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Identifying Microbes by Mass Spectrometry Proteomics (Paperback)
Loot Price: R2,507
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Identifying Microbes by Mass Spectrometry Proteomics (Paperback)
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All microbes, including bacteria, viruses, and fungi, can be
classified and identified by matching a few peptides known to be
unique to each organism. Identifying Microbes by Mass Spectrometry
Proteomics describes ways to identify microorganisms using powerful
new techniques combining hardware and software and yielding highly
accurate methods for detection, identification, and classification
of microbes. This straightforward technology can be used to detect
unknown and unsequenced microorganisms as well as microbes in
complex environmental samples. This book reviews various mass
analyzers used for detection and describes ionization methods
frequently used for analysis of microbial constituents, a necessary
step in the preparation of mass spectrometry (MS) samples. The text
also discusses diverse processing methods, which are used to
analyze MS files for matching mass spectral profiles, and examines
protein and nucleic acid sequence-based methods capable of
classification and identification of microbial agents. The book
also covers sample collection methods and specific sample
preparation techniques. The text addresses using computer software
and bioinformatics approaches for data mining to discriminate
microbes using mass spectrometry proteomics (MSP). It also
discusses historical pattern recognition-based methods and other
approaches such as analysis of pyrolysis products, chemical
ionization (CI) of fatty acid methyl esters, and MALDI-MS. The text
contains examples of the application of the MSP technique for
microbe detection and includes a survey of suitable and
commercially available MS-based platforms. Successful applications
include the identification of unknown microbes in honey bees
associated with colony collapse disorder and the analysis of virus
strains from the 2009 influenza pandemic. The final chapter
outlines future trends in these groundbreaking uses of MS
techniques, which are fast, not limited by sample type, and show
potential in answering complex environmental questions.
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