Microbial genomics

Modern sequencing technologies have opened our eyes to the world of bacteria, a world that was largely unknown to us only a decade ago. Whole genome sequencing generates a vast library of data, which requires bioinformaticians and statisticians to make sense of it. 

By studying microbial genomes, we can understand how bacteria change and evolve, and the role genetics plays in the properties they exhibit. This can lead to better methods to mitigate outbreaks of disease, or to potentially nurture the beneficial bacteria in our intestines.

At BIAS, we typically collaborate with other research groups, contributing our expertise in bioinformatics and applied statistics to various microbial projects.

Projects

The bacteria in the human gut

In close collaboration with the MidivLab at NMBU we use and develop methods in bioinformatics on both local and national High Performance Computing facilities to study the ecology of the microbes in the human gut. In the NFR-project UnveilMe we focus on the development of the bacteria in the infant gut, to understand how their production of short-chain fatty acids influence the developing immune system in children. In another collaboration with the company Genetic Analysis we have recently published the HumGut collection, a comprehensive database of the genomes found in the healthy human gut, also highlighted in Forskning.no. We have also been developing new methods using the Reduced Metagenome Sequencing approach to profile microbial communities.

Research articles related to these activities:

Hiseni P, Rudi K, Wilson RC, Hegge FT, Snipen L (2021). HumGut: a comprehensive human gut prokaryotic genomes collection filtered by metagenome data. Microbiome. 2021;9(1):165.

Snipen, L, Angell, IL, Rognes, T, Rudi, K (2021). Reduced Metagenome Sequencing for strain-resolution taxonomic profiles. Microbiome, Mar 29;9(1):79. doi: 10.1186/s40168-021-01019-8.

Nilsen M, Lokmic A, Angell IL, Lødrup Carlsen KC, Carlsen K, Haugen G, Hedlin G, Jonassen C, Marsland B, Nordlund B, Rehbinder E, Saunders C, Skjerven H, Snipen L, Staff A, Söderhäll C, Vettukattil M, Rudi K (2021). Fecal Microbiota Nutrient Utilization Potential Suggests Mucins as Drivers for Initial Gut Colonization of Mother-Child Shared Bacteria. Appl Environ Microbiol, Feb 26;87(6):e02201-20. doi: 10.1128/AEM.02201-20.

Nilsen M, Saunders  CM, Angell IL, Arntzen MØ, Lødrup Carlsen KC, Carlsen K, Haugen G, Hagen LH, Carlsen MH, Hedlin G, Jonassen CM, Nordlund B, Rehbinder EM, Skjerven HO, Snipen L, Staff AC, Vettukattil R, Rudi K. (2020). Butyrate Levels in the Transition from an Infant- to an Adult-Like Gut Microbiota Correlate with Bacterial Networks Associated with Eubacterium rectale and Ruminococcus gnavus. Genes, 11(11):1245.

 Using microbial data in forensics

How old is a biological trace from a crime scene? Is the biological trace found at a crime scene from blood, semen, saliva or other human body fluids? These questions may be answered by clever use of algorithms in bioinformatics and statistics after sequencing the DNA of the bacteria in such trace material. Our collaboration on this topic is with the Institute of Forensic Medicine at the University of Zurich, and with the Department of Forensic Sciences at Oslo University Hospital.

For further reading, check out the following research articles:

Salzmann, AP, Aroa, N, Russo, G, Kreutzer, S, Snipen, L, Haas, C (2021). Assessing time dependent changes in microbial composition of biological crime scene traces using microbial RNA markers. Forensics International: Genetics. 53

Dørum G, Ingold S, Hanson E, Ballantyne J, Russo G, Aluri S, Snipen L, Haas C (2019). Predicting the origin of stains from whole miRNome massively parallel sequencing data. Forensic Science International: Genetics. 40:131-139.

HanssenE.N.LilandK.H., Gill, P., SnipenL. (2018). Optimizing body fluid recognition from microbial taxonomic profilesForensic Science International: Genetics, 37: 13–20. doi: 10.1016/j.fsigen.2018.07.012   

HanssenE.N., Avershina, E., Rudi, K., Gill, P., Snipen, L. (2017). Body fluid prediction from microbial patterns for forensic application. Forensic Science International: Genetics, 30: 10–17. doi: 10.1016/j.fsigen.2017.05.009 

Using bioinformatics to save the oceans

In the newly started NFR-project Aquaed we are going to use modern long-read sequencing technology to classify the seafloor sediments related to the aquaculture industry. One aim is to improve the system for surveillance of the environmental conditions that surround aquaculture production facilities. This also involves a number of partners in the aquaculture industry.

Published 29. October 2019 - 10:58 - Updated 17. September 2021 - 14:24