Atropselective syntheses of (-) and (+) rugulotrosin A utilizing point-to-axial chirality transfer

Chiral, dimeric natural products containing complex structures and interesting biological properties have inspired chemists and biologists for decades. A seven-step total synthesis of the axially chiral, dimeric tetrahydroxanthone natural product rugulotrosin A is described. The synthesis employs a one-pot Suzuki coupling/dimerization to generate the requisite 2,2'-biaryl linkage. Highly selective point-to-axial chirality transfer was achieved using palladium catalysis with achiral phosphine ligands. Single X-ray crystal diffraction data were obtained to confirm both the atropisomeric configuration and absolute stereochemistry of rugulotrosin A. Computational studies are described to rationalize the atropselectivity observed in the key dimerization step. Comparison of the crude fungal extract with synthetic rugulotrosin A and its atropisomer verified that nature generates a single atropisomer of the natural product.P50 GM067041 - NIGMS NIH HHS; R01 GM099920 - NIGMS NIH HHS; GM-067041 - NIGMS NIH HHS; GM-099920 - NIGMS NIH HH

Efficient Temporal Processing of Naturalistic Sounds

In this study, we investigate the ability of the mammalian auditory pathway to adapt its strategy for temporal processing under natural stimulus conditions. We derive temporal receptive fields from the responses of neurons in the inferior colliculus to vocalization stimuli with and without additional ambient noise. We find that the onset of ambient noise evokes a change in receptive field dynamics that corresponds to a change from bandpass to lowpass temporal filtering. We show that these changes occur within a few hundred milliseconds of the onset of the noise and are evident across a range of overall stimulus intensities. Using a simple model, we illustrate how these changes in temporal processing exploit differences in the statistical properties of vocalizations and ambient noises to increase the information in the neural response in a manner consistent with the principles of efficient coding

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Modeling convergent ON and OFF pathways in the early visual system

For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron’s response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus–response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological “linear–nonlinear” (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron’s receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data

Estimating Receptive Fields from Responses to Natural Stimuli with Asymmetric Intensity Distributions

The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli

Cepred: Predicting the Co-Expression Patterns of the Human Intronic microRNAs with Their Host Genes

Identifying the tissues in which a microRNA is expressed could enhance the understanding of the functions, the biological processes, and the diseases associated with that microRNA. However, the mechanisms of microRNA biogenesis and expression remain largely unclear and the identification of the tissues in which a microRNA is expressed is limited. Here, we present a machine learning based approach to predict whether an intronic microRNA show high co-expression with its host gene, by doing so, we could infer the tissues in which a microRNA is high expressed through the expression profile of its host gene. Our approach is able to achieve an accuracy of 79% in the leave-one-out cross validation and 95% on an independent testing dataset. We further estimated our method through comparing the predicted tissue specific microRNAs and the tissue specific microRNAs identified by biological experiments. This study presented a valuable tool to predict the co-expression patterns between human intronic microRNAs and their host genes, which would also help to understand the microRNA expression and regulation mechanisms. Finally, this framework can be easily extended to other species

Suffix-specific RNAi Leads to Silencing of F Element in Drosophila melanogaster

Separate conserved copies of suffix, a short interspersed Drosophila retroelement (SINE), and also divergent copies in the 3′ untranslated regions of the three genes, have already been described. Suffix has also been identified on the 3′ end of the Drosophila non-LTR F element, where it forms the last conserved domain of the reverse transcriptase (RT). In our current study, we show that the separate copies of suffix are far more actively transcribed than their counterparts on the F element. Transcripts from both strands of suffix are present in RNA preparations during all stages of Drosophila development, providing the potential for the formation of double-stranded RNA and the initiation of RNA interference (RNAi). Using in situ RNA hybridization analysis, we have detected the expression of both sense and antisense suffix transcripts in germinal cells. These sense and antisense transcripts are colocalized in the primary spermatocytes and in the cytoplasm of the nurse cells, suggesting that they form double-stranded RNA. We performed further analyses of suffix-specific small RNAs using northern blotting and SI nuclease protection assays. Among the total RNA preparations isolated from embryos, larvae, pupae and flies, suffix-specific small interfering RNAs (siRNAs) were detected only in pupae. In wild type ovaries, both the siRNAs and longer suffix-specific Piwi-interacting RNAs (piRNAs) were observed, whereas in ovaries of the Dicer-2 mutant, only piRNAs were detected. We further found by 3′ RACE that in pupae and ovaries, F element transcripts lacking the suffix sequence are also present. Our data provide direct evidence that suffix-specific RNAi leads to the silencing of the relative LINE (long interspersed element), F element, and suggests that SINE-specific RNA interference could potentially downregulate a set of genes possessing SINE stretches in their 5′ or 3′ non-coding regions. These data also suggest that double stranded RNAs possessing suffix are processed by both RNAi and an additional silencing mechanism

The ERI-6/7 Helicase Acts at the First Stage of an siRNA Amplification Pathway That Targets Recent Gene Duplications

Endogenous small interfering RNAs (siRNAs) are a class of naturally occuring regulatory RNAs found in fungi, plants, and animals. Some endogenous siRNAs are required to silence transposons or function in chromosome segregation; however, the specific roles of most endogenous siRNAs are unclear. The helicase gene eri-6/7 was identified in the nematode Caenorhabditis elegans by the enhanced response to exogenous double-stranded RNAs (dsRNAs) of the null mutant. eri-6/7 encodes a helicase homologous to small RNA factors Armitage in Drosophila, SDE3 in Arabidopsis, and Mov10 in humans. Here we show that eri-6/7 mutations cause the loss of 26-nucleotide (nt) endogenous siRNAs derived from genes and pseudogenes in oocytes and embryos, as well as deficiencies in somatic 22-nucleotide secondary siRNAs corresponding to the same loci. About 80 genes are eri-6/7 targets that generate the embryonic endogenous siRNAs that silence the corresponding mRNAs. These 80 genes share extensive nucleotide sequence homology and are poorly conserved, suggesting a role for these endogenous siRNAs in silencing of and thereby directing the fate of recently acquired, duplicated genes. Unlike most endogenous siRNAs in C. elegans, eri-6/7–dependent siRNAs require Dicer. We identify that the eri-6/7–dependent siRNAs have a passenger strand that is ∼19 nt and is inset by ∼3–4 nts from both ends of the 26 nt guide siRNA, suggesting non-canonical Dicer processing. Mutations in the Argonaute ERGO-1, which associates with eri-6/7–dependent 26 nt siRNAs, cause passenger strand stabilization, indicating that ERGO-1 is required to separate the siRNA duplex, presumably through endonucleolytic cleavage of the passenger strand. Thus, like several other siRNA–associated Argonautes with a conserved RNaseH motif, ERGO-1 appears to be required for siRNA maturation

The Activities of Current Antimalarial Drugs on the Life Cycle Stages of Plasmodium: A Comparative Study with Human and Rodent Parasites

Michael Delves and colleagues compare the activity of 50 current and experimental antimalarials against liver, sexual blood, and mosquito stages of selected human and nonhuman parasite species, including Plasmodium falciparum, Plasmodium berghei, and Plasmodium yoelii