Beyond the biosynthetic gene cluster paradigm: Genome-wide coexpression networks connect clustered and unclustered transcription factors to secondary metabolic pathways

Fungal secondary metabolites are widely used as therapeutics and are vital components of drug discovery programs. A major challenge hindering discovery of novel secondary metabolites is that the underlying pathways involved in their biosynthesis are transcriptionally silent under typical laboratory growth conditions, making it difficult to identify the transcriptional networks that they are embedded in. Furthermore, while the genes participating in secondary metabolic pathways are typically found in contiguous clusters on the genome, known as biosynthetic gene clusters (BGCs), this is not always the case, especially for global and pathway-specific regulators of pathways’ activities. To address these challenges, we used 283 genome-wide gene expression data sets of the ascomycete cell factory Aspergillus niger generated during growth under 155 different conditions to construct two gene coexpression networks based on Spearman’s correlation coefficients (SCCs) and on mutual rank-transformed Pearson’s correlation coefficients (MR-PCCs). By mining these networks, we predicted six transcription factors, named MjkA to MjkF, to regulate secondary metabolism in A. niger. Overexpression of each transcription factor using the Tet-On cassette modulated the production of multiple secondary metabolites. We found that the SCC and MR-PCC approaches complemented each other, enabling the delineation of putative global (SCC) and pathway-specific (MR-PCC) transcription factors. These results highlight the potential of coexpression network approaches to identify and activate fungal secondary metabolic pathways and their products. More broadly, we argue that drug discovery programs in fungi should move beyond the BGC paradigm and focus on understanding the global regulatory networks in which secondary metabolic pathways are embedded.DFG, 404295023, Etablierung eines innovativen Ko-Kultivierungssystems zur Hochdurchsatzidentifizierung von antimikrobiellen WirkstoffenEC/FP7/607332/EU/Quantitative Biology for Fungal Secondary Metabolite Producers/QUANTFUN

Associations of Serum 25-Hydroxyvitamin D, Parathyroid Hormone and Calcium with Cardiovascular Risk Factors: Analysis of 3 NHANES Cycles (2001–2006)

Increasing evidence suggests a role for mineral metabolism in cardiovascular disease risk. 25-hydroxyvitamin D (25(OH)D), parathyroid hormone (PTH), and calcium may be directly associated with cardiovascular risk factors or mediated by each other.We combined data for adult participants in three cycles of the National Health and Nutrition Examination Survey (2001-2, 2003-4, 2005-6), a representative sample of the civilian, non-institutionalized US population (N = 3,958). Using this data we examined joint associations of 25(OH)D, PTH and calcium with a range of cardiovascular risk factors. 25(OH)D was inversely associated with fasting insulin (mean difference in insulin per 1 standard deviation 25(OH)D: -0.053 (95%CI: -0.091, -0.015)), glucose (-0.046 95%CI: -0.081, -0.012) and systolic blood pressure (SBP) (-0.032 95%CI: -0.062, -0.001), and positively associated with high density lipoprotein cholesterol HDL-c (0.088 95%CI: 0.044, 0.148), after adjustment for ethnicity, smoking, socio-economic status and waist circumference. PTH was positively associated with diastolic blood pressure (0.110, 95%CI: 0.055, 0.164) in confounder adjusted models, but was not associated with other cardiovascular risk factors. Albumin adjusted calcium was associated with triglycerides (0.102 95%CI: 0.063, 0.141), postload glucose (0.078, 95%CI: 0.025, 0.130), fasting insulin (0.074, 95%CI: 0.044, 0.104), HbA1c (0.070, 95%CI: 0.036, 0.105), SBP (0.064, 95%CI: 0.028, 0.100), fasting glucose (0.055, 95%CI: 0.018, 0.092) and low density lipoprotein cholesterol (0.052, 95%CI: 0.014, 0.091). With mutual adjustment for each other, these associations remained essentially unchanged.Lower levels of 25(OH)D and higher levels of calcium and PTH appear to be associated with different cardiovascular risk factors and may therefore affect cardiovascular disease risk through different mechanisms

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal speciesFilamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns.National Science Foundation (grant number DEB-1442113). Received by AR. U.S. National Library of Medicine training grant (grant number 2T15LM007450). Received by ALL. Conselho Nacional de Desenvolvimento Cientı´fico e 573 Tecnológico. Northern Portugal Regional Operational Programme (grant number NORTE-01- 0145-FEDER-000013). Received by FR. Fundação de Amparo à Pesquisa do 572 Estado de São Paulo. Received by GHG. National Institutes of Health (grant number R01 AI065728-01). Received by NPK. National Science Foundation (grant number IOS-1401682). Received by JHW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Accurate and sensitive detection of microbial eukaryotes from whole metagenome shotgun sequencing.

BackgroundMicrobial eukaryotes are found alongside bacteria and archaea in natural microbial systems, including host-associated microbiomes. While microbial eukaryotes are critical to these communities, they are challenging to study with shotgun sequencing techniques and are therefore often excluded.ResultsHere, we present EukDetect, a bioinformatics method to identify eukaryotes in shotgun metagenomic sequencing data. Our approach uses a database of 521,824 universal marker genes from 241 conserved gene families, which we curated from 3713 fungal, protist, non-vertebrate metazoan, and non-streptophyte archaeplastida genomes and transcriptomes. EukDetect has a broad taxonomic coverage of microbial eukaryotes, performs well on low-abundance and closely related species, and is resilient against bacterial contamination in eukaryotic genomes. Using EukDetect, we describe the spatial distribution of eukaryotes along the human gastrointestinal tract, showing that fungi and protists are present in the lumen and mucosa throughout the large intestine. We discover that there is a succession of eukaryotes that colonize the human gut during the first years of life, mirroring patterns of developmental succession observed in gut bacteria. By comparing DNA and RNA sequencing of paired samples from human stool, we find that many eukaryotes continue active transcription after passage through the gut, though some do not, suggesting they are dormant or nonviable. We analyze metagenomic data from the Baltic Sea and find that eukaryotes differ across locations and salinity gradients. Finally, we observe eukaryotes in Arabidopsis leaf samples, many of which are not identifiable from public protein databases.ConclusionsEukDetect provides an automated and reliable way to characterize eukaryotes in shotgun sequencing datasets from diverse microbiomes. We demonstrate that it enables discoveries that would be missed or clouded by false positives with standard shotgun sequence analysis. EukDetect will greatly advance our understanding of how microbial eukaryotes contribute to microbiomes. Video abstract

A Robust Phylogenomic Time Tree for Biotechnologically and Medically Important Fungi in the Genera Aspergillus and Penicillium

Understanding the evolution of traits across technologically and medically significant fungi requires a robust phylogeny. Even though species in the Aspergillus and Penicillium genera (family Aspergillaceae, class Eurotiomycetes) are some of the most significant technologically and medically relevant fungi, we still lack a genome-scale phylogeny of the lineage or knowledge of the parts of the phylogeny that exhibit conflict among analyses. Here, we used a phylogenomic approach to infer evolutionary relationships among 81 genomes that span the diversity of Aspergillus and Penicillium species, to identify conflicts in the phylogeny, and to determine the likely underlying factors of the observed conflicts. Using a data matrix comprised of 1,668 genes, we found that while most branches of the phylogeny of the Aspergillaceae are robustly supported and recovered irrespective of method of analysis, a few exhibit various degrees of conflict among our analyses. Further examination of the observed conflict revealed that it largely stems from incomplete lineage sorting and hybridization or introgression. Our analyses provide a robust and comprehensive evolutionary genomic roadmap for this important lineage, which will facilitate the examination of the diverse technologically and medically relevant traits of these fungi in an evolutionary context.The filamentous fungal family Aspergillaceae contains >1,000 known species, mostly in the genera Aspergillus and Penicillium. Several species are used in the food, biotechnology, and drug industries (e.g., Aspergillus oryzae and Penicillium camemberti), while others are dangerous human and plant pathogens (e.g., Aspergillus fumigatus and Penicillium digitatum). To infer a robust phylogeny and pinpoint poorly resolved branches and their likely underlying contributors, we used 81 genomes spanning the diversity of Aspergillus and Penicillium to construct a 1,668-gene data matrix. Phylogenies of the nucleotide and amino acid versions of this full data matrix as well as of several additional data matrices were generated using three different maximum likelihood schemes (i.e., gene-partitioned, unpartitioned, and coalescence) and using both site-homogenous and site-heterogeneous models (total of 64 species-level phylogenies). Examination of the topological agreement among these phylogenies and measures of internode certainty identified 11/78 (14.1%) bipartitions that were incongruent and pinpointed the likely underlying contributing factors, which included incomplete lineage sorting, hidden paralogy, hybridization or introgression, and reconstruction artifacts associated with poor taxon sampling. Relaxed molecular clock analyses suggest that Aspergillaceae likely originated in the lower Cretaceous and that the Aspergillus and Penicillium genera originated in the upper Cretaceous. Our results shed light on the ongoing debate on Aspergillus systematics and taxonomy and provide a robust evolutionary and temporal framework for comparative genomic analyses in Aspergillaceae. More broadly, our approach provides a general template for phylogenomic identification of resolved and contentious branches in densely genome-sequenced lineages across the tree of life