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BacIL - En Bioinformatisk Pipeline för Analys av Bakterieisolat
2019 (Swedish)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesisAlternative title
BacIL - A Bioinformatic Pipeline for Analysis of Bacterial Isolates (English)
Abstract [en]

Listeria monocytogenes and Campylobacter spp. are bacteria that sometimes can cause severe illness in humans. Both can be found as contaminants in food that has been produced, stored or prepared improperly, which is why it is important to ensure that the handling of food is done correctly. The National Food Agency (Livsmedelsverket) is the Swedish authority responsible for food safety. One important task is to, in collaboration with other authorities, track and prevent food-related disease outbreaks. For this purpose bacterial samples are regularly collected from border control, at food production facilities and retail as well as from suspected food items and drinking water during outbreaks, and epidemiological analyses are employed to determine the type of bacteria present and whether they can be linked to a common source.

One part of these epidemiological analyses involve bioinformatic analyses of the bacterial DNA. This includes determination of sequence type and serotype, as well as calculations of similarities between samples. Such analyses require data processing in several different steps which are usually performed by a bioinformatician using different computer programs. Currently the National Food Agency outsources most of these analyses to other authorities and companies, and the purpose of this project was to develop a pipeline that would allow for these analyses to be performed in-house.

The result was a pipeline named BacIL - Bacterial Identification and Linkage which has been developed to automatically perform sequence typing, serotyping and SNP-analysis of Listeria monocytogenes as well as sequence typing and SNP-analysis of Campylobacter jejuni, C. coli and C. lari. The result of the SNP-analysisis is used to create clusters which can be used to identify related samples. The pipeline decreases the number of programs that have to be manually started from more than ten to two.

Place, publisher, year, edition, pages
2019. , p. 43
Series
UPTEC X ; 19027
Keywords [sv]
bioinformatik, pipeline
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-388087OAI: oai:DiVA.org:uu-388087DiVA, id: diva2:1331534
External cooperation
Livsmedelsverket
Educational program
Molecular Biotechnology Engineering Programme
Supervisors
Examiners
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-27Bibliographically approved

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Bioinformatics (Computational Biology)

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