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Rhizosphere microbes influence host circadian clock function

The circadian clock is an important determinant of individual fitness that is entrained by local conditions. In addition to known abiotic inputs that entrain the circadian clock, individual pathogenic soil bacteria affect the circadian period of plant hosts. Yet, in nature, plants interact with diverse microbial communities including hundreds to thousands of microbial taxa, and the effect of these communities on clock function remains unclear. In Arabidopsis thaliana, we used diverse rhizosphere inoculates and both wild-type and clock mutant genotypes to test the effect of complex rhizosphere microbial communities on the host circadian clock. Host plants with an intact rhizosphere microbiome expressed a circadian period that was closer to 24 hrs in duration and significantly shorter (by 60 minutes on average) relative to plants grown with a disrupted microbiome. Wild-type host genotypes differed significantly in clock sensitivity to microbiome treatments, where the effect was most pronounced in the Landsberg erecta genotype and least in the Columbia genotype. Rhizosphere microbes collected from a host genotype with a short-period phenotype (toc1-21) and used as inoculate significantly shortened the long-period phenotype of the ztl-1 clock mutant genotype. The results indicate that complex rhizosphere microbial communities significantly affect host clock function.

plant biology

Crystal structure of m4-1BB/4-1BBL complex reveals an unusual dimeric ligand that undergoes structural changes upon receptor binding.

The interaction between the 4-1BB and its ligand 4-1BBL provides co-stimulatory signals for T cell activation and proliferation, but differences in the mouse and human molecules might result in differential engagement of this pathway. Here, we report the crystal structure of mouse 4-1BBL and of the mouse 4-1BB/4-1BBL complex, together provide insights into the molecular recognition of the cognate receptor by m4-1BBL. In contrast to all human or mouse TNF ligands that form non-covalent mostly trimeric assemblies, the m4-1BBL structure formed a novel disulfide linked dimeric assembly. The structure showed that certain differences in the amino acid composition along the intramolecular interface, together with two specific residues (Cys 246 and Ser 256) that are exclusively present in m4-1BBL, are responsible for unique dimerization. Unexpectedly, upon binding to m4-1BB, m4-1BBL undergoes structural changes within each protomer, in addition the individual m4-1BBL protomers rotate with respect to each other, leading to a different dimerization interface with more inter-subunit interactions. In the m4-1BB/4-1BBL complex, each receptor monomer binds exclusively to a single ligand subunit with contributions of cysteine-rich domain (CRD) 1, CRD2 and CRD3. Furthermore, structure-guided mutagenesis of the binding interface revealed that novel binding interactions with the GH loop, rather than the DE loop, are energetically critical and define the species based receptor selectivity for m4-1BBL. A comparison with the human 4-1BB/4-1BBL complex highlighted several differences between the ligand and receptor binding interfaces and provide an explanation for the absence of inter species cross-reactivity between human and mouse 4-1BB and 4-1BBL molecules.

immunology

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.

genomics

The COMA complex is required for positioning Ipl1 activity proximal to Cse4 nucleosomes in budding yeast

Kinetochores are macromolecular protein complexes assembled on centromeric chromatin that ensure accurate chromosome segregation by linking DNA to spindle microtubules and integrating safeguard mechanisms. A kinetochore-associated pool of Ipl1Aurora B kinase, a subunit of the chromosomal passenger complex (CPC), was previously implicated in feedback control mechanisms. To study the kinetochore subunit connectivity built on budding yeast point centromeres and its CPC interactions we performed crosslink-guided in vitro reconstitution. The Ame1/Okp1CENP-U/Q heterodimer, forming the COMA complex with Ctf19/Mcm21CENP-P/O, selectively bound Cse4CENP-A nucleosomes through the Cse4 N-terminus and thereby establishes a direct link to the outer kinetochore MTW1 complex. The Sli15/Ipl1INCENP/Aurora B core-CPC interacted with COMA through the Ctf19 C-terminus, and artificial tethering of Sli15 to Ame1/Okp1 rescued synthetic lethality upon Ctf19/Mcm21 deletion in a Sli15 centromere-targeting deficient mutant. This study reveals characteristics of the inner kinetochore architecture assembled at point centromeres and the relevance of its Sli15/Ipl1 interaction for CPC function.

cell biology

A simple approximation to bias in gene-environment interaction estimates when a case might not be the case

Case-control genetic association studies are often used to examine the role of the genetic basis in complex diseases, such as cancer and neurodegenerative diseases. The role of the genetic basis might vary by non-genetic (environmental) measures, what is traditionally defined as gene-environment interactions (GxE). A commonly overlooked complication is that the set of clinically diagnosed cases might be contaminated by a subset with a nuisance pathologic state that presents with the same symptoms as the pathologic state of interest. The genetic basis of the pathologic state of interest might differ from that of the nuisance pathologic state. Often frequencies of the pathologically defined states within the clinically diagnosed set of cases vary by the environment. We derive a simple and general approximation to bias in GxE parameter estimates when presence of the nuisance pathologic state is ignored. We then perform extensive simulation studies to show that ignoring presence of the nuisance pathologic state can result in substantial bias in GxE estimates and that the approximation we derived is reasonably accurate in finite samples. We demonstrate the applicability of the proposed approximation in a study of Alzheimers disease.

genetics

Comparative Pathway Integrator: a framework of meta-analytic integration of multiple transcriptomic studies for consensual and differential pathway analysis

MotivationPathway analysis provides a knowledge-driven approach to interpret differentially expressed genes associated with disease status. Many tools have been developed to analyze a single study. When multiple studies of different conditions are jointly analyzed, novel integrative tools are needed. In addition, pathway redundancy issue introduced by combining public pathway databases hinders knowledge discovery.\n\nMethods and ResultsWe present a meta-analytic integration tool, Comparative Pathway Integrator (CPI), to address these issues using adaptively weighted Fishers method to discover consensual and differential enrichment patterns, consensus clustering to reduce pathway redundancy, and a novel text mining algorithm to assist interpretation of the pathway clusters. We applied CPI to jointly analyze six psychiatric disorder transcriptomic studies to demonstrate its effectiveness, and found functions confirmed by previous biological studies as well novel enrichment patterns.\n\nAvailabilityCPI is accessible online: http://tsenglab.biostat.pitt.edu/software.htm.\n\nContactxiangruz@andrew.cmu.edu

bioinformatics

Correlation between the oral microbiome and brain resting state connectivity in smokers

Recent studies have shown a critical role of the gastrointestinal microbiome in brain and behavior via the complex gut-microbiome-brain axis, however, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli in the oral microenvironment such as smoking. Additionally, given the complex structural and functional networks in brain system, our knowledge about the relationship between microbiome and brain function in specific brain circuits is still very limited. In this pilot work, we leveraged next generation microbial sequencing with functional neuroimaging techniques to enable the delineation of microbiome-brain network links as well as their relationship to cigarette smoking. Thirty smokers and 30 age- and sex- matched non-smokers were recruited for measuring both microbial community and brain functional networks. Statistical analyses were performed to demonstrate the influence of smoking on the abundance of the constituents within the oral microbial community and functional network connectivity among brain regions as well as the associations between microbial shifts and the brain functional network connectivity alternations. Compared to non-smokers, we found a significant decrease in beta diversity (p = 6x10-3) in smokers and identified several classes (Betaproteobacteria, Spirochaetia, Synergistia, and Mollicutes) as having significant alterations in microbial abundance. Taxonomic analyses demonstrate that the microbiota with altered abundance are mainly involved in pathways related to cell processes, DNA repair, immune system, and neurotransmitters signaling. One brain functional network connectivity component was identified to have a significant difference between smokers and nonsmokers (p = 0.033), mainly including connectivity between brain default network and other task-positive networks. The brain functional component was also significantly associated with some smoking related oral microbiota, suggesting a potential link between smoking-induced oral microbiome dysbiosis and brain functional connectivity, possibly through immunological and neurotransmitter signaling pathways. This work is the first attempt to link oral microbiome and brain functional networks, and provides support for future work in characterizing the role of oral microbiome in mediating smoking effects on brain activity.

microbiology

A direct comparison of genome alignment and transcriptome pseudoalignment

MotivationGenome alignment of reads is the first step of most genome analysis workflows. In the case of RNA-Seq, transcriptome pseudoalignment of reads is a fast alternative to genome alignment, but the different \"coordinate systems\" of the genome and transcriptome have made it difficult to perform direct comparisons between the approaches.\n\nResultsWe have developed tools for converting genome alignments to transcriptome pseudoalignments, and conversely, for projecting transcriptome pseudoalignments to genome alignments. Using these tools, we performed a direct comparison of genome alignment with transcriptome pseudoalignment. We find that both approaches produce similar quantifications. This means that for many applications genome alignment and transcriptome pseudoalignment are interchangeable.\n\nAvailability and Implementationbam2tcc is a C++14 software for converting alignments in SAM/BAM format to transcript compatibility counts (TCCs) and is available at https://github.com/pachterlab/bam2tcc. kallisto genomebam is a user option of kallisto that outputs a sorted BAM file in genome coordinates as part of transcriptome pseudoalignment. The feature has been released with kallisto v0.44.0, and is available at https://pachterlab.github.io/kallisto/.\n\nSupplementary MaterialN/A\n\nContactLior Pachter (lpachter@caltech.edu)

bioinformatics

Value-based Decision Making Takes Place in the Action Domain in the Prefrontal Cortex

Value-based decision making is a process in which humans or animals maximize their gain by selecting appropriate options and performing the corresponding actions to acquire them. Whether the evaluation process of the options in the brain can be independent from their action contingency has been hotly debated. To address the question, we trained rhesus monkeys to make decisions by integrating evidence and studied whether the integration occurred in the stimulus or the action domain in the brain. After the monkeys learned the task, we recorded both from the orbitofrontal (OFC) and dorsolateral prefrontal (DLPFC) cortices. We found that the OFC neurons encoded the value associated with the single piece of evidence in the stimulus domain. Importantly, the representations of the value in the OFC was transient and the information was not integrated across time for decisions. The integration of evidence was observed only in the DLPFC and only in the action domain. We further used a neural network model to show how the stimulus-to-action transition of value information may be computed in the DLPFC. Our results indicated that the decision making in the brain is computed in the action domain without an intermediate stimulus-based decision stage.

neuroscience

Using experimental data and information criteria to guide model selection for reaction--diffusion problems in mathematical biology

Reaction-diffusion models describing the movement, reproduction and death of individuals within a population are key mathematical modelling tools with widespread applications in mathematical biology. A diverse range of such continuum models have been applied in various biological contexts by choosing different flux and source terms in the reaction-diffusion framework. For example, to describe collective spreading of cell populations, the flux term may be chosen to reflect various movement mechanisms, such as random motion (diffusion), adhesion, haptotaxis, chemokinesis and chemotaxis. The choice of flux terms in specific applications, such as wound healing, is usually made heuristically, and rarely is it tested quantitatively against detailed cell density data. More generally, in mathematical biology, the questions of model validation and model selection have not received the same attention as the questions of model development and model analysis. Many studies do not consider model validation or model selection, and those that do often base the selection of the model on residual error criteria after model calibration is performed using nonlinear regression techniques. In this work, we present a model selection case study, in the context of cell invasion, with a very detailed experimental data set. Using Bayesian analysis and information criteria, we demonstrate that model selection and model validation should account for both residual errors and model complexity. These considerations are often overlooked in the mathematical biology literature. The results we present here provide a clear methodology that can be used to guide model selection across a range of applications. Furthermore, the case study we present provides a clear example where neglecting the role of model complexity can give rise to misleading outcomes.

biophysics

High throughput droplet single-cell Genotyping of Transcriptomes (GoT) reveals the cell identity dependency of the impact of somatic mutations

Defining the transcriptomic identity of clonally related malignant cells is challenging in the absence of cell surface markers that distinguish cancer clones from one another or from admixed non-neoplastic cells. While single-cell methods have been devised to capture both the transcriptome and genotype, these methods are not compatible with droplet-based single-cell transcriptomics, limiting their throughput. To overcome this limitation, we present single-cell Genotyping of Transcriptomes (GoT), which integrates cDNA genotyping with high-throughput droplet-based single-cell RNA-seq. We further demonstrate that multiplexed GoT can interrogate multiple genotypes for distinguishing subclonal transcriptomic identity. We apply GoT to 26,039 CD34+ cells across six patients with myeloid neoplasms, in which the complex process of hematopoiesis is corrupted by CALR-mutated stem and progenitor cells. We define high-resolution maps of malignant versus normal hematopoietic progenitors, and show that while mutant cells are comingled with wildtype cells throughout the hematopoietic progenitor landscape, their frequency increases with differentiation. We identify the unfolded protein response as a predominant outcome of CALR mutations, with significant cell identity dependency. Furthermore, we identify that CALR mutations lead to NF-{kappa}B pathway upregulation specifically in uncommitted early stem cells. Collectively, GoT provides high-throughput linkage of single-cell genotypes with transcriptomes and reveals that the transcriptional output of somatic mutations is heavily dependent on the native cell identity.

cancer biology

Nanopore formation in the cuticle of the insect olfactory sensillum

Insects sense odorants through small (50-200-nm diameter) pores in the cuticle covering the olfactory sensilla. These nanopores serve as a filter, preventing the entry of larger airborne particles and limiting water loss. Here we show that the nanopores in Drosophila originate from a curved ultrathin film formed in the outermost layer of the cuticle, secreted from specialized plasma membrane protrusions. The gore-tex/Osiris23 gene, encoding an endosomal protein, is required for nanopore formation and odor receptivity, and is expressed specifically in developing olfactory shaft cells. The 24-member Osiris gene family is expressed in various cuticle-secreting cells, and is found only in insect genomes. Some Osiris mutants show defective cuticle-associated functions, suggesting that Osiris genes may provide a platform for investigating functional surface nano-fabrication in insects.\n\nOne Sentence SummaryAn insect-specific endosomal protein promotes the formation of nano-scale pore structures of the apical extracellular matrix.

developmental biology

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity, while contributing to health and disease in human populations

Regulatory DNA has the potential to be adaptive, and large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans. For the first time, a comprehensive study of adaptive eQTLs is possible. Many eQTLs have large allele frequency differences between populations, and these differences can be due to natural selection. Here, we combined population branch statistics with tissue-specific eQTL data to identify positively selected loci in human populations. Adaptive eQTLs tend to affect fewer tissues than non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results suggest that pleiotropy can inhibit adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we find that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for adaptive outliers. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. These results reveal tissues that have been the targets of adaptation during the last 100,000 years of human evolution. The strongest adaptive signal in many regions of the human genome is an eQTL, including an eQTL associated with the Duffy blood group and malaria resistance. Scans of selection also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that adaptive eQTLs have played an important role in human evolution.

genomics

Roles of Polycomb gene EED in pathogenesis and prognosis of acute myeloid leukemia and diffuse large B cell lymphoma

In this study, we performed correlation analysis of polycomb gene EED and hematologic malignancies using the omics and clinical data of acute myeloid leukemia (LAML) and diffuse large B-Cell lymphoma (DLBC) from TCGA database. We found that: (1) High EED mRNA level was associated with poor prognosis and high CALGB cytogenetics risk of LAML patients. (2) EED mRNA level in DLBC cancer cells was higher than control cells. (3) EED gene expression could be regulated by both copy number alterations and DNA methylation. (4) Additionally, there were different EED co-expression genes nets in the two kinds of hematologic malignancies. In all, we confirmed that there are potential clinical significance of EED gene in pathogenesis and prognosis of hematologic malignancies.

systems biology

Experiments and simulations on short chain fatty acid production in a colonic bacterial community

Understanding how production of specific metabolites by gut microbes is modulated by interactions with surrounding species and by environmental nutrient availability is an important open challenge in microbiome research. As part of this endeavor, this work explores interactions between F. prausnitzii, a major butyrate producer, and B. thetaiotaomicron, an acetate producer, under three different in vitro media conditions in monoculture and coculture. In silico Genome-scale dynamic flux balance analysis (dFBA) models of metabolism in the system using COMETS (Computation of Microbial Ecosystems in Time and Space) are also tested for explanatory, predictive and inferential power. Experimental findings indicate enhancement of butyrate production in coculture relative to F. prausnitzii monoculture but defy a simple model of monotonic increases in butyrate production as a function of acetate availability in the medium. Simulations recapitulate biomass production curves for monocultures and accurately predict the growth curve of coculture total biomass, using parameters learned from monocultures, suggesting that the model captures some aspects of how the two bacteria interact. However, a comparison of data and simulations for environmental acetate and butyrate changes suggest that the organisms adopt one of many possible metabolic strategies equivalent in terms of growth efficiency. Furthermore, the model seems not to capture subsequent shifts in metabolic activities observed experimentally under low-nutrient regimes. Some discrepancies can be explained by the multiplicity of possible fermentative states for F. prausnitzii. In general, these results provide valuable guidelines for design of future experiments aimed at better determining the mechanisms leading to enhanced butyrate in this ecosystem.\n\nImportanceStudies associating butyrate levels with human colonic health have inspired research on therapeutic microbiota consortia that would optimize butyrate production if implanted in the human colon. Faecalibacterium prausnitzii is commonly observed in human fecal samples and produces butyrate as a product of fermentation. Previous studies indicate that Bacteroides thetaiotaomicron, also commonly found in human fecal samples, may enhance butyrate production in F. prausnitzi when the two species are co-localized. This possibility is investigated here under different environmental conditions using experimental methods paired with computer simulations of the whole metabolism of bacterial cells. Initial findings indicate that interactions between these two species result in enhanced butyrate production. However, results also paint a nuanced picture, suggesting the existence of a multiplicity of equivalently efficient metabolic strategies and complex interactions between acetate and butyrate production in these species that appear highly dependent on specific environmental conditions.

systems biology

Dietary lysozyme supplement alters serum biochemical makers and milk metabolite profile of sows via gut microbiota

Lysozyme is an important antimicrobial agent with promising future in replacing antibiotics in livestok production. The aim of current study was to determine variations in sows gut microbiota, serum immunity and breast milk metabolite profile mediated by lysozyme supplementation.Thirty-six pregnant sows were assigned to a control group without supplementation and two treatments with 0.5 g/kg and 1.0 g/kg lysozyme provided in formula feed for 21days. Microbiota analysis based on 16s RNA high-throughput sequencing and untargeted liquid chromatography tandem mass spectrometry were applied and combined in analysis. Serum biochemical indicators and immunoglobulins were also determined. Sows received 1.0kg/t lyszoyme treatment shown significant redution in microbial diversity. Spirochaetes, Euryarchaeota and Actinobacteria significantly increased while Firmicutes showed a remarkable reduction in 1.0kg/t treated group compared with control. Pyrimidine metabolism,Purine metabolism and Amino acid related enzymes were significantly upregulated in 1.0kg/t lysozyme treated group. The richness of gram-positive bacteria were significantly down-regulated by lysozyme treatments. Serum aspartate transaminase (AST) activity was significantly un-regulated. Serum IgM levels were significantly higher in the 1.0 kg/t group compared with control, while IgA levels was significantly lower in 1.0kg/t group. Over thirty metabolites from sows breast milk including L-Glutamine,creatine and L-Arginine were sigficantly altered by lysozyme treatment. There existed crucial correlations among gut microbiota, serum immunity and breast milk metabolites where lactobacillus and prevotella may play a key role in lysozyme mediated host-microbial interactions. Overall, lysozyme supplementation could effectively improve the composition, metabolic functions and phenotypes of sows gut microbiota and it also benefit sows with better immune status and breast milk composition.\n\nImportanceEnteric infections caused by pathogens have a significant negative effect on neonatal survival and animal health in swine production. The application of antibiotics in feeds at subtherapeutic levels could improve performance and overall health and is used extensively throughout the industry. However, abuse of antibiotics is contributing to the high level of drug resistance in microbial communities and rising concerns regarding human health. Here, we revealed that lysozyme supplementation could effectively improve the composition, metabolic functions and phenotypes of sows gut microbiota and it also benefit sows with better immune status and breast milk composition. These findings confirmed that lysozyme could be a suitable alternative to antibiotics in swine production.

microbiology

Response of Australian pied oystercatchers Haematopus longirostris to increasing abundance of the beach bivalve prey Donax deltoides

This study measured the response of Australian pied oystercatchers Haematopus longirostris on South Ballina Beach, New South Wales, Australia during a recovery in the stock of the primary prey species Donax deltoides, a large beach clam and commonly known as the pipi. It was predicted that oystercatcher counts would increase when pipi abundance increased (numerical response) and that oystercatcher feeding rates would also increase (functional response). Between Oct 2009 and Mar 2015, mean pipi density increased from c. zero to 30 pipis/m2. Mean oystercatcher feeding rates increased to an asymptote of c. 0.26 pipis/min. Breeding season mean counts of adult-plumage oystercatchers increased from 23 to 43, largely driven by non-territorial birds. Prey size selection was absent, both among different prey types and among pipis > 20 mm. This report provides some insights into the feeding ecology of oystercatchers on sandy ocean beaches that should be valuable in planning future studies.

ecology

MicroRNAs buffer genetic variation at specific temperatures during embryonic development

Successful embryogenesis requires the coordination of developmental events. Perturbations, such as environmental changes, must be buffered to ensure robust development. However, how such buffering occurs is currently unknown in most developmental systems. Here, we demonstrate that seven miRNAs are differentially expressed during Drosophila embryogenesis at varying temperatures within natural physiological ranges. Lack of miR-3-309, -31a, -310c, -980 or -984c causes developmental delays specifically at a given temperature. Detailed analysis on miR-310c and -984c shows that their targets are typically mis-expressed in mutant backgrounds, with phenotypes more pronounced at temperatures where miRNAs show highest expression in wild-type embryos. Our results show that phenotypes may arise at specific temperatures while remaining silent at others, even within typical temperature ranges. Our work uncovers that miRNAs mask genetic variation at specific temperatures to increase embryonic robustness, highlighting another layer of complexity in miRNA expression.

developmental biology