Microbial analysis identification

Though especially the cultural parameters of the studied cells have a huge impact on their signature variability it seems that - a decent Raman signature library provided - the majority of cultivation differences can be accommodated and thus no extreme standardization of culturing conditions is required for identification via this method. But for the sake of taxonomic resolution care has to be taken in finding appropriate culturing conditions to affect the implementation possibilities of Raman spectroscopy in microbial analysis positively [43]. 

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). °... 

Currently, most of the rapid microbial analyses are based on MALDl techniques. Selecting an optimal matrix is a cracial step in developing all of the sample preparation protocols for the MALDI-MS. The MALDl matrices that are frequently used for microbial analysis are a-cyano-4-hydroxycinnamic acid (CHCA), feralic acid (FA), and sinapinic acid (SA). It has been demonstrated that the use of a different matrix for the same kind of sample led to a significant change in the MALDl mass spectrum. For example, the MALDl mass spectra of E. coli obtained with CHCA and a mixture of SA/4-methoxycinnamic acid showed significantly different signals (Demirev et al. 1999). CHCA is one of the most common matrix for bacterial identification. 

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. 

Use of an integrated system incorporating CCC separation, PDA detector, and LC-MS proved to be a valuable tool in the rapid identification of known compounds from microbial extracts.6 This collection of analytical data has enabled us to make exploratory use of advanced data analysis methods to enhance the identification process. For example, from the UV absorbance maxima and molecular weight for the active compound(s) present in a fraction, a list of potential structural matches from a natural products database (e.g., Berdy Bioactive Natural Products Database, Dictionary of Natural Products by Chapman and Hall, etc.) can be generated. Subsequently, the identity of metabolite(s) was ascertained by acquiring a proton nuclear magnetic resonance ( H-NMR) spectrum. 

Because of minimal sample preparation and minimally invasive approaches Raman spectroscopy has the potential to gain new insights into viral and microbial biochemistry as well as a rapid identification of pathogenic microorganisms. In this chapter the unique potential of several Raman spectroscopic techniques for medical and pharmaceutical issues is discussed, which focus on the analysis of viruses as well as on microbial detection... 

Culture-independent methods of soil microbial community analysis include methods based on (1) the extraction, quantification, and identification... 

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