It has long been known that many flying insects use visual cues to orient with respect to the wind and to control their groundspeed in the face of varying wind conditions. Much less explored has been the role of mechanosensory cues in orienting insects relative to the ambient air. Here we show that Drosophila melanogaster, magnetically tethered so as to be able to rotate about their yaw axis, are able to detect and orient into a wind, as would be experienced during forward flight. Further, this behavior is velocity dependent and is likely subserved, at least in part, by the Johnston’s organs, chordotonal organs in the antennae also involved in near-field sound detection. These wind-mediated responses may help to explain how flies are able to fly forward despite visual responses that might otherwise inhibit this behavior. Expanding visual stimuli, such as are encountered during forward flight, are the most potent aversive visual cues known for D. melanogaster flying in a tethered paradigm. Accordingly, tethered flies strongly orient towards a focus of contraction, a problematic situation for any animal attempting to fly forward. We show in this study that wind stimuli, transduced via mechanosensory means, can compensate for the aversion to visual expansion and thus may help to explain how these animals are indeed able to maintain forward flight.

We present a novel slit scanning confocal microscope with a CCD camera image sensor and a virtual slit aperture for descanning that can be adjusted during post-processing. A very efficient data structure and mathematical criteria for aligning the virtual aperture guarantee the ease of use. We further introduce a method to reduce the anisotropic lateral resolution of slit scanning microscopes. System performance is evaluated against a spinning disk confocal microscope on identical specimens. The virtual slit scanning microscope works as the spinning disk type and outperforms on thick specimens.

We identified a novel regulator, Thermococcales glycolytic regulator (Tgr), functioning as both an activator and a repressor of transcription in the hyperthermophilic archaeon Thermococcus kodakaraensis KOD1. Tgr (TK1769) displays similarity (28% identical) to Pyrococcus furiosus TrmB (PF1743), a transcriptional repressor regulating the trehalose/maltose ATP-binding cassette transporter genes, but is more closely related (67%) to a TrmB paralog in P. furiosus (PF0124). Growth of a tgr disruption strain (Deltatgr) displayed a significant decrease in growth rate under gluconeogenic conditions compared with the wild-type strain, whereas comparable growth rates were observed under glycolytic conditions. A whole genome microarray analysis revealed that transcript levels of almost all genes related to glycolysis and maltodextrin metabolism were at relatively high levels in the Deltatgr mutant even under gluconeogenic conditions. The Deltatgr mutant also displayed defects in the transcriptional activation of gluconeogenic genes under these conditions, indicating that Tgr functions as both an activator and a repressor. Genes regulated by Tgr contain a previously identified sequence motif, the Thermococcales glycolytic motif (TGM). The TGM was positioned upstream of the Transcription factor B-responsive element (BRE)/TATA sequence in gluconeogenic promoters and downstream of it in glycolytic promoters. Electrophoretic mobility shift assay indicated that recombinant Tgr protein specifically binds to promoter regions containing a TGM. Tgr was released from the DNA when maltotriose was added, suggesting that this sugar is most likely the physiological effector. Our results strongly suggest that Tgr is a global transcriptional regulator that simultaneously controls, in response to sugar availability, both glycolytic and gluconeogenic metabolism in T. kodakaraensis via its direct binding to the TGM.

The 100 copies of tandemly arrayed Drosophila linker (H1) and core (H2A/B and H3/H4) histone gene cluster are coordinately regulated during the cell cycle. However, the molecular mechanisms that must allow differential transcription of linker versus core histones prevalent during development remain elusive. Here, we used fluorescence imaging, biochemistry, and genetics to show that TBP (TATA-box-binding protein)-related factor 2 (TRF2) selectively regulates the TATA-less Histone H1 gene promoter, while TBP/TFIID targets core histone transcription. Importantly, TRF2-depleted polytene chromosomes display severe chromosomal structural defects. This selective usage of TRF2 and TBP provides a novel mechanism to differentially direct transcription within the histone cluster. Moreover, genome-wide chromatin immunoprecipitation (ChIP)-on-chip analyses coupled with RNA interference (RNAi)-mediated functional studies revealed that TRF2 targets several classes of TATA-less promoters of >1000 genes including those driving transcription of essential chromatin organization and protein synthesis genes. Our studies establish that TRF2 promoter recognition complexes play a significantly more central role in governing metazoan transcription than previously appreciated.

Whereas recent studies have elucidated principles for representation of information within the entorhinal cortex, less is known about the molecular basis for information processing by entorhinal neurons. The HCN1 gene encodes ion channels that mediate hyperpolarization-activated currents (I(h)) that control synaptic integration and influence several forms of learning and memory. We asked whether hyperpolarization-activated, cation nonselective 1 (HCN1) channels control processing of information by stellate cells found within layer II of the entorhinal cortex. Axonal projections from these neurons form a major component of the synaptic input to the dentate gyrus of the hippocampus. To determine whether HCN1 channels control either the resting or the active properties of stellate neurons, we performed whole-cell recordings in horizontal brain slices prepared from adult wild-type and HCN1 knock-out mice. We found that HCN1 channels are required for rapid and full activation of hyperpolarization-activated currents in stellate neurons. HCN1 channels dominate the membrane conductance at rest, are not required for theta frequency (4-12 Hz) membrane potential fluctuations, but suppress low-frequency (<4 Hz) components of spontaneous and evoked membrane potential activity. During sustained activation of stellate cells sufficient for firing of repeated action potentials, HCN1 channels control the pattern of spike output by promoting recovery of the spike afterhyperpolarization. These data suggest that HCN1 channels expressed by stellate neurons in layer II of the entorhinal cortex are key molecular components in the processing of inputs to the hippocampal dentate gyrus, with distinct integrative roles during resting and active states.

The evolutionary rate of proteins involved in obligate protein-protein interactions is slower and the degree of coevolution higher than that for nonobligate protein-protein interactions. The coevolution of the proteins involved in certain nonobligate interactions is, however, essential to cell survival. To gain insight into the coevolution of one such nonobligate protein pair, the cytosolic ribonuclease inhibitor (RI) proteins and secretory pancreatic-type ribonucleases from cow (Bos taurus) and human (Homo sapiens) were produced in Escherichia coli and purified, and their physicochemical properties were analyzed. The two intraspecies complexes were found to be extremely tight (bovine Kd = 0.69 fM; human Kd = 0.34 fM). Human RI binds to its cognate ribonuclease (RNase 1) with 100-fold greater affinity than to the bovine homologue (RNase A). In contrast, bovine RI binds to RNase 1 and RNase A with nearly equal affinity. This broader specificity is consistent with there being more pancreatic-type ribonucleases in cows (20) than humans (13). Human RI (32 cysteine residues) also has 4-fold less resistance to oxidation by hydrogen peroxide than does bovine RI (29 cysteine residues). This decreased oxidative stability of human RI, which is caused largely by Cys74, implies a larger role for human RI as an antioxidant. The conformational and oxidative stabilities of both RIs increase upon complex formation with ribonucleases. Thus, RI has evolved to maintain its inhibition of invading ribonucleases, even when confronted with extreme environmental stress. That role appears to take precedence over its role in mediating oxidative damage.

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

In tandem ring-closing metathesis of alkynyl silaketals containing two different tethered olefins, the gem-dimethyl group showed the expected Thorpe-Ingold effect, thereby giving good level of group selectivity. Unexpectedly, however, the corresponding gem-diphenyl group did not show any Thorpe-Ingold effect for the ring closure reaction.

Genetically encoded optical indicators hold the promise of enabling non-invasive monitoring of activity in identified neurons in behaving organisms. However, the interpretation of images of brain activity produced using such sensors is not straightforward. Several recent studies of sensory coding used G-CaMP 1.3-a calcium sensor-as an indicator of neural activity; some of these studies characterized the imaged neurons as having narrow tuning curves, a conclusion not always supported by parallel electrophysiological studies. To better understand the possible cause of these conflicting results, we performed simultaneous in vivo 2-photon imaging and electrophysiological recording of G-CaMP 1.3 expressing neurons in the antennal lobe (AL) of intact fruitflies. We find that G-CaMP has a relatively high threshold, that its signal often fails to capture spiking response kinetics, and that it can miss even high instantaneous rates of activity if those are not sustained. While G-CaMP can be misleading, it is clearly useful for the identification of promising neural targets: when electrical activity is well above the sensor’s detection threshold, its signal is fairly well correlated with mean firing rate and G-CaMP does not appear to alter significantly the responses of neurons that express it. The methods we present should enable any genetically encoded sensor, activator, or silencer to be evaluated in an intact neural circuit in vivo in Drosophila.

We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in firing pattern) in the voltage responses to repetitions of the exact same input. Thus, the common approach of fitting models by attempting to perfectly replicate, point by point, a single chosen trace out of the spectrum of variable responses does not seem to do justice to the data. In addition, finding a single error function that faithfully characterizes the distance between two spiking traces is not a trivial pursuit. To address these issues, one can adopt a multiple objective optimization approach that allows the use of several error functions jointly. When more than one error function is available, the comparison between experimental voltage traces and model response can be performed on the basis of individual features of interest (e.g., spike rate, spike width). Each feature can be compared between model and experimental mean, in units of its experimental variability, thereby incorporating into the fitting this variability. We demonstrate the success of this approach, when used in conjunction with genetic algorithm optimization, in generating an excellent fit between model behavior and the firing pattern of two distinct electrical classes of cortical interneurons, accommodating and fast-spiking. We argue that the multiple, diverse models generated by this method could serve as the building blocks for the realistic simulation of large neuronal networks.