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Biochem Mol biol J

ISSN: 2471-8084

Volume 3, Issue 2

Metabolomics Conference 2017

August 29-30, 2017 Prague, Czech Republic



International Conference and Exhibition on

Metabolomics and Systems Biology


Page 24

Automated annotation of the wheat

metabolome during


infection using

stable isotopic labeling and custom-tailored

data processing workflows

Christoph Bueschl, Bernhard Kluger, Maria Doppler, Asja Ceranic,

Rudolf Krska


Rainer Schuhmacher

University of Natural Resources and Life Sciences, Austria


ungi of the genus


infect crop plants thereby

causing plant diseases and contamination of food with

its toxic secondary metabolites so-called mycotoxins. To

characterize the plant’s metabolic defense mechanisms to


infection, we have developed several analytical

protocols accompanied by custom-designed automated

data processing tools. The first workflow, entitled all

extract, is designed for the detection of all LC-HRMS

accessible metabolites of wheat. It uses either uniformly


C-labeled or


N-labeled wheat reference material, which

has been grown in-house and has an isotopic enrichment

of ~99%, for metabolite detection and annotation (~1.000

carbon- and ~300 nitrogen-containing metabolites).

Moreover, the


C-labeling step enables metabolome-

wide internal standardization thereby improving relative

quantification and subsequent statistical comparison

of the experimental groups. A second workflow, named

TracExtract, allows probing the metabolism of exogenous

or endogenous


C-labeled tracer compounds in wheat

plants and reports only biotransformation products that

the plant has produced from the respective tracer. Using

this approach, uniformly


C-labeled phenylalanine and

tryptophan tracers have been used to annotate respective

tracer-derived wheat biotransformation products (120 and

60 respectively). This annotation is especially helpful since

many of the already known defense-related metabolites in

wheat are descendants of these two tracer compounds.

Furthermore, the tracer approach was successfully used

to investigate the plant’s detoxification mechanisms


Fusarium graminearum

most potent mycotoxin

deoxynivalenol. A total of nine mostly novel detoxification

products were detected. Finally, all information about the

wheat metabolites is aggregated thus describing each

detected metabolite with its total number of carbon and

nitrogen atoms and if it is derived from phenylalanine or

tryptophan. This untargeted annotation is an invaluable

resource for further investigation of wheat-


interaction on a metabolic level and enables a more

focused investigation of potential novel defense-related



Christoph Bueschl is a Postdoctoral Researcher at Metabolomics group at

IFA-Tulln with expertise in automated data processing of LC-HRMS data. He

is specialized in data evaluation and software development of stable isotope

assisted and LC-HRMS based untargeted metabolomics experiments as

well as stable isotope assisted tracer experiments that probe the secondary

metabolism of either endogenous or exogenous secondary metabolites in

biological systems. His developed software tools are actively being used,

steadily improved and extended with new functionality and applied in various

projects and co-operations. Besides data processing of LC-HRMS data, one of

his research interests is statistical evaluation of large datasets especially in the

area of metabolomics research.

[email protected]

Christoph Bueschl et al., Biochem Mol biol J, 3:2

DOI: 10.21767/2471-8084-C1-002