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IDENTIFICATION OF MYCOPLASMATACEAE BY THE FLUORESCENT ANTIBODY METHOD.

Clark, Harold W. (The George Washington University, Washington, D.C.), Jack S. Bailey, Richard C. Fowler, and Thomas McP. Brown. Identification of Mycoplasmataceae by the fluorescent antibody method. J. Bacteriol. 85:111-118. 1963.-The conditions of the fluorescent antibody reactions were studied in relation to their application to Mycoplasmataceae or pleuropneumonia-like organisms (PPLO). Mycoplasma hominis type 1 and 2 antigens and their homologous antisera were used to determine the activity and specificity of these and other strains. Fluorescein isothiocyanate conjugated antiserum globulin preparations were used in both the direct and indirect fluorescent antibody methods. A direct tube technique was used for the detection and measurement of growth in broth cultures by the addition of conjugated antiserum. The specific fluorescent staining and recognition of hot water fixed M. hominis colonies was presented as a suitable identification standard. The antigenic activity was found to remain in the insoluble residue after exposure of M. hominis strains to sonic vibration (9 kc) for 30 min and centrifugation. Brief 2-min exposures of tissue cells to vibration (9 kc) caused the disruption of tissues, with the release of viable and "bound" nonwashable strains that reacted specifically with fluorescent antibody. It is proposed to apply both the sonic vibration and the fluorescent antibody techniques for the identification of Mycoplasmataceae in human tissues.

Journal Article↗

Automated annotation of keywords for proteins related to mycoplasmataceae using machine learning techniques.

MOTIVATION: With the increase in submission of sequences to public databases, the curators of these are not able to cope with the amount of information. The motivation of this work is to generate a system for automated annotation of data we are particularly interested in, namely proteins related to the Mycoplasmataceae family. Following previous works on automatic annotation using symbolic machine learning techniques, the present work proposes a method of automatic annotation of keywords (a part of the SWISS-PROT annotation procedure), and the validation, by an expert, of the annotation rules generated. The aim of this procedure is twofold: to complete the annotation of keywords of those proteins which is far from adequate, and to produce a prototype of the validation environment, which is aimed at an expert who does not have a deep knowledge of the structure of the current databases containing the necessary information s/he needs. RESULTS: As for the first objective, a rate of correct keywords annotation of 60% is reported in the literature. Our preliminary results show that with a slightly different method, applied this method to data related to Mycoplasmataceae only, we are able to increase that rate of correct annotation.

Abstracting and Indexing↗

Classification of eubacteria based on their complete genome: where does Mycoplasmataceae belong?

The amino acid compositions of 11 Gram-positive and 12 Gram-negative eubacteria were determined from their complete genomes. They were classified into two groups, 'S-type' represented by Staphylococcus aureus and 'E-type' represented by Escherichia coli, based on their patterns of amino acid compositions determined from the complete genome. These two groups were characterized by their concentrations of Arg, Ala and Lys. Mycoplasmas, which lack a cell wall, belonged to the 'S-type', while Gram-positive mycobacteria belonged to the 'E-type'. Rickettsia prowazekii, Borrelia burgdorferi, Campylobacter jejuni and Helicobacter pylori, which are Gram-negative, belong to the 'S-type'. The classification into two groups based on their amino acid compositions determined from the complete genome was independent of Gram staining. In addition, the amino acid composition based on the plasmid resembled that based on the parent complete genome.

Amino Acid Sequence↗