Mass spectral database

JICST/JOIS. The Japan Information Center for Science and Technology (fICST) Mass Spectral Database is accessible to users in Japan through the JICST Eactual Database System (fOlS-E). The database uses the NIST/EPA/ MSCD data collection supplemented by spectra from the Mass Spectrometry Society of Japan (84). 

Variations on the spectral peaks from different species of the same genus were also observed. Three species of Pseudomonas produced the spectra shown in Figure 14.2. These spectra are clearly unique and were used to correctly identify unknown samples. Because of peak ratio reproducibility issues in bacterial protein profiles obtained by MALDI MS,11 a fingerprint approach that had been used for other mass spectrometry approaches has not been used. The profile reproducibility problem was first recognized by Reilly et al.12,13 and later researched by others in the field.14,15 As a later alternative, a direct comparison of the mass-to-charge ratio (m/z) of the unknown mass spectral peaks with a database of known protein masses has been used to identify unknown samples.14... 

For PyMS to be used for (1) routine identification of microorganisms and (2) in combination with ANNs for quantitative microbiological applications, new spectra must be comparable with those previously collected and held in a data base.127 Recent work within our laboratory has demonstrated that this problem may be overcome by the use of ANNs to correct for instrumental drift. By calibrating with standards common to both data sets, ANN models created using previously collected data gave accurate estimates of determi-nand concentrations, or bacterial identities, from newly acquired spectra.127 In this approach calibration samples were included in each of the two runs, and ANNs were set up in which the inputs were the 150 new calibration masses while the outputs were the 150 old calibration masses. These associative nets could then by used to transform data acquired on that one day to data acquired at an earlier data. For the first time PyMS was used to acquire spectra that were comparable with those previously collected and held in a database. In a further study this neural network transformation procedure was extended to allow comparison between spectra, previously collected on one machine, with spectra later collected on a different machine 129 thus calibration transfer by ANNs was affected. Wilkes and colleagues130 have also used this strategy to compensate for differences in culture conditions to construct robust microbial mass spectral databases. 

Eng, J., McCormack, A.L., Yates, J.R., III (1994). An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Amer. Mass. Spectrom. 5, 976-989. 

Field, H.I., Fenyo, D., Beavis, R.C. (2002). RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database. Proteomics 2, 36 17. 

H. I. Field, D. Fenyo, and R. C. Beavis. RADARS, a Bioinformatics Solution that Automates Proteome Mass Spectral Analysis, Optimises Protein Identification, and Archives Data in a Relational Database. Proteomics, 2, no. 1 (2002) 36-47. 

METLIN Metabolite Database (http //metlin.scripps.edu), a repository for mass spectral metabolite data. Each metabolite has a link to the Kyoto Encyclopedia of Genes and Genomes. 

S.R. Heller, The history of the NIST/EPA/NIH mass spectral database, Today s Chemist at Work, 8(2) (1999) 45-50. 

C. Wagner, M. Sefkow, and J. Kopka, Construction and application of a mass spectral and retention time index database generated from plant GC/EI TOF MS metabolite profiles. 

NIST Mass Spectral Database 98. National Institute of Standards and Technology, www.nist. gov/srd/nistla.htm, Gaithersburg, MD, 1998. 

This assures better reproducibility of spectra, and therefore allows comparison of spectra obtained from different mass spectrometers or from mass spectral databases (Chap 5.7). 

Provided El spectra have been measured under some sort of standard conditions (70 eV, ion source at 150-250 °C, pressure in the order of 10 " Pa), they exhibit very good reproducibility. This is not only the case for repeated measurements on the same instrument, but also between mass spectrometers having different types of mass analyzers, and/or coming from different manufacturers. This property soon led to the collection of large El mass spectral libraries, either printed [76-78] or computerized. [79] The best established El mass spectral databases are the NIST/EPA/NIH Mass Spectral Database and the Wiley/NBS Mass Spectral Database, each of them giving access to about 120,000 evaluated spectra. [80-83]... 

GC/MS was the primary tool for identifying the first DBFs, and it remains an important tool for measuring and identifying new DBFs. Large mass spectral libraries (NIST and Wiley databases, which contain >200,000 spectra) enable rapid identifications. When DBFs are not present in these databases, high-resolution... 

Electronic databases of the mass spectral fragmentation patterns of known molecules can be rapidly searched by computer. The pattern and intensity of fragments in the mass spectrum is characteristic of an individual compound so comparison of the experimental mass spectrum of a compound with those in a library can be used to positively identify it, if its spectrum has been recorded previously. 

The comparison can be made manually on the basis of collections of tables (for example, A. Cornu R. Massot Compilation of Mass Spectral Data) or may be effected with computer assistance large databases can be used (e.g. Mass Spectral Data Base, Royal Society of Chemistry, Cambridge). 

Figure 22-6 Electron ionization (70 eV) mass spectra of molecular ion region of benzene (C4H6) and biphenyl (C,2H,0). [From Nisr/EPA/NIH Mass Spectral Database...

Figure 22-10 Election ionization (70 eV) mass spectra of isomeric ketones with the Composition C4H,20. [From NIST/EPA/MH Mass Spectral Database.8]...

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