Linked Life Data

15618299

Source:http://linkedlifedata.com/resource/pubmed/id/15618299

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
410
pubmed:dateCreated
2005-1-13
pubmed:abstractText
Filamentous fungi and yeast from the genera Saccharomyces, Penicillium, Aspergillus, and Fusarium are well known for their impact on our life as pathogens, involved in food spoilage by degradation or toxin contamination, and also for their wide use in biotechnology for the production of beverages, chemicals, pharmaceuticals, and enzymes. The genomes of these eukaryotic micro-organisms range from about 6000 genes in yeasts (S. cerevisiae) to more than 10,000 genes in filamentous fungi (Aspergillus sp.). Yeast and filamentous fungi are expected to share much of their primary metabolism; therefore much understanding of the central metabolism and regulation in less-studied filamentous fungi can be learned from comparative metabolite profiling and metabolomics of yeast and filamentous fungi. Filamentous fungi also have a very active and diverse secondary metabolism in which many of the additional genes present in fungi, compared with yeast, are likely to be involved. Although the 'blueprint' of a given organism is represented by the genome, its behaviour is expressed as its phenotype, i.e. growth characteristics, cell differentiation, response to the environment, the production of secondary metabolites and enzymes. Therefore the profile of (secondary) metabolites--fungal chemodiversity--is important for functional genomics and in the search for new compounds that may serve as biotechnology products. Fungal chemodiversity is, however, equally efficient for identification and classification of fungi, and hence a powerful tool in fungal taxonomy. In this paper, the use of metabolite profiling is discussed for the identification and classification of yeasts and filamentous fungi, functional analysis or discovery by integration of high performance analytical methodology, efficient data handling techniques and core concepts of species, and intelligent screening. One very efficient approach is direct infusion Mass Spectrometry (diMS) integrated with automated data handling, but a full metabolic picture requires the combination of several different analytical techniques.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0022-0957
pubmed:author
pubmed:issnType
Print
pubmed:volume
56
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
273-86
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Metabolite profiling of fungi and yeast: from phenotype to metabolome by MS and informatics.
pubmed:affiliation
Center for Microbial Biotechnology, BioCentrum-DTU, Technical University of Denmark, Søltofs Plads Building 221, DK-2800 Kgs Lyngby, Denmark. js@biocentrum.dtu.dk
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't