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Gi/o protein-coupled receptor (Gi/o-GPCR) inhibition of pancreatic β-cell Ca2+ entry limits islet insulin secretion; however, the mechanism has not been identified. As Gi/o-GPCRs activate G protein-gated inwardly rectifying K+ (GIRK) channels, we examined their contribution to β-cell Gi/o signaling. However, Gi/o-GPCR-induced β-cell GIRK currents were not observed; this was demonstrated with a pharmacological approach and by genetic knockout of the predominant β-cell GIRK channel subunit. Thus, we increased the chemical driving force for K+ movement through GIRK channels by removing extracellular K+. Interestingly, under these conditions Gi/o-GPCR-induced β-cell membrane potential (Vm) hyperpolarization was lost even though K+ channel activation could still hyperpolarize Vm, which indicated that Gi/o-GPCRs do not hyperpolarize β-cell Vm by activating K+ channels. As extracellular K+ is required for Na+/K+ ATPase (NKA) activity, we next tested and found that mouse and human β-cell NKAs were activated by Gi/o-GPCRs. Stimulation of Gi/o-GPCRs initiated cyclical β-cell NKA activity, resulting in islet Ca2+ oscillations. Moreover, paracrine activation of β-cell NKAs by intraislet δ-cell somatostatin (SST) secretion decelerated islet Ca2+ oscillations and diminished insulin secretion, which was mediated by direct activation of β-cell Gi/o-GPCRs. Gi/o signaling induced islet Ca2+ oscillations through Src tyrosine kinase-dependent NKA phosphorylation and activation; an effect that was recapitulated by stimulating insulin receptor tyrosine kinases. Whereas, islet NKA function was completely inhibited by cAMP-dependent PKA activation. Therefore, these findings reveal that NKA-mediated hyperpolarization of β-cell Vm is the primary and conserved mechanism for Gi/o-GPCR control of electrical excitability, Ca2+ handling, and insulin secretion. Disclosure M.Dickerson: None. D.Jacobson: None. P.Dadi: None. K.E.Zaborska: None. A.Y.Nakhe: None. C.Schaub: None. J.Dobson: None. N.M.Wright: None. J.Lynch: None. C.Scott: None. Funding American Diabetes Association (1-17-IBS-024) ; Vanderbilt Integrated Training in Engineering and Diabetes Grant (T32DK101003) , National Institutes of Health Grants (DK-097392 and DK-115620) , Juvenile Diabetes Research Foundation Grant (2-SRA-2019-701-S-B) , and a Pilot and Feasibility grant through the Vanderbilt Diabetes Research and Training Center Grant (P60-DK-20593) .

Background Scientists have amassed a wealth of microbiome datasets, making it possible to study microbes in biotic and abiotic systems on a population or planetary scale; however, this potential has not been fully realized given that the tools, datasets, and computation are available in diverse repositories and locations. To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community. Findings The iMicrobe platform brings together analysis tools and microbiome datasets by leveraging National Science Foundation–supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API, which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP). Conclusions iMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a web-based platform.

BackgroundScientists have amassed a wealth of microbiome datasets, making it possible to study microbes in biotic and abiotic systems on a population or planetary scale; however, this potential has not been fully realized given that the tools, datasets, and computation are available in diverse repositories and locations. To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community.FindingsThe iMicrobe platform brings together analysis tools and microbiome datasets by leveraging National Science Foundation–supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API, which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP).ConclusionsiMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a web-based platform.

Sex chromosomes have evolved many times in animals and studying these replicate evolutionary “experiments” can help broaden our understanding of the general forces driving the origin and evolution of sex chromosomes. However this plan of study has been hindered by the inability to identify the sex chromosome systems in the large number of species with cryptic, homomorphic sex chromosomes. Restriction site-associated DNA sequencing (RAD-seq) is a critical enabling technology that can identify the sex chromosome systems in many species where traditional cytogenetic methods have failed. Using newly generated RAD-seq data from 12 gecko species, along with data from the literature, we reinterpret the evolution of sex-determining systems in lizards and snakes and test the hypothesis that sex chromosomes can routinely act as evolutionary traps. We uncovered between 17 and 25 transitions among gecko sex-determining systems. This is approximately one-half to two-thirds of the total number of transitions observed among all lizards and snakes. We find support for the hypothesis that sex chromosome systems can readily become trap-like and show that adding even a small number of species from understudied clades can greatly enhance hypothesis testing in a model-based phylogenetic framework. RAD-seq will undoubtedly prove useful in eva luating other species for male or female heterogamety, particularly the majority of fish, amphibian, and reptile species that lack visibly heteromorphic sex chromosomes, and will significantly accelerate th ep ace of biological discovery.

© 2017 Elsevier Ltd Arsenic (As) is a geogenic contaminant affecting groundwater in geologically diverse systems globally. Arsenic release from aquifer sediments to groundwater is favored when biogeochemical conditions, especially oxidation-reduction (redox) potential, in aquifers fluctuate. The specific objective of this research is to identify the solid-phase sources and geochemical mechanisms of release of As in aquifers of the Des Moines Lobe glacial advance. The overarching concept is that conditions present at the aquifer-aquitard interfaces promote a suite of geochemical reactions leading to mineral alteration and release of As to groundwater. A microprobe X-ray absorption spectroscopy (μXAS) approach is developed and applied to rotosonic drill core samples to identify the solid-phase speciation of As in aquifer, aquitard, and aquifer-aquitard interface sediments. This approach addresses the low solid-phase As concentrations, as well as the fine-scale physical and chemical heterogeneity of the sediments. The spectroscopy data are analyzed using novel cosine-distance and correlation-distance hierarchical clustering for Fe 1s and As 1s μXAS datasets. The solid-phase Fe and As speciation is then interpreted using sediment and well-water chemical data to propose solid-phase As reservoirs and release mechanisms. The results confirm that in two of the three locations studied, the glacial sediment forming the aquitard is the source of As to the aquifer sediments. The results are consistent with three different As release mechanisms: (1) desorption from Fe (oxyhydr)oxides, (2) reductive dissolution of Fe (oxyhydr)oxides, and (3) oxidative dissolution of Fe sulfides. The findings confirm that glacial sediments at the interface between aquifer and aquitard are geochemically active zones for As. The diversity of As release mechanisms is consistent with the geographic heterogeneity observed in the distribution of elevated-As wells.

Shotgun metagenomics and marker gene amplicon sequencing can be used to directly measure or predict the functional repertoire of the microbiota en masse, but current methods do not readily estimate the functional capability of individual microorganisms. Here we present BugBase, an algorithm that predicts organism-level coverage of functional pathways as well as biologically interpretable phenotypes such as oxygen tolerance, Gram staining and pathogenic potential, within complex microbiomes using either whole-genome shotgun or marker gene sequencing data. We find BugBase’s organism-level pathway coverage predictions to be statistically higher powered than current ‘bag-of-genes’ approaches for discerning functional changes in both host-associated and environmental microbiomes.

Archaeological investigations of the Overlook Rockshelter in the Caves Branch River Valley of central Belize offer a unique view of ancient Maya cave ritual through the complete recovery and analysis of all artifacts within the site's two small activity areas. In general, the assemblage contains many of the same types of objects documented from other nearby caves and rockshelters. However, the nearly 1700 ceramics sherds showed almost no refits, demonstrating that sherds were deposited at the site individually, rather than as complete vessels. The human bone assemblage represents three or four individuals, with the majority of the bones comprising a single individual, and all of these were deposited as incomplete secondary interments. Analogies for this depositional behavior based on archaeological and ethnographic studies suggest that this rockshelter may represent a waypoint within a ritual circuit composed of multiple locations over which fragments of complete items such as ceramic vessels and secondary burials were spread.

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. Using simulated data we show that HOMINID has accuracy in identifying associated SNPs, and performs better compared to existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition, and can facilitate discovery of mechanisms controlling host-microbiome interactions.Availability and implementationSoftware, code, tutorial, installation and setup details, and synthetic data are available in the project homepage: https://github.com/blekhmanlab/hominid.Real dataset used here is from Blekhman et al. (Blekhman et al. 2015); 16S rRNA gene sequence data and OTU tables are available on the HMP DACC website (www.hmpdacc.org), and host genetic data are deposited in dbGaP under project number phs000228.

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCC(ij)(0)) and their z-transforms (z(ij)(0)) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of z(ij)(0) successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results.

Background The human gut microbiome is associated with the development of colon cancer, and recent studies have found changes in the microbiome in cancer patients compared to healthy controls. Studying the microbial communities in the tumor microenvironment may shed light on the role of host–bacteria interactions in colorectal cancer. Here, we highlight the major shifts in the colorectal tumor microbiome relative to that of matched normal colon tissue from the same individual, allowing us to survey the microbial communities in the tumor microenvironment and providing intrinsic control for environmental and host genetic effects on the microbiome. Methods We sequenced the microbiome in 44 primary tumor and 44 patient-matched normal colon tissue samples to determine differentially abundant microbial taxa These data were also used to functionally characterize the microbiome of the cancer and normal sample pairs and identify functional pathways enriched in the tumor-associated microbiota. Results We find that tumors harbor distinct microbial communities compared to nearby healthy tissue. Our results show increased microbial diversity in the tumor microenvironment, with changes in the abundances of commensal and pathogenic bacterial taxa, including Fusobacterium and Providencia. While Fusobacterium has previously been implicated in colorectal cancer, Providencia is a novel tumor-associated agent which has not been identified in previous studies. Additionally, we identified a clear, significant enrichment of predicted virulence-associated genes in the colorectal cancer microenvironment, likely dependent upon the genomes of Fusobacterium and Providencia. Conclusions This work identifies bacterial taxa significantly correlated with colorectal cancer, including a novel finding of an elevated abundance of Providencia in the tumor microenvironment. We also describe the predicted metabolic pathways and enzymes differentially present in the tumor-associated microbiome, and show an enrichment of virulence-associated bacterial genes in the tumor microenvironment. This predicted virulence enrichment supports the hypothesis that the microbiome plays an active role in colorectal cancer development and/or progression. Our results provide a starting point for future prognostic and therapeutic research with the potential to improve patient outcomes. Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0177-8) contains supplementary material, which is available to authorized users.

The human gut microbiota is impacted by host nutrition and health status and therefore represents a potentially adaptive phenotype influenced by metabolic and immune constraints. Previous studies contrasting rural populations in developing countries to urban industrialized ones have shown that industrialization is strongly correlated with patterns in human gut microbiota; however, we know little about the relative contribution of factors such as climate, diet, medicine, hygiene practices, host genetics, and parasitism. Here, we focus on fine-scale comparisons of African rural populations in order to (i) contrast the gut microbiota of populations inhabiting similar environments but having different traditional subsistence modes and either shared or distinct genetic ancestry, and (ii) examine the relationship between gut parasites and bacterial communities. Characterizing the fecal microbiota of Pygmy hunter-gatherers as well as Bantu individuals from both farming and fishing populations in Southwest Cameroon, we found that the gut parasite Entamoeba is significantly correlated with microbiome composition and diversity. We show that across populations, colonization by this protozoa can be predicted with 79% accuracy based on the composition of an individual's gut microbiota, and that several of the taxa most important for distinguishing Entamoeba absence or presence are signature taxa for autoimmune disorders. We also found gut communities to vary significantly with subsistence mode, notably with some taxa previously shown to be enriched in other hunter-gatherers groups (in Tanzania and Peru) also discriminating hunter-gatherers from neighboring farming or fishing populations in Cameroon., Author Summary The community of microorganisms inhabiting the gastrointestinal tract plays a critical role in determining human health. It’s been hypothesized that the industrialized lifestyle, marked by a diet rich in processed foods, higher use of antibiotics, increased hygiene, and exposure to various chemicals, has altered microbiota in ways that are harmful. Studies have addressed this by comparing rural and industrialized populations, and have found that they systematically vary in their gut microbiome composition. Nevertheless, the relative influence of host genetics, diet, climate, medication, hygiene practices, and parasitism is still not clear. In addition, microbial variation between nearby human populations has not been explored in depth. Moreover, The World Health Organization estimates that 24% of the world’s population, concentrated in developing countries, is infected with gut parasites. Despite this, and evidence for direct interactions between the immune system and both gut parasites and bacteria, we know relatively little about the relationship between gut helminths, protozoa, and bacteria. In our study, we aimed to address some of this complexity. To do so, we characterized the gut microbial communities and parasites from Pygmy hunter-gatherer and Bantu farming and fishing populations from seven locations in the rainforest of Southwest Cameroon. We found that both subsistence mode and the presence of the gut protozoa, Entamoeba, were significantly correlated with microbiome composition. These findings support previous studies demonstrating diet is an important determinant of gut microbiota, and further show that this pattern holds true at a local scale, in traditional societies inhabiting a similar environment. Additionally, we show a significant relationship between a common human parasite (Entamoeba) and gut bacterial community composition, suggesting potential important interactions between the immune system, gut bacteria, and gut parasites, highlighting the need for more hierarchical cross population studies that include parasitism as potential factor influencing gut microbiota dynamics.

We have previously shown differential regulation of components of the Retinoic acid (RA) pathway in Xenopus tadpole hindlimb regeneration. RA is thought to act as a morphogen, providing positional information during development and regeneration. We have investigated the regulation of genes involved in RA synthesis, catabolism, and binding in developing and regenerating Xenopus limbs. Our data indicate that RA is synthesised by Raldh2 in proximal cells during limb bud outgrowth. Furthermore, Cyp26b is expressed transiently in the progress zone of developing limbs and the blastema of regenerating limbs suggesting degradation of RA occurs in both processes. The RA-binding protein Crabp2 is also upregulated during regeneration. We summarise this data to predict the presence of evolving gradients of RA in the developing amphibian limb. Thus, RA from the stump cells could be responsible for the establishment of proximal-distal pattern during limb regeneration, as predicted by classical studies.

Retinoic acid (RA) is a known teratogen that is also required endogenously for normal development of the embryo. RA can act as a morphogen, through direct binding to receptors and RA response elements in the genome, and classical studies of limb development and regeneration in amphibians have shown that it is likely to provide positional information. Availability of RA depends on both metabolic synthesis and catabolic degradation, and specific binding proteins act to further modulate the binding of RA to response elements. Here, we describe the expression of seven genes involved in metabolism (Raldh1-3), catabolism (Cyp26a and b) and binding of RA (Crabp1 and 2) during organogenesis in the clawed frog Xenopus laevis. Taken together, this data indicates regions of the embryo that could be affected by RA mediated patterning, and identifies some differences with other vertebrates.

We used ultra-high field (7 T) fMRI and parallel imaging to scan the superior parietal lobule (SPL) of human subjects as they mentally traversed a maze path in one of four directions (up, down, left, right). A counterbalanced design for maze presentation and a quasi-isotropic voxel (1.46 x 1.46 x 2 mm thick) collection were implemented. Fifty-one percent of single voxels in the SPL were tuned to the direction of the maze path. Tuned voxels were distributed throughout the SPL, bilaterally. A nearest neighbor analysis revealed a "honeycomb" arrangement such that voxels tuned to a particular direction tended to occur in clusters. Three-dimensional (3D) directional clusters were identified in SPL as oriented centroids traversing the cortical depth. There were 13 same-direction clusters per hemisphere containing 22 voxels per cluster, on the average; the mean nearest-neighbor, same-direction intercluster distance was 9.4 mm. These results provide a much finer detail of the directional tuning in SPL, as compared to those obtained previously at 4 T (Gourtzelidis et al. Exp Brain Res 165:273-282, 2005). The more accurate estimates of quantitative clustering parameters in 3D brain space in this study were made possible by the higher signal-to-noise and contrast-to-noise ratios afforded by the higher magnetic field of 7 T as well as the quasi-isotropic design of voxel data collection.

We calculated voxel-by-voxel pairwise crosscorrelations between prewhitened resting-state BOLD fMRI time series recorded from 60 cortical areas (30 per hemisphere) in 18 human subjects (nine women and nine men). Altogether, more than a billion-and-a-quarter pairs of BOLD time series were analyzed. For each pair, a crosscorrelogram was computed by calculating 21 crosscorrelations, namely at zero lag ± 10 lags of 2 s duration each. For each crosscorrelogram, in turn, the crosscorrelation with the highest absolute value was found and its sign, value, and lag were retained for further analysis. In addition, the crosscorrelations at zero lag (irrespective of the location of the peak) were also analyzed as a special case. Based on known varying density of anatomical connectivity, we distinguished four general brain groups for which we derived summary statistics of crosscorrelations between voxels within an area (group I), between voxels of paired homotopic areas across the two hemispheres (group II), between voxels of an area and all other voxels in the same (ipsilateral) hemisphere (group III), and voxels of an area and all voxels in the opposite (contralateral) hemisphere (except those in the homotopic area) (group IV). We found the following. (a) Most of the crosscorrelogram peaks occurred at zero lag, followed by ± 1 lag; (b) over all groups, positive crosscorrelations were much more frequent than negative ones; (c) average crosscorrelation was highest for group I, and decreased progressively for groups II-IV; (d) the ratio of positive over negative crosscorrelations was highest for group I and progressively smaller for groups II-IV; (e) the highest proportion of positive crosscorrelations (with respect to all positive ones) was observed at zero lag; and (f) the highest proportion of negative crosscorrelations (with respect to all negative ones) was observed at lag = 2. These findings reveal a systematic pattern of crosscorrelations with respect to their sign, magnitude, lag and brain group, as defined above. Given that these groups were defined along a qualitative gradient of known overall anatomical connectivity, our results suggest that functional interactions between two voxels may simply reflect the density of such anatomical connectivity between the areas to which the voxels belong.