Microbial analysis characterization

Minz D., Flax J. L., Green S. J., Muyzer G., Cohen Y., Wagner M., Rittmann B. E., and Stahl D. A. (1999b) Diversity of sulfate-reducing bacteria in oxic and anoxic regions of a microbial mat characterized by comparative analysis of dissimilatory sulfite reductase genes. Appl. Environ. Microbiol. 65, 4666-4671. 

Fatty acid profiling by GC is routine in some clinical reference laboratories, particularly for identification of anaerobic bacteria. Fatty acids and lipids are bonded to proteins, carbohydrates, or other chemical entities in microbial cell walls and membranes. Fatty acids of chain length from Cg to C20 are useful for identifying Gram negative organisms at the species and genus levels. Perhaps the only automated GC-based microbial characterization system that is commercially available is a microbial analysis system based on derivatization GC of fatty acid methyl esters (Microbial ID, Inc., Newark, NJ). °... 

Holoman TRP, MA Elberson, LA Cutter, HD May, KR Sowers (1998) Characterization of a defined 2,3,5,6-tetrachlorobiphenyl-orffio-dechlorinating microbial community by comparative seqnence analysis of genes coding for 16S xRLihAppl Environ Microbiol 64 3359-3367. 

The complete four-component system is necessary when the diagnostic requirement is rapid, low unit-cost analysis for both the strain-level characterization of pathogenic agents and identification of hoax bio-terror materials. Using the complete system, we are proposing to validate MS-based microbial taxonomy and to transfer the technology from an analytical research to a clinical or public health production-diagnosis environment. 

The OUR is an activity-related quantitative measure of the aerobic biomass influence on the relationship between the electron donor (organic substrate) and the electron acceptor (dissolved oxygen, DO). It is a measure of the flow of electrons through the entire process system under aerobic conditions (Figure 2.2). The OUR versus time relationship of wastewater samples from sewers becomes a backbone for analysis of the microbial system. This relationship is crucial for characterization of the suspended wastewater phase in terms of COD components and corresponding kinetic and stoichiometric parameters of in-sewer processes. 

The L-rhamnulose 1-phosphate aldolase (RhuA EC 4.1.2.19) is found in the microbial degradation of L-rhamnose which, after conversion into the corresponding ketose 1-phosphate 44, is cleaved into 41 and L-lactaldehyde (l-16). The RhuA has been isolated from E. coli [336-339], and characterized as a metallo-protein [194,340,341]. Cloning was reported for the E. coli [342,343] and Salmonella typhimurium [344] genes, and construction of an efficient overexpression system [195,220] has set the stage for crystallization of the homotetrameric E. coli protein for the purposes of an X-ray structure analysis [345]. 

In a major study of the microbial metabolism of acronycine (177), Rosazza and co-workers examined 47 cultures for their capacity to transform this alkaloid, 10 of which were active in producing metabolites more polar than the starting material. The major metabolite was identified as the 9-hydroxy derivative 177 following isolation from the incubation of 176 with Cunninghamella echinulata NRRL 3655. This product was characterized as the acetate 182 by MS and PMR analysis, the latter technique... 

The published literature on the effects of microbial activities on wine chemical composition is now considerable. Understanding the significance of wine chemistry is, however, heavily dependent on complex analytical strategies which combine extensive chemical characterization and sensory descriptive analysis. However, sensory analysis is extremely resource-intense, requiring many hours of panelists time. This prevents widespread application of these powerful analytical tools. Advanced statistical techniques have been developed that are closing the gap between chemical and sensory techniques. Such techniques allow the development of models, which should ultimately provide a sensory description based on chemical data. For example, Smyth et al. (2005) have developed reasonable models which can reveal the most likely compounds that relate to particular attributes that characterise the overall sensory profile of a wine. For wines such as Riesling and Chardonnay, the importance of several yeast volatile compounds has been indicated. Such information will allow yeast studies to target key compounds better rather than just those that are convenient to measure. 

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