Candida albicans commensalism in the oral mucosa is favoured by limited virulence and metabolic adaptation.

As part of the human microbiota, the fungus Candida albicans colonizes the oral cavity and other mucosal surfaces of the human body. Commensalism is tightly controlled by complex interactions of the fungus and the host to preclude fungal elimination but also fungal overgrowth and invasion, which can result in disease. As such, defects in antifungal T cell immunity render individuals susceptible to oral thrush due to interrupted immunosurveillance of the oral mucosa. The factors that promote commensalism and ensure persistence of C. albicans in a fully immunocompetent host remain less clear. Using an experimental model of C. albicans oral colonization in mice we explored fungal determinants of commensalism in the oral cavity. Transcript profiling of the oral isolate 101 in the murine tongue tissue revealed a characteristic metabolic profile tailored to the nutrient poor conditions in the stratum corneum of the epithelium where the fungus resides. Metabolic adaptation of isolate 101 was also reflected in enhanced nutrient acquisition when grown on oral mucosa substrates. Persistent colonization of the oral mucosa by C. albicans also correlated inversely with the capacity of the fungus to induce epithelial cell damage and to elicit an inflammatory response. Here we show that these immune evasive properties of isolate 101 are explained by a strong attenuation of a number of virulence genes, including those linked to filamentation. De-repression of the hyphal program by deletion or conditional repression of NRG1 abolished the commensal behaviour of isolate 101, thereby establishing a central role of this factor in the commensal lifestyle of C. albicans in the oral niche of the host.

MetaNetX/MNXref: unified namespace for metabolites and biochemical reactions in the context of metabolic models.

MetaNetX/MNXref is a reconciliation of metabolites and biochemical reactions providing cross-links between major public biochemistry and Genome-Scale Metabolic Network (GSMN) databases. The new release brings several improvements with respect to the quality of the reconciliation, with particular attention dedicated to preserving the intrinsic properties of GSMN models. The MetaNetX website (https://www.metanetx.org/) provides access to the full database and online services. A major improvement is for mapping of user-provided GSMNs to MXNref, which now provides diagnostic messages about model content. In addition to the website and flat files, the resource can now be accessed through a SPARQL endpoint (https://rdf.metanetx.org).

Vacuolins and myosin VII are required for phagocytic uptake and phagosomal membrane recycling in Dictyostelium discoideum.

Flotillins are lipid raft residents involved in membrane trafficking and recycling of plasma membrane proteins. Dictyostelium discoideum uses phagocytosis to kill, digest and feed on bacteria. It possesses three flotillin-like vacuolins that are strongly associated with membranes and that gradually accumulate on maturing phagosomes. Absence of vacuolins reduced adhesion and particle recognition resulting in a drastic reduction in the uptake of various types of particles. This was caused by a block in the recycling of plasma membrane components and the absence of their specific cortex-associated proteins. In addition, absence of vacuolins also impaired phagolysosome biogenesis, without significantly impacting killing and digestion of a range of bacteria. Strikingly, both absence and overexpression of vacuolins induced a strong downregulation of myosin VII (also known as MyoI) expression, as well as its binding partner talin A. Episomal expression of myosin VII fully rescued defects in uptake and adhesion but not in phagosome maturation. These results suggest a dual role for vacuolins: a novel mechanism involving membrane microdomains and myosin VII-talin A in clustering phagosomal receptors and adhesion molecules at the plasma membrane, and a role in phagolysosomal biogenesis.

Disentangle genus microdiversity within a complex microbial community by using a multi-distance long-read binning method: example of Candidatus Accumulibacter.

Complete genomes can be recovered from metagenomes by assembling and binning DNA sequences into metagenome assembled genomes (MAGs). Yet, the presence of microdiversity can hamper the assembly and binning processes, possibly yielding chimeric, highly fragmented and incomplete genomes. Here, the metagenomes of four samples of aerobic granular sludge bioreactors containing Candidatus (Ca.) Accumulibacter, a phosphate-accumulating organism of interest for wastewater treatment, were sequenced with both PacBio and Illumina. Different strategies of genome assembly and binning were investigated, including published protocols and a binning procedure adapted to the binning of long contigs (MuLoBiSC). Multiple criteria were considered to select the best strategy for Ca. Accumulibacter, whose multiple strains in every sample represent a challenging microdiversity. In this case, the best strategy relies on long-read only assembly and a custom binning procedure including MuLoBiSC in metaWRAP. Several high-quality Ca. Accumulibacter MAGs, including a novel species, were obtained independently from different samples. Comparative genomic analysis showed that MAGs retrieved in different samples harbour genomic rearrangements in addition to accumulation of point mutations. The microdiversity of Ca. Accumulibacter, likely driven by mobile genetic elements, causes major difficulties in recovering MAGs, but it is also a hallmark of the panmictic lifestyle of these bacteria.

Anti-adipogenic signals at the onset of obesity-related inflammation in white adipose tissue.

Chronic inflammation that affects primarily metabolic organs, such as white adipose tissue (WAT), is considered as a major cause of human obesity-associated co-morbidities. However, the molecular mechanisms initiating this inflammation in WAT are poorly understood. By combining transcriptomics, ChIP-seq and modeling approaches, we studied the global early and late responses to a high-fat diet (HFD) in visceral (vWAT) and subcutaneous (scWAT) AT, the first being more prone to obesity-induced inflammation. HFD rapidly triggers proliferation of adipocyte precursors within vWAT. However, concomitant antiadipogenic signals limit vWAT hyperplastic expansion by interfering with the differentiation of proliferating adipocyte precursors. Conversely, in scWAT, residing beige adipocytes lose their oxidizing properties and allow storage of excessive fatty acids. This phase is followed by tissue hyperplastic growth and increased angiogenic signals, which further enable scWAT expansion without generating inflammation. Our data indicate that scWAT and vWAT differential ability to modulate adipocyte number and differentiation in response to obesogenic stimuli has a crucial impact on the different susceptibility to obesity-related inflammation of these adipose tissue depots.

Expression Pattern of the Pneumocystis jirovecii Major Surface Glycoprotein Superfamily in Patients with Pneumonia.

BACKGROUND: The human pathogen Pneumocystis jirovecii harbors 6 families of major surface glycoproteins (MSGs) encoded by a single gene superfamily. MSGs are presumably responsible for antigenic variation and adhesion to host cells. The genomic organization suggests that a single member of family I is expressed at a given time per cell, whereas members of the other families are simultaneously expressed. METHODS: We analyzed RNA sequences expressed in several clinical samples, using specific weighted profiles for sorting of reads and calling of single-nucleotide variants to estimate the diversity of the expressed genes. RESULTS: A number of different isoforms of at least 4 MSG families were expressed simultaneously, including isoforms of family I, for which confirmation was obtained in the wet laboratory. CONCLUSION: These observations suggest that every single P. jirovecii population is made of individual cells with distinct surface properties. Our results enhance our understanding of the unique antigenic variation system and cell surface structure of P. jirovecii.

A systems genetics resource and analysis of sleep regulation in the mouse.

Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep "sleep-wake" phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%-78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported.

Inferring gene expression networks with hubs using a degree weighted Lasso approach.

MOTIVATION: Genome-scale gene networks contain regulatory genes called hubs that have many interaction partners. These genes usually play an essential role in gene regulation and cellular processes. Despite recent advancements in high-throughput technology, inferring gene networks with hub genes from high-dimensional data still remains a challenging problem. Novel statistical network inference methods are needed for efficient and accurate reconstruction of hub networks from high-dimensional data. RESULTS: To address this challenge we propose DW-Lasso, a degree weighted Lasso (least absolute shrinkage and selection operator) method which infers gene networks with hubs efficiently under the low sample size setting. Our network reconstruction approach is formulated as a two stage procedure: first, the degree of networks is estimated iteratively, and second, the gene regulatory network is reconstructed using degree information. A useful property of the proposed method is that it naturally favors the accumulation of neighbors around hub genes and thereby helps in accurate modeling of the high-throughput data under the assumption that the underlying network exhibits hub structure. In a simulation study, we demonstrate good predictive performance of the proposed method in comparison to traditional Lasso type methods in inferring hub and scale-free graphs. We show the effectiveness of our method in an application to microarray data of Escherichia coli and RNA sequencing data of Kidney Clear Cell Carcinoma from The Cancer Genome Atlas datasets. AVAILABILITY AND IMPLEMENTATION: Under the GNU General Public Licence at https://cran.r-project.org/package=DWLasso. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Condition-specific series of metabolic sub-networks and its application for gene set enrichment analysis.

MOTIVATION: Genome-scale metabolic networks and transcriptomic data represent complementary sources of knowledge about an organism's metabolism, yet their integration to achieve biological insight remains challenging. RESULTS: We investigate here condition-specific series of metabolic sub-networks constructed by successively removing genes from a comprehensive network. The optimal order of gene removal is deduced from transcriptomic data. The sub-networks are evaluated via a fitness function, which estimates their degree of alteration. We then consider how a gene set, i.e. a group of genes contributing to a common biological function, is depleted in different series of sub-networks to detect the difference between experimental conditions. The method, named metaboGSE, is validated on public data for Yarrowia lipolytica and mouse. It is shown to produce GO terms of higher specificity compared to popular gene set enrichment methods like GSEA or topGO. AVAILABILITY AND IMPLEMENTATION: The metaboGSE R package is available at https://CRAN.R-project.org/package=metaboGSE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Greater topoclimatic control of above- versus below-ground communities.

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above-ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above- and below-ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above-ground species than on below-ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above-ground than for below-ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above- and below-ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems.

Updates in Rhea - an expert curated resource of biochemical reactions.

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.

Vps13F links bacterial recognition and intracellular killing in Dictyostelium.

Bacterial sensing, ingestion, and killing by phagocytic cells are essential processes to protect the human body from infectious microorganisms. The cellular mechanisms involved in intracellular killing, their relative importance, and their specificity towards different bacteria are however poorly defined. In this study, we used Dictyostelium discoideum, a phagocytic cell model amenable to genetic analysis, to identify new gene products involved in intracellular killing. A random genetic screen led us to identify the role of Vps13F in intracellular killing of Klebsiella pneumoniae. Vps13F knock-out (KO) cells exhibited a delayed intracellular killing of K. pneumoniae, although the general organization of the phagocytic and endocytic pathway appeared largely unaffected. Transcriptomic analysis revealed that vps13F KO cells may be functionally similar to previously characterized fspA KO cells, shown to be defective in folate sensing. Indeed, vps13F KO cells showed a decreased chemokinetic response to various stimulants, suggesting a direct or indirect role of Vps13F in intracellular signaling. Overstimulation with excess folate restored efficient killing in vps13F KO cells. Finally, genetic inactivation of Far1, the folate receptor, resulted in inefficient intracellular killing of K. pneumoniae. Together, these observations show that stimulation of Dictyostelium by bacterial folate is necessary for rapid intracellular killing of K. pneumoniae.

MetaNetX/MNXref--reconciliation of metabolites and biochemical reactions to bring together genome-scale metabolic networks.

MetaNetX is a repository of genome-scale metabolic networks (GSMNs) and biochemical pathways from a number of major resources imported into a common namespace of chemical compounds, reactions, cellular compartments--namely MNXref--and proteins. The MetaNetX.org website (http://www.metanetx.org/) provides access to these integrated data as well as a variety of tools that allow users to import their own GSMNs, map them to the MNXref reconciliation, and manipulate, compare, analyze, simulate (using flux balance analysis) and export the resulting GSMNs. MNXref and MetaNetX are regularly updated and freely available.

Identification and Functional Ascertainment of the Pneumocystis jirovecii Potential Drug Targets Gsc1 and Kre6 Involved in Glucan Synthesis.

The most efficient drug against the human pathogenic fungus Pneumocystis jirovecii is cotrimoxazole targeting the folate biosynthesis. However, resistance toward it is emerging and adverse effects occur in some patients. Studies in rodent models suggested that echinocandins could be useful to treat Pneumocystis pneumonia. Echinocandins inhibit the catalytic subunit Gsc1 of the enzymatic complex ensuring the synthesis of 1,3-ß glucan, an essential constituent of cell walls of most fungi. Besides, inhibitors of the enzyme Kre6 involved in the synthesis of 1,6-ß glucan, another essential component of fungal walls, were recently described. We identified and functionally characterized these two potential drug targets in the human pathogen P. jirovecii by rescue of the null allele of the orthologous gene in Saccharomyces cerevisiae. The P. jirovecii proteins Gsc1 and Kre6 identified using those of the relative Pneumocystis carinii as the query sequence showed high sequence identity to the putative fungal orthologs (53-97% in conserved functional domains). The expression of their encoding genes on plasmid rescued the increased sensitivity to, respectively, caspofungin or calcofluor white of the corresponding S. cerevisiae null allele. The uniqueness and likely essentiality of these proteins suggest that they are potential good drug targets.

Reconciliation of metabolites and biochemical reactions for metabolic networks.

Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.

Genome of an arbuscular mycorrhizal fungus provides insight into the oldest plant symbiosis.

The mutualistic symbiosis involving Glomeromycota, a distinctive phylum of early diverging Fungi, is widely hypothesized to have promoted the evolution of land plants during the middle Paleozoic. These arbuscular mycorrhizal fungi (AMF) perform vital functions in the phosphorus cycle that are fundamental to sustainable crop plant productivity. The unusual biological features of AMF have long fascinated evolutionary biologists. The coenocytic hyphae host a community of hundreds of nuclei and reproduce clonally through large multinucleated spores. It has been suggested that the AMF maintain a stable assemblage of several different genomes during the life cycle, but this genomic organization has been questioned. Here we introduce the 153-Mb haploid genome of Rhizophagus irregularis and its repertoire of 28,232 genes. The observed low level of genome polymorphism (0.43 SNP per kb) is not consistent with the occurrence of multiple, highly diverged genomes. The expansion of mating-related genes suggests the existence of cryptic sex-related processes. A comparison of gene categories confirms that R. irregularis is close to the Mucoromycotina. The AMF obligate biotrophy is not explained by genome erosion or any related loss of metabolic complexity in central metabolism, but is marked by a lack of genes encoding plant cell wall-degrading enzymes and of genes involved in toxin and thiamine synthesis. A battery of mycorrhiza-induced secreted proteins is expressed in symbiotic tissues. The present comprehensive repertoire of R. irregularis genes provides a basis for future research on symbiosis-related mechanisms in Glomeromycota.

MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks.

MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality.

pfsearchV3: a code acceleration and heuristic to search PROSITE profiles.

SUMMARY: The PROSITE resource provides a rich and well annotated source of signatures in the form of generalized profiles that allow protein domain detection and functional annotation. One of the major limiting factors in the application of PROSITE in genome and metagenome annotation pipelines is the time required to search protein sequence databases for putative matches. We describe an improved and optimized implementation of the PROSITE search tool pfsearch that, combined with a newly developed heuristic, addresses this limitation. On a modern x86_64 hyper-threaded quad-core desktop computer, the new pfsearchV3 is two orders of magnitude faster than the original algorithm. AVAILABILITY AND IMPLEMENTATION: Source code and binaries of pfsearchV3 are freely available for download at http://web.expasy.org/pftools/#pfsearchV3, implemented in C and supported on Linux. PROSITE generalized profiles including the heuristic cut-off scores are available at the same address.

Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.