TITLE
Analyzing food ingredients by a novel APTA-SHAPE
technology
SHORT PROJECT DESCRIPTION
1$0($1'326,7,21
Asger Givskov Jørgensen, Phd student
START/END DATE
6/1/19 7/26/22
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TBA
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Participation in ENG-FOOD matchmaking November 24th 2020 - presentation "Analyzing food
ingredients by a novel APTA-SHAPE technology"
PICTURE RELATED TO THE PROJECT
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Main supervisor Prof Jørgen Kjems and co-supervisor
Ass. prof Daniel Dupont, Inano, AU. Research Scientist
Anders Hauge Okholm and Christian Sibbersen, Arla.
Prof Derek V. Byrne, Prof Lotte Bach Larsen and Ass.
prof Nina Aagaard Poulsen, Food Science, AU.
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(MAX. 200 WORDS IN TOTAL)
The project aims to establish a general and rapid
method for the molecular definition of ingredients
and contaminations in raw milk and consumer
products. The Ph.D. project will explore the
applicability of a recent in-house developed method,
APTA-SHAPE, define the molecular content in raw
milk and consumer products hereof to access
product source, quality, and food safety in milk
production. Selected examples are identifying and
analyzing molecular determinants for extended
shelf-life (e.g., Skyr) and product authentication (i.e.,
batch variation, origin, and cow species).
The APTA-SHAPE exploits the fact that short
single-stranded DNA or RNA oligonucleotides
(referred to as aptamers) can adopt a very large
variety of 3D shapes that, like antibodies, specifically
recognize and bind most ingredients in, for instance,
food including proteins, peptides, sugars and other
biological molecules. The number of sensor
molecules in the input aptamer library is extremely
high, exceeding 10E16 molecules, and individual
molecules can be addressed by established high
throughput sequencing methods applied to a subset
of the probes (approx. 10E8 molecules). The final
readout is generally based on thousands of
parameters. The preliminary results demonstrate
that APTA-SHAPE can characterize the molecular
definition of milk serum regarding kappa casein
genotype and identify the source of commercial milk
based on the samples' protein composition.
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RNA research, dairy research, proteomics, big data
processing, next generation sequencing
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Establishing biomarker for determining Skyr shelf-life,
cheese quality and mammary gland inflamation.
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