three training feeders was endowed with an additional cue, namely, a distinct colour. Our results suggest that bees can recall a maximum of two locations when each is associated with a different scent. However, this number can be increased if the scent cues are augmented by visual cues. These findings have implications for the ways in which associations are established and laid down in honeybee memory.     

A visually evoked escape response of the housefly

Summary Flies (Musca domestica) avoid danger by initiating a rapid jump followed by flight. To identify the visual cues that trigger the escape response in the housefly, we measured the timing and probability of escapes when the fly was presented with a variety of visual stimuli created by moving targets toward it. Our results show that an escape response is triggered by an approaching dark disk, but not by a receding dark disk. On the other hand, a bright disk elicits escape only when it recedes. A disk with black and white rings is less effective at eliciting escape than is a dark solid disk of the same size. This indicates that the darkening contrast produced by an approaching stimulus is a more crucial parameter than expansion cues contained in the optical flow. Escape is also triggered by a horizontally moving dark edge, but not by a moving bright edge or by a grating. An examination of several visual parameters reveals that the darkening contrast, measured from the onset of stimulation to the start of escape is nearly constant for a variety of stimuli that trigger escape reliably. Thus darkening contrast, coupled with motion may be crucial in eliciting the visually evoked escape response. Other visual parameters such as time-to-contact or target angular velocity seem to be relatively unimportant to the timing of escapes.Abbreviations P _s Probability of successful escape - r _disk radius of disk target - r _arena radius of shielding arena - v _disk linear velocity of disk target - v _edge linear velocity of edge - d _disk angular velocity of disk target boundary - _edge angular velocity of edge - _escape target distance at escape - d _start target distance before onset of target movement - h _edge height of the edge above fly - x _start distance from corner of triangle to start position of edge (0 or 50 mm) - x _escape distance from corner of triangle to the position of the edge when the fly escapes - x _center distance from corner of triangle to point above the center of the pad - x _total distance from the corner of the triangle to the base (height of triangle = base of triangle)     

The cover of living and dead corals from airborne remote sensing

Trends in coral cover are widely used to indicate the health of coral reefs but are costly to obtain from field survey over large areas. In situ studies of reflected spectra at the coral surface show that living and recently dead colonies can be distinguished. Here, we investigate whether such spectral differences can be detected using an airborne remote sensing instrument. The Compact Airborne Spectrographic Imager (Itres Research Ltd, Canada) was flown in two configurations: 10 spectral bands with 1-m² pixels and 6 spectral bands with 0.25-m² pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral resolution to distinguish living Porites, living Pocillopora spp., partially dead Porites, recently dead Porites (total colony mortality within 6 months), old dead (>6 months) Porites, Halimeda spp., and coralline red algae when there is no water column to confuse spectra. All substrata were distinguished using fourth-order spectral derivatives around 538 nm and 562 nm. Then, at a shallow site (Tivaru) at Rangiroa Atoll, Tuamotu Archipelago (French Polynesia), we show that live and dead coral can be distinguished from the air to a depth of at least 4 m using first- and fourth-order spectral derivatives between 562–580 nm. However, partially dead and recently dead Porites colonies could not be distinguished from an airborne platform. Spectral differences among substrata are then exploited to predict the cover of reef substrata in ten 25-m² plots at nearby Motu Nuhi (max depth 8 m). The actual cover in these plots was determined in situ using quadrats with a 0.01-m² grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m² quadrats. At this small scale, disparity, measured as the absolute difference in cover between field and remote-sensing methods, reached 25% in some substrata but was always less than 10% for living coral (99% of which consisted of Porites spp.). At the scale of the reef (all ten 25-m² quadrats), however, disparities in percent cover between imagery and field data were less than 10% for all substrata and extremely low for some classes (e.g. <3% for living Porites, recently dead Porites and Halimeda). The least accurately estimated substrata were sand and coralline red algae, which were overestimated by absolute values 7.9% and 6.6%, respectively. The precision of sampling was similar for field and remote-sensing methods: field methods required 19 plots to detect a 10% difference in coral cover among three reefs with a statistical power of 95%. Remote-sensing methods required 21 plots. However, it took 1 h to acquire imagery over 92,500 m² of reef, which represents 3,700 plots of 25 m² each, compared with 3 days to survey 10 such plots underwater. There were no significant differences in accuracy between 1-m² and 0.25-m² image resolutions, suggesting that the advantage of using smaller pixels is offset by reduced spectral information and an increase in noise (noise was observed to be 1.6–1.8 times greater in 0.25-m² pixels). We show that airborne remote sensing can be used to monitor coral and algal cover over large areas, providing that water is shallow and clear, and that brown fleshy macroalgae are scarce, that depth is known independently (e.g. from sonar survey).     

Going with the flow: a brief history of the study of the honeybee’s navigational ‘odometer’

Honeybees navigate to a food source using a sky-based compass to determine their travel direction, and an odometer to register how far they have travelled. The past 20 years have seen a renewed interest in understanding the nature of the odometer. Early work, pioneered by von Frisch and colleagues, hypothesized that travel distance is measured in terms of the energy that is consumed during the journey. More recent studies suggest that visual cues play a role as well. Specifically, bees appear to gauge travel distance by sensing the extent to which the image of the environment moves in the eye during the journey from the hive to the food source. Most of the evidence indicates that travel distance is measured during the outbound journey. Accumulation of odometric errors is restricted by resetting the odometer every time a prominent landmark is passed. When making detours around large obstacles, the odometer registers the total distance of the path that is flown to the destination, and not the “bee-line” distance. Finally, recent studies are revealing that bees can perform odometry in three dimensions.