Microbial analysis

Maraz, A. et al.. Microbial analysis of food, in Safety in Agri-food Chains, Luning, P.A., DeVlieghere, R, and Verhe, R., Eds., Wageningen Academic Publishers, Wageningen, 2006, 471. 

It follows that for routine purposes, the ideal method for microbial analysis would include the following criteria ... 

Due to the mainly qualitative nature of PCA, DFA, and HCA, the role of PyMS in microbiology has been somewhat restricted. For example, using these clustering methods, the use of PyMS to identify microorganisms can be a subjective process because it relies on the interpretation of complex scatter plots and dendrograms. Furthermore the qualitative nature of PCA, DFA, and FICA prevents the application of PyMS to quantitative microbial analysis, while limitations also arise from batch-to-batch variation of PyMS data.80... 

Fig. 10.2 Variability in resolution of tools of microbial analysis (Adopted from Nannipieri et al. 2003). Shades represents the resolution darker the shade more the resolution and vice versa...

Applications of Raman Spectroscopy to Virology and Microbial Analysis... 

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]. 

Kennedy, A. C. and Busaca, A. J. (1995). Microbial analysis to identify source of PM-10 material, in Proceedings of the Air and Waste Management Association Specialty Conference on Particulate Matter Health and Regulatory Issues. Williams Wilkins, Pittsburgh, PA, 670-675. 

Banters TGM, Swinne D, Stove V, NeUs HI (2003) Detection of single cells of Cryptococcus neoformans in clinical samples by sohd-phase cytometry. 1 Clin Microbiol 41 1736-1737 BraUsford M (1996) Real-time microbial analysis of pharmaceutical water. Microbiol Eur 4 18-20 Brailsford M (1997a) Making the switch to real-time microbiological process control. Manuft Chemist (March) 3 5-36... 

In short. E-nose integrated with chemometrics is a reliable, rapid, and economic technique which could be explored as a routine diagnostic tool for microbial analysis. 

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). °... 

During operation of the bioreactors, samples were collected for the analysis of key operating parameters, such as dissolved oxygen, nutrient levels, total organic carbon and suspended solids. Microbial analysis was performed to assess the cell concentration of the specialized bacteria being added. All cultures were prepared in advance and added to the bioreactors. Additional samples were collected to measure the contaminant concentration across the bioreactor, as well as in the various portions of the treatment system, in order to calculate a mass balance. 

Fig. 3.1 Workflow of sample preparation approaches for microbial analysis. MS mass spectrometry...

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. 

Electrochemical biosensors have some advantages over other analytical systems in that they can operate in turbid media, offer comparable instrumental sensitivity, and are more amenable to miniaturization. Modem electroanalytical techniques have very low detection limits (typically 10" M) that can be achieved using small volumes (1-20 p,l) of samples. Furthermore, the continuous response of an electrode system allows for on-line control and the equipment required for electrochemical analysis is simple and cheap compared to most other analytical technique. Amperometric immunosensors aimed at microbial analysis have recently been report (14-20) including some immunomagnetic bead technology (19-21). 

Previously, microbial population analysis was based on enrichment and cultivation techniques. It has become clear that plate counts very often do not represent the true microhial community, as many strains are resistant to cultivation. Microbial analysis has become much more reliable (and easier) due to the development of noncultivation techniques. Owing to the relative ease of molecular techniques, many data are collected from a wide variety of microbial communities however, the role of the detected populations is often not known. This can be attributed to the difficulty of functional analysis of complex communities the conversions of a community can be measured, but it is difficult and often impossible to assign the conversion to certain populations. However, there are some exceptions. Some microbial populations can be analyzed with a combination of microsensor and molecular techniques. Then, it is possible to determine the location of certain microbial processes (with microsensors) and to determine the location of certain microbial populations (with fluorescent in situ hybridization, FISH). Comparing these data can lead to estimations of activities and kinetics of populations in situ. 

Similarly, Atlantic cod fry were fed with feed containing a LAB isolated from Atlantic cod Gadus morhua (Gildberg et ai, 1997). After three weeks of feeding the fry were exposed to a virulent strain of Vibrio anguillarum. Three weeks after challenge, surviving fish were taken for microbial analysis by the same method mentioned above except that the intestinal contents were analyzed for microbial culturable counts. The intestine from fish fed with LAB had a virtual monoculture of LAB, whereas the intestine of control fish had a mixed microbiota. As the intestinal content from control fish also contained Pseudomonas-VkQ bacteria, it was concluded that the LAB had displaced other potential colonizers. 

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