The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins

Management recommendations for pancreatic manifestations of von Hippel–Lindau disease

Von Hippel–Lindau disease (VHL) is a multineoplasm inherited disease manifesting with hemangioblastoma of the central nervous system and retina, adrenal pheochromocytoma, renal cell carcinoma, pancreatic neuroendocrine tumors and cysts, and neoplasms/cysts of the ear, broad ligament, and testicles. During 2018-2020, the VHL Alliance gathered several committees of experts in the various clinical manifestations of VHL to review the literature, gather the available evidence on VHL, and develop recommendations for patient management. The current report details the results of the discussion of a group of experts in the pancreatic manifestations of VHL along with their proposed recommendations for the clinical surveillance and management of patients with VHL. The recommendations subcommittee performed a comprehensive systematic review of the literature and conducted panel discussions to reach the current recommendations. The level of evidence was defined according to the Shekelle variation of the Grading of Recommendations, Assessment, Development, and Evaluation grading system. The National Comprehensive Cancer Network Categories of Evidence and Consensus defined the committee members' interpretation of the evidence and degree of consensus. The recommendations encompass the main aspects of VHL-related pancreatic manifestations and their clinical management. They are presented in a clinical orientation, including general planning of screening and surveillance for pancreatic neuroendocrine tumors, utility of biochemical biomarkers, the optimal choice for imaging modality, indirect risk stratification, indications for tissue sampling of VHL-related pancreatic neuroendocrine tumors, and interventions. These recommendations are designed to serve as the reference for all aspects of the screening, surveillance, and management of VHL-related pancreatic manifestations

Development of intuitive rules: Evaluating the application of the dual-system framework to understanding children's intuitive reasoning

This is an author-created version of this article. The original source of publication is Psychon Bull Rev. 2006 Dec;13(6):935-53 The final publication is available at www.springerlink.com Published version: http://dx.doi.org/10.3758/BF0321390

The second-generation antipsychotic drug aripiprazole modulates the serotonergic system in pancreatic islets and induces beta cell dysfunction in female mice

[Aims/hypothesis]: Second-generation antipsychotic (SGA) drugs have been associated with the development of type 2 diabetes and the metabolic syndrome in patients with schizophrenia. In this study, we aimed to investigate the effects of two different SGA drugs, olanzapine and aripiprazole, on metabolic state and islet function and plasticity. [Methods]: We analysed the functional adaptation of beta cells in 12-week-old B6;129 female mice fed an olanzapine- or aripiprazole-supplemented diet (5.5–6.0 mg kg−1 day−1) for 6 months. Glucose and insulin tolerance tests, in vivo glucose-stimulated insulin secretion and indirect calorimetry were performed at the end of the study. The effects of SGAs on beta cell plasticity and islet serotonin levels were assessed by transcriptomic analysis and immunofluorescence. Insulin secretion was assessed by static incubations and Ca2+ fluxes by imaging techniques. [Results]: Treatment of female mice with olanzapine or aripiprazole for 6 months induced weight gain (p<0.01 and p<0.05, respectively), glucose intolerance (p<0.01) and impaired insulin secretion (p<0.05) vs mice fed a control chow diet. Aripiprazole, but not olanzapine, induced serotonin production in beta cells vs controls, likely by increasing tryptophan hydroxylase 1 (TPH1) expression, and inhibited Ca2+ flux. Of note, aripiprazole increased beta cell size (p<0.05) and mass (p<0.01) vs mice fed a control chow diet, along with activation of mechanistic target of rapamycin complex 1 (mTORC1)/S6 signalling, without preventing beta cell dysfunction. [Conclusions/interpretation]: Both SGAs induced weight gain and beta cell dysfunction, leading to glucose intolerance; however, aripiprazole had a more potent effect in terms of metabolic alterations, which was likely a result of its ability to modulate the serotonergic system. The deleterious metabolic effects of SGAs on islet function should be considered while treating patients as these drugs may increase the risk for development of the metabolic syndrome and diabetes.This work was funded by H2020 Marie Sklodowska-Curie ITN-TREATMENT (Grant Agreement 721236, European Commission). We also acknowledge grants RTI2018-094052-B-100/ AEI/10.13039/501100011033 (Ministerio de Ciencia e Innovación y Fondo Europeo de Desarrollo Regional [FEDER]) and S2017/BMD-3684 (Comunidad de Madrid, Spain), and grants from Fundación Ramón Areces (Spain) and CIBERDEM (ISCIII, Spain)

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.National Institutes of Health (U.S.) (U24 CA180922

Nonspecific Protein-DNA Binding Is Widespread in the Yeast Genome

Recent genome-wide measurements of binding preferences of ~200 transcription regulators in the vicinity of transcription start sites in yeast, have provided a unique insight into the cis- regulatory code of a eukaryotic genome (Venters et al., Mol. Cell 41, 480 (2011)). Here, we show that nonspecific transcription factor (TF)-DNA binding significantly influences binding preferences of the majority of transcription regulators in promoter regions of the yeast genome. We show that promoters of SAGA-dominated and TFIID-dominated genes can be statistically distinguished based on the landscape of nonspecific protein-DNA binding free energy. In particular, we predict that promoters of SAGA-dominated genes possess wider regions of reduced free energy compared to promoters of TFIID-dominated genes. We also show that specific and nonspecific TF-DNA binding are functionally linked and cooperatively influence gene expression in yeast. Our results suggest that nonspecific TF-DNA binding is intrinsically encoded into the yeast genome, and it may play a more important role in transcriptional regulation than previously thought

Evolution of a Membrane Protein Regulon in Saccharomyces

Expression variation is widespread between species. The ability to distinguish regulatory change driven by natural selection from the consequences of neutral drift remains a major challenge in comparative genomics. In this work, we used observations of mRNA expression and promoter sequence to analyze signatures of selection on groups of functionally related genes in Saccharomycete yeasts. In a survey of gene regulons with expression divergence between Saccharomyces cerevisiae and S. paradoxus, we found that most were subject to variation in trans-regulatory factors that provided no evidence against a neutral model. However, we identified one regulon of membrane protein genes controlled by unlinked cis- and trans-acting determinants with coherent effects on gene expression, consistent with a history of directional, nonneutral evolution. For this membrane protein group, S. paradoxus alleles at regulatory loci were associated with elevated expression and altered stress responsiveness relative to other yeasts. In a phylogenetic comparison of promoter sequences of the membrane protein genes between species, the S. paradoxus lineage was distinguished by a short branch length, indicative of strong selective constraint. Likewise, sequence variants within the S. paradoxus population, but not across strains of other yeasts, were skewed toward low frequencies in promoters of genes in the membrane protein regulon, again reflecting strong purifying selection. Our results support a model in which a distinct expression program for the membrane protein genes in S. paradoxus has been preferentially maintained by negative selection as the result of an increased importance to organismal fitness. These findings illustrate the power of integrating expression- and sequence-based tests of natural selection in the study of evolutionary forces that underlie regulatory change

Gene Expression Divergence is Coupled to Evolution of DNA Structure in Coding Regions

Sequence changes in coding region and regulatory region of the gene itself (cis) determine most of gene expression divergence between closely related species. But gene expression divergence between yeast species is not correlated with evolution of primary nucleotide sequence. This indicates that other factors in cis direct gene expression divergence. Here, we studied the contribution of DNA three-dimensional structural evolution as cis to gene expression divergence. We found that the evolution of DNA structure in coding regions and gene expression divergence are correlated in yeast. Similar result was also observed between Drosophila species. DNA structure is associated with the binding of chromatin remodelers and histone modifiers to DNA sequences in coding regions, which influence RNA polymerase II occupancy that controls gene expression level. We also found that genes with similar DNA structures are involved in the same biological process and function. These results reveal the previously unappreciated roles of DNA structure as cis-effects in gene expression