Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between ...typically developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD or TD controls into germ-free mice and reveal that colonization with ASD microbiota is sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and modulates neuronal excitability in the brain. We propose that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.
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•Mice harboring human ASD, but not TD, microbiomes exhibit ASD-like behaviors•ASD and TD microbiota produce differential metabolome profiles in mice•Extensive alternative splicing of risk genes in brains of mice with ASD microbiota•BTBR mice treated with 5AV or taurine improved repetitive and social behaviors
Repetitive and social behavioral abnormalities in mice with microbiomes from patients with autism spectrum disorder can be corrected by the administration of specific metabolites.
Inflammatory bowel disease (IBD) is characterized by flares of inflammation with a periodic need for increased medication and sometimes even surgery. The aetiology of IBD is partly attributed to a ...deregulated immune response to gut microbiome dysbiosis. Cross-sectional studies have revealed microbial signatures for different IBD subtypes, including ulcerative colitis, colonic Crohn's disease and ileal Crohn's disease. Although IBD is dynamic, microbiome studies have primarily focused on single time points or a few individuals. Here, we dissect the long-term dynamic behaviour of the gut microbiome in IBD and differentiate this from normal variation. Microbiomes of IBD subjects fluctuate more than those of healthy individuals, based on deviation from a newly defined healthy plane (HP). Ileal Crohn's disease subjects deviated most from the HP, especially subjects with surgical resection. Intriguingly, the microbiomes of some IBD subjects periodically visited the HP then deviated away from it. Inflammation was not directly correlated with distance to the healthy plane, but there was some correlation between observed dramatic fluctuations in the gut microbiome and intensified medication due to a flare of the disease. These results will help guide therapies that will redirect the gut microbiome towards a healthy state and maintain remission in IBD.
Biological tissues exhibit complex spatial heterogeneity that directs the functions of multicellular organisms. Quantifying protein expression is essential for elucidating processes within complex ...biological assemblies. Imaging mass spectrometry (IMS) is a powerful emerging tool for mapping the spatial distribution of metabolites and lipids across tissue surfaces, but technical challenges have limited the application of IMS to the analysis of proteomes. Methods for probing the spatial distribution of the proteome have generally relied on the use of labels and/or antibodies, which limits multiplexing and requires a priori knowledge of protein targets. Past efforts to make spatially resolved proteome measurements across tissues have had limited spatial resolution and proteome coverage and have relied on manual workflows. Here, we demonstrate an automated approach to imaging that utilizes label-free nanoproteomics to analyze tissue voxels, generating quantitative cell-type-specific images for >2000 proteins with 100-µm spatial resolution across mouse uterine tissue sections preparing for blastocyst implantation.
The dominant fungi in arid grasslands and shrublands are members of the Ascomycota phylum. Ascomycota fungi are important drivers in carbon and nitrogen cycling in arid ecosystems. These fungi play ...roles in soil stability, plant biomass decomposition, and endophytic interactions with plants. They may also form symbiotic associations with biocrust components or be latent saprotrophs or pathogens that live on plant tissues. However, their functional potential in arid soils, where organic matter, nutrients and water are very low or only periodically available, is poorly characterized.
Five Ascomycota fungi were isolated from different soil crust microhabitats and rhizosphere soils around the native bunchgrass Pleuraphis jamesii in an arid grassland near Moab, UT, USA. Putative genera were Coniochaeta, isolated from lichen biocrust, Embellisia from cyanobacteria biocrust, Chaetomium from below lichen biocrust, Phoma from a moss microhabitat, and Aspergillus from the soil. The fungi were grown in replicate cultures on different carbon sources (chitin, native bunchgrass or pine wood) relevant to plant biomass and soil carbon sources. Secretomes produced by the fungi on each substrate were characterized. Results demonstrate that these fungi likely interact with primary producers (biocrust or plants) by secreting a wide range of proteins that facilitate symbiotic associations. Each of the fungal isolates secreted enzymes that degrade plant biomass, small secreted effector proteins, and proteins involved in either beneficial plant interactions or virulence. Aspergillus and Phoma expressed more plant biomass degrading enzymes when grown in grass- and pine-containing cultures than in chitin. Coniochaeta and Embellisia expressed similar numbers of these enzymes under all conditions, while Chaetomium secreted more of these enzymes in grass-containing cultures.
This study of Ascomycota genomes and secretomes provides important insights about the lifestyles and the roles that Ascomycota fungi likely play in arid grassland, ecosystems. However, the exact nature of those interactions, whether any or all of the isolates are true endophytes, latent saprotrophs or opportunistic phytopathogens, will be the topic of future studies.
The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples ...containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.
Abstract
Background
Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. ...However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets.
Results
We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality.
Conclusions
Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.
Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This ...study evaluates whether hourly levels of fine particulate matter (PM.sub.2.5) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV.sub.1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM.sub.2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM.sub.2.5, DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM.sub.2.5, but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM.sub.2.5, had a significant association with FEV.sub.1 . When DBGT and PM.sub.2.5 exposures were placed in the same model, the strongest association between cumulative PM.sub.2.5 exposures and the use of rescue bronchodilator was identified at the 0-24 hours (OR = 1.030; 95% CI = 1.012-1.049; p-value = 0.001) and 0-48 hours (OR = 1.030; 95% CI = 1.013-1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (beta = 3.257; SE = 0.879; p-value>0.001) and 0-6 hours (beta = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV.sub.1 . No significant interactions between DBGT and PM.sub.2.5 were observed for rescue bronchodilator use or FEV.sub.1. Conclusions Short-term increases in PM.sub.2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV.sub.1). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM.sub.2.5 and DBGT on lung function in asthmatics.
Soil organic matter (SOM) dynamics are central to soil biogeochemistry and fertility. The retention of SOM is governed initially by interactions with minerals, which mediate the sorption of ...chemically diverse organic matter (OM) molecules via distinct surface areas and chemical functional group availabilities. Unifying principles of mineral-OM interactions remain elusive because of the multi-layered nature of biochemical-mineral interactions that contribute to soil aggregate formation and the heterogeneous nature of soils among ecosystems. This study sought to understand how soil mineralogy as well as nitrogen (N) enrichment regulate OM composition in grassland soils. Using a multi-site grassland experiment, we demonstrate that the composition of mineral-associated OM depended on the clay content and specific mineral composition in soils across the sites. With increasing abundance of ferrihydrite (Fh) across six different grassland locations, OM in the hydrophobic zone became more enriched in lipid- and protein-like compounds, whereas the kinetic zone OM became more enriched in lignin-like molecules. These relationships suggest that the persistence of various classes of OM in soils may depend on soil iron mineralogy and provide experimental evidence to support conceptual models of zonal mineral-OM associations. Experimental N addition disrupted the accumulation of protein-like molecules in the hydrophobic zone and the positive correlation of lignin-like molecules in the kinetic zone with Fh content, compared to unfertilized soils. These data suggest that mineralogy and clay content together influence the chemical composition not only of mineral-associated OM, but also of soluble compounds within the soil matrix. If these relationships are prevalent over larger spatial and temporal scales, they provide a foundation for understanding SOM cycling and persistence under a variety of environmental contexts.
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•Beyond clay content, mineralogy strongly controlled the composition of MAOM.•Ferrihydrite accumulated proteins and lipids in the hydrophobic zone of MAOM.•The mineral core influenced biochemical persistence of OM in the kinetic zone.•Nitrogen fertilization altered carbon chemistry and organo-mineral interactions.
Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that ...data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.
A comprehensive understanding of host dependency factors for SARS-CoV-2 remains elusive. Here, we map alterations in host lipids following SARS-CoV-2 infection using nontargeted lipidomics. We find ...that SARS-CoV-2 rewires host lipid metabolism, significantly altering hundreds of lipid species to effectively establish infection. We correlate these changes with viral protein activity by transfecting human cells with each viral protein and performing lipidomics. We find that lipid droplet plasticity is a key feature of infection and that viral propagation can be blocked by small-molecule glycerolipid biosynthesis inhibitors. We find that this inhibition was effective against the main variants of concern (alpha, beta, gamma, and delta), indicating that glycerolipid biosynthesis is a conserved host dependency factor that supports this evolving virus.
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