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InWeb_InBioMap (InWeb_IM for short) is a scored, integrated human protein–protein interaction network resource aggregated from public, experimentally determined protein–protein interactions. The resource enables functional interpretation of large-scale genomics data. Genome-scale human protein–protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein–protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

β-Mannans are plant cell wall polysaccharides that are commonly found in human diets. However, a mechanistic understanding into the key populations that degrade this glycan is absent, especially for the dominant Firmicutes phylum. Here, we show that the prominent butyrate-producing Firmicute Roseburia intestinalis expresses two loci conferring metabolism of β-mannans. We combine multi-“omic” analyses and detailed biochemical studies to comprehensively characterize loci-encoded proteins that are involved in β-mannan capturing, importation, de-branching and degradation into monosaccharides. In mixed cultures, R. intestinalis shares the available β-mannan with Bacteroides ovatus , demonstrating that the apparatus allows coexistence in a competitive environment. In murine experiments, β-mannan selectively promotes beneficial gut bacteria, exemplified by increased R. intestinalis , and reduction of mucus-degraders. Our findings highlight that R. intestinalis is a primary degrader of this dietary fiber and that this metabolic capacity could be exploited to selectively promote key members of the healthy microbiota using β-mannan-based therapeutic interventions. How dietary β-mannans are utilized by gut Gram-positive bacteria is unclear. Here, the authors uncover the enzymatic pathway for β-mannan metabolism in Roseburia intestinalis and show that these polysaccharides promote beneficial gut bacteria, highlighting a potential for β-mannan-based therapeutic interventions.

Gene expression is controlled by pathways of regulatory factors often involving the activity of protein kinases on transcription factor proteins. Despite this well established mechanism, the number of well described pathways that include the regulatory role of protein kinases on transcription factors is surprisingly scarce in eukaryotes. To address this, PhosTF was developed to infer functional regulatory interactions and pathways in both simulated and real biological networks, based on linear cyclic causal models with latent variables. GeneNetWeaverPhos , an extension of GeneNetWeaver , was developed to allow the simulation of perturbations in known networks that included the activity of protein kinases and phosphatases on gene regulation. Over 2000 genome-wide gene expression profiles, where the loss or gain of regulatory genes could be observed to perturb gene regulation, were then used to infer the existence of regulatory interactions, and their mode of regulation in the budding yeast Saccharomyces cerevisiae . Despite the additional complexity, our inference performed comparably to the best methods that inferred transcription factor regulation assessed in the DREAM4 challenge on similar simulated networks. Inference on integrated genome-scale data sets for yeast identified ∼ 8800 protein kinase/phosphatase-transcription factor interactions and ∼ 6500 interactions among protein kinases and/or phosphatases. Both types of regulatory predictions captured statistically significant numbers of known interactions of their type. Surprisingly, kinases and phosphatases regulated transcription factors by a negative mode or regulation (deactivation) in over 70% of the predictions.

Laboratory evolution experiments have led to important findings relating organism adaptation and genomic evolution. However, continuous monitoring of long-term evolution has been lacking for natural systems, limiting our understanding of these processes in situ. Here we characterize the evolutionary dynamics of a lineage of a clinically important opportunistic bacterial pathogen, Pseudomonas aeruginosa, as it adapts to the airways of several individual cystic fibrosis patients over 200,000 bacterial generations, and provide estimates of mutation rates of bacteria in a natural environment. In contrast to predictions based on in vitro evolution experiments, we document limited diversification of the evolving lineage despite a highly structured and complex host environment. Notably, the lineage went through an initial period of rapid adaptation caused by a small number of mutations with pleiotropic effects, followed by a period of genetic drift with limited phenotypic change and a genomic signature of negative selection, suggesting that the evolving lineage has reached a major adaptive peak in the fitness landscape. This contrasts with previous findings of continued positive selection from long-term in vitro evolution experiments. The evolved phenotype of the infecting bacteria further suggests that the opportunistic pathogen has transitioned to become a primary pathogen for cystic fibrosis patients.

Background Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. Methods We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. Results This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD “classifier genes” discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. Conclusions Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease.

Reproducibility is a key challenge of synthetic biology, but the foundation of reproducibility is only as solid as the reference materials it is built upon. Here we focus on the reproducibility of fluorescence measurements from bacteria transformed with engineered genetic constructs. This comparative analysis comprises three large interlaboratory studies using flow cytometry and plate readers, identical genetic constructs, and compatible unit calibration protocols. Across all three studies, we find similarly high precision in the calibrants used for plate readers. We also find that fluorescence measurements agree closely across the flow cytometry results and two years of plate reader results, with an average standard deviation of 1.52-fold, while the third year of plate reader results are consistently shifted by more than an order of magnitude, with an average shift of 28.9-fold. Analyzing possible sources of error indicates this shift is due to incorrect preparation of the fluorescein calibrant. These findings suggest that measuring fluorescence from engineered constructs is highly reproducible, but also that there is a critical need for access to quality controlled fluorescent calibrants for plate readers.

Obesity and type 2 diabetes (T2D) are metabolic disorders influenced by lifestyle and genetic factors that are characterized by insulin resistance in skeletal muscle, a prominent site of glucose disposal. Numerous genetic variants have been associated with obesity and T2D, of which the majority are located in non-coding DNA regions. This suggests that most variants mediate their effect by altering the activity of gene-regulatory elements, including enhancers. Here, we map skeletal muscle genomic enhancer elements that are dynamically regulated after exposure to the free fatty acid palmitate or the inflammatory cytokine TNFα. By overlapping enhancer positions with the location of disease-associated genetic variants, and resolving long-range chromatin interactions between enhancers and gene promoters, we identify target genes involved in metabolic dysfunction in skeletal muscle. The majority of these genes also associate with altered whole-body metabolic phenotypes in the murine BXD genetic reference population. Thus, our combined genomic investigations identified genes that are involved in skeletal muscle metabolism. Obesity and type 2 diabetes (T2D) are metabolic disorders characterized by insulin resistance in skeletal muscle. Here, the authors map skeletal muscle enhancer elements dynamically regulated after exposure to free fatty acid palmitate or inflammatory cytokine TNFα and identify target genes involved in metabolic dysfunction in skeletal muscle.

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi‐omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single‐dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes. Synopsis Genetic variant effects can be described according to the spread of affected molecules across the cellular molecular network. Integrative multi‐omics analyses show how variants can shift network states in a global manner while other variant effects remain local or regional. Global changes of the cellular molecular network in response to genetic variation result from the requirement to balance the activity of diverse cellular processes. Quantification of cellular molecular network state differences due to combined PKA and TOR activity in a scalar quantity (“PT score”) captures genetically encoded and environmental variability in transcripts, proteins, and protein phosphorylation in yeast. Genetic alteration of the (PKA/TOR‐dependent) network state affects correlated and anti‐correlated protein pairs across large distances in a physical interaction network. Complex fitness traits such as thermotolerance and longevity are subject to network state alteration. Graphical Abstract Genetic variant effects can be described according to the spread of affected molecules across the cellular molecular network. Integrative multi‐omics analyses show how variants can shift network states in a global manner while other variant effects remain local or regional.

Glycerol is considered as a promising substrate for biotechnological applications and the non-conventional yeast Yarrowia lipolytica has been used extensively for the valorization of this compound. Contrary to S. cerevisiae, Y. lipolytica seems to prefer glycerol over glucose and it has been reported previously that the presence of glycerol can suppress the consumption of glucose in co-substrate fermentations. Based on these observations, we hypothesized glycerol repression-like effects in Y. lipolytica, which are converse to well described carbon repression mechanisms ensuring the prioritized use of glucose (e.g., in S. cerevisiae). We therefore aimed to investigate this effect on the level of transcription. Strains varying in the degree of glucose suppression were chosen and characterized in high-resolution growth screenings, resulting in the detection of different growth phenotypes under glycerol-glucose mixed conditions. Two strains, IBT and W29, were selected and cultivated in chemostats using glucose, glycerol and glucose/glycerol as carbon sources, followed by an RNA-Seq-based transcriptome analysis. We could show that several transporters were significantly higher expressed in W29, which is potentially related to the observed physiological differences. However, most of the expression variation between the strains were regardless of the carbon source applied, and cross-comparisons revealed that the strain-specific carbon source responses underwent in the opposite direction. A deeper analysis of the substrate specific carbon source response led to the identification of several differentially expressed genes with orthologous functions related to signal transduction and transcriptional regulation. This study provides an initial investigation on potentially novel carbon source regulation mechanisms in yeasts.

Little is known about the involvement of type 2 immune response-promoting intestinal tuft cells in metabolic regulation. We here examined the temporal changes in small intestinal tuft cell number and activity in response to high-fat diet-induced obesity in mice and investigated the relation to whole-body energy metabolism and the immune phenotype of the small intestine and epididymal white adipose tissue. Intake of high fat diet resulted in a reduction in overall numbers of small intestinal epithelial and tuft cells and reduced expression of the intestinal type 2 tuft cell markers Il25 and Tslp . Amongst >1,700 diet-regulated transcripts in tuft cells, we observed an early association between body mass expansion and increased expression of the gene encoding the serine protease inhibitor neuroserpin. By contrast, tuft cell expression of genes encoding gamma aminobutyric acid (GABA)-receptors was coupled to Tslp and Il25 and reduced body mass gain. Combined, our results point to a possible role for small intestinal tuft cells in energy metabolism via coupled regulation of tuft cell type 2 markers and GABA signaling receptors, while being independent of type 2 immune cell involvement. These results pave the way for further studies into interventions that elicit anti-obesogenic circuits via small intestinal tuft cells.