Metabolomics of Endophytic Fungi Producing Associated Plant Secondary Metabolites: Progress, Challenges and Opportunities

By S. Kusari, M. Spiteller. 2012

109 citations recorded by the source corpus.

Microorganisms are indispensable for every aspect of human life, in fact all life on earth, although they cannot be seen by the naked eye. Since time immemorial, every process in the biosphere has been affected by the apparently unending ability of microbes to renovate the world around them. More recently, many discoveries have been made in isolating a special class of microorganisms, mainly fungi but also bacteria, commonly called endophytes, which have been shown to have the natural potential for accumulation of various bioactive metabolites which may directly or indirectly be used as therapeutic agents against a plethora of maladies (Kusari & Spiteller, 2010, 2011). Bioprospecting endophytes have led to exciting possibilities to explore and utilize their potential. Several bioprospecting strategies might be employed in order to discover potent endophytes with desirable traits (Figure 1). These include randomly sampling different plants from any population to isolate the associated endophytes, or first performing a detailed study of an ecosystem in order to determine its features with regard to its natural population of plant species, their relationship with the environment, soil composition, and biogeochemical cycles. Another approach is to evaluate the evolutionary relatedness among groups of plants at a particular sampling site, correlating to species, genus, and populations, through morphological data matrices and molecular sequencing, followed by isolation of endophytes from the desired plants. Traditional medicinal plants are also bioprospected for endophytes, especially for the ones capable of producing one or more of the bioactive secondary metabolites present in the host plants. Finally, the valuable information obtained using the different bioprospecting schemes can be pooled together, comparatively evaluated, and stored for further use applying suitable data mining approaches.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/4e07a4e012099037481726cf5e698ddd4ca15059

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In Molecular Biology

  1. M. Watt
  2. Ute Roessner
  3. O. Kayser
  4. P. Kusari
  5. S. Kusari
  6. M. Spiteller
  7. Oliver Fiehn

In Pharmacology

  1. O. Kayser
  2. P. Kusari
  3. S. Kusari
  4. M. Spiteller
  5. Ute Roessner

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