114 research outputs found

    Plasmid fitness costs are caused by specific genetic conflicts enabling resolution by compensatory mutation

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    Plasmids play an important role in bacterial genome evolution by transferring genes between lineages. Fitness costs associated with plasmid carriage are expected to be a barrier to gene exchange, but the causes of plasmid fitness costs are poorly understood. Single compensatory mutations are often sufficient to completely ameliorate plasmid fitness costs, suggesting that such costs are caused by specific genetic conflicts rather than generic properties of plasmids, such as their size, metabolic burden, or gene expression level. By combining the results of experimental evolution with genetics and transcriptomics, we show here that fitness costs of 2 divergent large plasmids in Pseudomonas fluorescens are caused by inducing maladaptive expression of a chromosomal tailocin toxin operon. Mutations in single genes unrelated to the toxin operon, and located on either the chromosome or the plasmid, ameliorated the disruption associated with plasmid carriage. We identify one of these compensatory loci, the chromosomal gene PFLU4242, as the key mediator of the fitness costs of both plasmids, with the other compensatory loci either reducing expression of this gene or mitigating its deleterious effects by up-regulating a putative plasmid-borne ParAB operon. The chromosomal mobile genetic element Tn6291, which uses plasmids for transmission, remained up-regulated even in compensated strains, suggesting that mobile genetic elements communicate through pathways independent of general physiological disruption. Plasmid fitness costs caused by specific genetic conflicts are unlikely to act as a long-term barrier to horizontal gene transfer (HGT) due to their propensity for amelioration by single compensatory mutations, helping to explain why plasmids are so common in bacterial genomes.</jats:p

    Intelligence, reason of state and the art of governing risk and opportunity in early modern Europe

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    Drawing upon primary and secondary historical material, this paper explores the role of intelligence in early modern government. It focuses upon developments in seventeenth- and early-eighteenth-century England, a site-specific genealogical moment in the broader history of state power/knowledges. Addressing a tendency in Foucauldian work to neglect pre-eighteenth-century governance, the analysis reveals a set of interrelated processes which gave rise to an innovative technique for anticipating hazard and opportunity for the state. At the intersection of raison d’État, the evolving art of government, widespread routines of secrecy and a post-Westphalia field of European competition and exchange, intelligence was imagined as a fundamental solution to the concurrent problems of ensuring peace and stability while improving state forces. In the administrative offices of the English Secretary of State, an assemblage of complex and interrelated procedures sought to produce and manipulate information in ways which exposed both possible risks to the state and potential opportunities for expansion and gain. As this suggests, the art of intelligence played an important if largely unacknowledged role in the formation and growth of the early modern state. Ensuring strategic advantage over rivals, intelligence also limited the ability of England's neighbours to dominate trade, control the seas and master the colonies, functioning as a constitutive feature of European balance and equilibrium. As the analysis concludes, understanding intelligence as a form of governmental technique – a way of doing something – reveals an entirely novel way of thinking about and investigating its myriad (historical and contemporary) formations

    NIST interlaboratory study on glycosylation analysis of monoclonal antibodies : comparison of results from diverse analytical methods

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    Glycosylation is a topic of intense current interest in the development of biopharmaceuticals since it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy‑six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation  analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type.. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods

    Bioinformatics tools for cancer metabolomics

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    It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages
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