Dr. Wei Wang from the Liu team succefully defended her Ph.D. dissertation in October 2021. Her thesis is titled “”Computational Frameworks for Indel-Aware Evolutionary Analysis Using Large-Scale Genomic Sequence Data”. She has accepted an offer to join Meta Platforms Inc. (formerly known as Facebook Inc.). Congratulations Wei!
The Liu and Bonito labs have created a new method for scalable statistical inference of phylogenetic networks from large-scale genomic sequence datasets. The new method has been published as part of peer-reviewed proceedings of RECOMB-CG 2018. The publication can be accessed here.
In related work, members of the Liu lab have developed a novel non-parametric/semi-parametric method for statistical support estimation. The approach has initially been applied to classical problems in computational biology and bioinformatics. The work was also published as part of peer-reviewed proceedings of RECOMB-CG 2018. The publication can be accessed here. An extended journal paper has been submitted to Algorithms for Molecular Biology.
Check out the latest paper and press release on our research into physiological interactions between a synthetic consortium of the marine alga, Nannochloropsis oceanica, and the terrestrial fungus, Mortierella elongata. These organisms interact in ways that boost their oil production that can be harvested for human use in biofuels, nutrition, cosmetics and biotechnology.
“Engineering modular diterpene biosynthetic pathways in Physcomitrella patens” by Aparajita Banerjee, Jonathan A. Arnesen, Daniel Moser*, Balindile B. Motsa*, Sean R. Johnson, and Bjoern Hamberger (*outstanding undergraduate students of the team)
Published November 26th, 2018: DOI 10.1007/s00425-018-3053-0
Industrial interest in diterpenoids stems from equally broad applications such as renewable feedstocks, inks, tackifiers, flavors and nutraceuticals, fragrances, and on the far end of the value-spectrum, therapeutics. However, access to these biomaterials is limited by the native sources, where they often accumulate as part of complex mixtures of related but undesired compounds, or because formal (petro)-chemical synthesis is an economic and environmental challenge.
This study driven by postdoc Aparajita Banerjee and MSc student Jonathan Arnesen, members of the Hamberger team (Department of Biochemistry and Molecular Biology, MSU) investigated the installation of modern pathways to higher plant specialized metabolites, diterpenes, in the ancient land plant lineage, the moss Physcomitrella. From biotechnological perspective Physcomitrella is an intriguing system, as the lineage is 450 MY old and evolution of even simple terpenes, such as the ubiquitous phytohormones Gibberellic acid, has not happened yet. Also, like in yeast, or mice, genome editing is conveniently done by homologous recombination, which is not feasible in any other plant.
Figure: Terpene production in stably engineered plant system.
From left to right:
These features prompted the team to develop a modular plug & play system to equip Physcomitrella in stably transformed lines with several pathways to modern terpenes by targeted genome engineering. These now accumulate modern land plant diterpenes. And just because it was hypothetically possible, Banerjee and Arnesen went a step further, targeting highly abundant long-terminal retro-transposons, considered “selfish” copy-and-paste DNA elements making up about half of the Physcomitrella genome, and also common in higher plants. While the fluorescent marker landed right in the retroelement locus, the far more advanced terpene pathways revealed that this new system is more complex and will need more work than initially anticipated.
A true dimension of Biodiversity: fungi growing inside the cells of plants. The moss in this image is from an experiment being conducted by Davis Mathieu (Hamberger) and Abigail Bryson (Bonito). The moss pictured here, Physcomitrella patens, was grown for six weeks with Mortierella sp. The moss tissue was cleared overnight using 10% KOH and then stained with Cotton Blue, a chitin stain. This image is 1000X.