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To elucidate ecosystem functioning, it is fundamental to recognize what processes occur in which environments (where) and which microorganisms carry them out (who). Here, we present PREGO, a one-stop-shop knowledge base providing such associations. PREGO combines text mining and data integration techniques to mine such what-where-who associations from data and metadata scattered in the scientific literature and in public omics repositories. Microorganisms, biological processes, and environment types are identified and mapped to ontology terms from established community resources. Analyses of comentions in text and co-occurrences in metagenomics data/metadata are performed to extract associations and a level of confidence is assigned to each of them thanks to a scoring scheme. The PREGO knowledge base contains associations for 364,508 microbial taxa, 1090 environmental types, 15,091 biological processes, and 7971 molecular functions with a total of almost 58 million associations. These associations are available through a web portal, an Application Programming Interface (API), and bulk download. By exploring environments and/or processes associated with each other or with microbes, PREGO aims to assist researchers in design and interpretation of experiments and their results. To demonstrate PREGO’s capabilities, a thorough presentation of its web interface is given along with a meta-analysis of experimental results from a lagoon-sediment study of sulfur-cycle related microbes. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

This corrects the article DOI: 10.1038/nrd.2018.14.

SUMMARY: This study examines the association between certain audit firm characteristics and audit firm litigation risk. Previous research shows a link between audit client characteristics and audit firm litigation risk. However, insurance companies do not make extensive use of financial information about individual audit clients to make risk assessments. Instead, they primarily use information about the audit firms themselves. Using data from a large insurance company, we examine the link between several audit firm characteristics and audit-related litigation. Based on a dichotomous measure of risk (existence of a lawsuit), we find that larger firms, firms experiencing rapid growth, firms that sue their clients, and firms with a history of problems all face greater litigation risk. Introducing a continuous measure of the cost of litigation we find, in addition to the previously mentioned risk factors, that firms with a prior history of regulatory problems and firms that choose smaller deductibles are more risky to the insurance company. However, our proxies for independence and expertise are not associated with litigation risk.

Several cyclic processes take place within a single organism. For example, the cell cycle is coordinated with the 24 h diurnal rhythm in animals and plants, and with the 40 min ultradian rhythm in budding yeast. To examine the evolution of periodic gene expression during these processes, we performed the first systematic comparison in three organisms (Homo sapiens, Arabidopsis thaliana and Saccharomyces cerevisiae) by using public microarray data. We observed that although diurnal-regulated and ultradian-regulated genes are not generally cell-cycle-regulated, they tend to have cell-cycle-regulated paralogues. Thus, diverged temporal expression of paralogues seems to facilitate cellular orchestration under different periodic stimuli. Lineage-specific functional repertoires of periodic-associated paralogues imply that this mode of regulation might have evolved independently in several organisms.

BACKGROUND: Extensive transcription of non-coding RNAs has been detected in eukaryotic genomes and is thought to constitute an additional layer in the regulation of gene expression. Despite this role, their transcription through the cell cycle has not been studied; genome-wide approaches have only focused on protein-coding genes. To explore the complex transcriptome architecture underlying the budding yeast cell cycle, we used 8 bp tiling arrays to generate a 5 minute-resolution, strand-specific expression atlas of the whole genome. RESULTS: We discovered 523 antisense transcripts, of which 80 cycle or are located opposite periodically expressed mRNAs, 135 unannotated intergenic non-coding RNAs, of which 11 cycle, and 109 cell-cycle-regulated protein-coding genes that had not previously been shown to cycle. We detected periodic expression coupling of sense and antisense transcript pairs, including antisense transcripts opposite of key cell-cycle regulators, like FAR1 and TAF2. CONCLUSIONS: Our dataset presents the most comprehensive resource to date on gene expression during the budding yeast cell cycle, revealing both protein-coding and non-coding RNA periodicity of expression and the first that profiles non-annotated RNAs. It enables hypothesis-driven mechanistic studies concerning the functions of non-coding RNAs.

A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome.

Information on protein-protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at http://string.embl.de/

Spindle pole bodies (SPBs) provide a structural basis for genome inheritance and spore formation during meiosis in yeast. Upon carbon source limitation during sporulation, the number of haploid spores formed per cell is reduced. We show that precise spore number control (SNC) fulfills two functions. SNC maximizes the production of spores (1-4) that are formed by a single cell. This is regulated by the concentration of three structural meiotic SPB components, which is dependent on available amounts of carbon source. Using experiments and computer simulation, we show that the molecular mechanism relies on a self-organizing system, which is able to generate particular patterns (different numbers of spores) in dependency on one single stimulus (gradually increasing amounts of SPB constituents). We also show that SNC enhances intratetrad mating, whereby maximal amounts of germinated spores are able to return to a diploid lifestyle without intermediary mitotic division. This is beneficial for the immediate fitness of the population of postmeiotic cells.

The combination of prediction tools in complex workflows and pipelines facilitates prediction of protein features from sequence., A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome.