Nine different strains of mycobacteria grown on media deficient in iron all produced mycobactins. Most strains produced one mycobactin in great preponderance. Mycobacteria from clearly distinct taxonomic groups gave mycobactins differing in the structure of their nuclei. One group of taxonomically related mycobacteria produced mycobactins having the same nucleus but with different distributions of side chains within the homologous mixtures. Simple methods are described for identifying mycobactins on a small scale; these may be of value in classifying mycobacteria. Structures are proposed for mycobactin A from Mycobacterium aurum, mycobactin R from M. terrae, mycobactin F, produced together with mycobactin H by M. fortuitum, and mycobactins M and N from M. marinum. The first three of these differ from known mycobactins in details of substitution and configuration of asymmetric centres in the nucleus. Mycobactins M and N are substantially different, having only small acyl groups (acetyl and propionyl respectively) at the hydroxamic acid centre of the mycobactic acid moiety. Both are homologous mixtures having long-chain saturated 3-hydroxy-2-methyl acid fragments in the cobactin moiety. All mycobactins so far isolated promote almost maximal growth of M. johnei at 30ng./ml. in liquid medium. The activity of some mycobactins extends to much lower concentrations, mycobactin S showing significant growth promotion at 0.3ng./ml. Mycobactin M or N in combination with mycobactins having a long side chain in the mycobactic acid moiety exerts a mutually antagonistic effect on the growth of M. johnei, the mixture giving less growth than either mycobactin separately. Mycobactin M also decreases the growth of M. kansasii and M. tuberculosis on liquid media. These antagonistic effects are probably caused by a lengthening of the lag phase.
The analysis of network data is an area that is rapidly growing, both within and outside of the discipline of statistics.This review provides a concise summary of methods and models used in the statistical analysis of network data, including the Erdős-Renyi model, the exponential family class of network models and recently developed latent variable models.Many of the methods and models are illustrated by application to the well-known Zachary karate dataset. Software routines available for implementing methods are emphasised throughout.The aim of this paper is to provide a review with enough detail about many common classes of network model to whet the appetite and to point the way to further reading.
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian setting. Three methods for fitting the model are provided, incorporating an expectation-maximization algorithm, Gibbs sampling and a variational Bayes approximation. The article briefly outlines the methodology behind each of these techniques and discusses some of the technical difficulties associated with them. Methods to remedy these problems are also described. Visualization methods for each of these techniques are included, as well as criteria to aid model selection.
A single pure component was isolated from mycobactin P by countercurrent distribution; its side chain is n-cis-octadec-2-enoyl; its purity and molecular structure were confirmed by mass spectrometry of its aluminium complex. The separation of ferric and of aluminium complexes of mycobactins by thin-layer chromatography is described. Mycobacterium terrae, M. marinum and M. smegmatis produce mycobactins that differ among themselves and from mycobactins P and T. A nomenclature for the mycobactins and their derivatives is suggested.
The benefits of on-site analysis of environmental pollutants are well known, with such techniques increasing sample throughput and reducing the overall cost of pollution level monitoring. This article describes a transportable time-of-flight (TOF) mass spectrometer, based upon a converging, annular TOF (CAT) arrangement. The instrument, the transportable CAT or T-CAT is battery powered and self-contained. The vacuum chamber is never vented and is kept at a very low pressure, even during analysis. Sample gases are admitted to the mass spectrometer via a membrane inlet system. Data collection and analysis are accomplished via a portable PC. The T-CAT is capable of detection limits approaching those of more conventional, nonportable design. The device shows reasonable linearity over wide concentration ranges. Initial results indicate that the T-CAT will be capable of use in a wide range of applications, particularly for environmental monitoring. This article describes the features of the T-CAT, and presents initial results from the membrane inlet/T-CAT system.
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