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3945 Publications
Showing 831-840 of 3945 resultsAmyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP) aggregate to form amyloid fibrils that deposit in tissues, and are associated with Alzheimer's disease (AD) and Type-II Diabetes (T2D), respectively. Individuals with T2D have an increased risk of developing AD, and conversely, AD patients have an increased risk of developing T2D. Evidence suggests that this link between AD and T2D might originate from a structural similarity between aggregates of Aβ and hIAPP. Using the cryoEM method Micro-Electron Diffraction (MicroED) we determined the atomic structures of 11-residue segments from both Aβ and hIAPP, termed Aβ 24-34 WT and hIAPP 19-29 S20G, with 64% sequence similarity. We observe a high degree of structural similarity between their backbone atoms (0.96 Å RMSD). Moreover, fibrils of these segments induce amyloid formation through self- and cross-seeding. Furthermore, inhibitors designed for one segment show cross-efficacy for full-length Aβ and hIAPP and reduce cytotoxicity of both proteins, though by apparently blocking different cytotoxic mechanisms. The similarity of the atomic structures of Aβ 24-34 WT and hIAPP 19-29 S20G offers a molecular model for cross-seeding between Aβ and hIAPP.
The suppression of tumorigenicity 2/IL-33 (ST2/IL-33) pathway has been implicated in several immune and inflammatory diseases. ST2 is produced as 2 isoforms. The membrane-bound isoform (ST2L) induces an immune response when bound to its ligand, IL-33. The other isoform is a soluble protein (sST2) that is thought to be a decoy receptor for IL-33 signaling. Elevated sST2 levels in serum are associated with an increased risk for cardiovascular disease. We investigated the determinants of sST2 plasma concentrations in 2,991 Framingham Offspring Cohort participants. While clinical and environmental factors explained some variation in sST2 levels, much of the variation in sST2 production was driven by genetic factors. In a genome-wide association study (GWAS), multiple SNPs within IL1RL1 (the gene encoding ST2) demonstrated associations with sST2 concentrations. Five missense variants of IL1RL1 correlated with higher sST2 levels in the GWAS and mapped to the intracellular domain of ST2, which is absent in sST2. In a cell culture model, IL1RL1 missense variants increased sST2 expression by inducing IL-33 expression and enhancing IL-33 responsiveness (via ST2L). Our data suggest that genetic variation in IL1RL1 can result in increased levels of sST2 and alter immune and inflammatory signaling through the ST2/IL-33 pathway.
The pea aphid, Acyrthosiphon pisum, exhibits several environmentally cued polyphenisms, in which discrete, alternative phenotypes are produced. At low-density, parthenogenetic females produce unwinged female progeny, but at high-density females produce progeny that develop with wings. These alternative phenotypes represent a solution to the competing demands of dispersal and reproduction. Males also develop as either winged or unwinged, but these alternatives are determined by a genetic polymorphism. Winged and unwinged males are morphologically less distinct from each other than winged and unwinged females, possibly because males experience fewer trade-offs between dispersal and reproduction. To assess whether shared physiological differences mirror the shared morphological differences that characterize the wing polyphenism and polymorphism, we used a cDNA microarray representing an estimated 10% of the coding genome (1734 genes) to examine differential transcript accumulation between winged and unwinged females and males. We identified several transcripts that differentially accumulate between winged and unwinged morphs in both sexes, the majority of which are involved in energy production. Unexpectedly, the extent of differential transcript accumulation between winged and unwinged morphs was greater for adult males than for adult females. Together, these results suggest not only that similar physiological differences underlie the polyphenism and polymorphism, but that male morphs, like females, are subject to trade-offs between reproduction and dispersal that are reflected in levels of transcript accumulation and possibly genome-wide patterns of gene regulation. These data also provide a baseline for future studies of the molecular and physiological basis of life-history trade-offs.
The sense of taste is a specialized chemosensory system dedicated to the evaluation of food and drink. Despite the fact that vertebrates and insects have independently evolved distinct anatomic and molecular pathways for taste sensation, there are clear parallels in the organization and coding logic between the two systems. There is now persuasive evidence that tastant quality is mediated by labeled lines, whereby distinct and strictly segregated populations of taste receptor cells encode each of the taste qualities.
The behavioral response to a sensory stimulus may depend on both learned and innate neuronal representations. How these circuits interact to produce appropriate behavior is unknown. In Drosophila, the lateral horn (LH) and mushroom body (MB) are thought to mediate innate and learned olfactory behavior, respectively, although LH function has not been tested directly. Here we identify two LH cell types (PD2a1 and PD2b1) that receive input from an MB output neuron required for recall of aversive olfactory memories. These neurons are required for aversive memory retrieval and modulated by training. Connectomics data demonstrate that PD2a1 and PD2b1 neurons also receive direct input from food odor-encoding neurons. Consistent with this, PD2a1 and PD2b1 are also necessary for unlearned attraction to some odors, indicating that these neurons have a dual behavioral role. This provides a circuit mechanism by which learned and innate olfactory information can interact in identified neurons to produce appropriate behavior.
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.
Determining the precise spatial extent of expression of genes across different tissues, along with knowledge of the biochemical function of the genes is critical for understanding the roles of various genes in the development of metazoan organisms. To address this problem, we have developed high-throughput methods for generating images of gene expression in Drosophila melanogaster imaginal discs and for the automated analysis of these images. Our method automatically learns tissue shapes from a small number of manually segmented training examples and automatically aligns, extracts and scores new images, which are analyzed to generate gene expression maps for each gene. We have developed a reverse lookup procedure that enables us to identify genes that have spatial expression patterns most similar to a given gene of interest. Our methods enable us to cluster both the genes and the pixels that of the maps, thereby identifying sets of genes that have similar patterns, and regions of the tissues of interest that have similar gene expression profiles across a large number of genes.
Neural circuits mediating visually evoked escape behaviors are promising systems in which to dissect the neural basis of behavior. Behavioral responses to predator-like looming stimuli, and their underlying neural computations, are remarkably similar across species. Recently, genetic tools have been applied in this classical paradigm, revealing novel non-cortical pathways that connect loom processing to defensive behaviors in mammals and demonstrating that loom encoding models from locusts also fit vertebrate neural responses. In both invertebrates and vertebrates, relative spike-timing in descending pathways is a mechanism for escape behavior choice. Current findings suggest that experimentally tractable systems, such as Drosophila, may be applicable models for sensorimotor processing and persistent states in higher organisms.
Evolution has generated an enormous variety of morphological, physiological, and behavioral traits in animals. How do behaviors evolve in different directions in species equipped with similar neurons and molecular components? Here we adopted a comparative approach to investigate the similarities and differences of escape behaviors in response to noxious stimuli and their underlying neural circuits between closely related drosophilid species. Drosophilids show a wide range of escape behaviors in response to noxious cues, including escape crawling, stopping, head casting, and rolling. Here we find that D. santomea, compared with its close relative D. melanogaster, shows a higher probability of rolling in response to noxious stimulation. To assess whether this behavioral difference could be attributed to differences in neural circuitry, we generated focused ion beam-scanning electron microscope volumes of the ventral nerve cord of D. santomea to reconstruct the downstream partners of mdIV, a nociceptive sensory neuron in D. melanogaster. Along with partner interneurons of mdVI (including Basin-2, a multisensory integration neuron necessary for rolling) previously identified in D. melanogaster, we identified two additional partners of mdVI in D. santomea. Finally, we showed that joint activation of one of the partners (Basin-1) and a common partner (Basin-2) in D. melanogaster increased rolling probability, suggesting that the high rolling probability in D. santomea is mediated by the additional activation of Basin-1 by mdIV. These results provide a plausible mechanistic explanation for how closely related species exhibit quantitative differences in the likelihood of expressing the same behavior.